From 7e55a51314e6e59ee64e9802fd34bfdc692c1350 Mon Sep 17 00:00:00 2001
From: explosion-bot <explosion-bot@users.noreply.github.com>
Date: Fri, 1 Jul 2022 08:04:32 +0000
Subject: [PATCH 001/174] Auto-format code with black

---
 spacy/tests/matcher/test_matcher_api.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/spacy/tests/matcher/test_matcher_api.py b/spacy/tests/matcher/test_matcher_api.py
index 2c2af6ce5..7c16da9f8 100644
--- a/spacy/tests/matcher/test_matcher_api.py
+++ b/spacy/tests/matcher/test_matcher_api.py
@@ -685,8 +685,8 @@ def test_matcher_ent_iob_key(en_vocab):
 def test_matcher_min_max_operator(en_vocab):
     # Exactly n matches {n}
     doc = Doc(
-        en_vocab, words=["foo", "bar", "foo", "foo", "bar",
-                         "foo", "foo", "foo", "bar", "bar"]
+        en_vocab,
+        words=["foo", "bar", "foo", "foo", "bar", "foo", "foo", "foo", "bar", "bar"],
     )
     matcher = Matcher(en_vocab)
     pattern = [{"ORTH": "foo", "OP": "{3}"}]

From 59c763eec171e9285b39e793baa2cfbf2ccd48d7 Mon Sep 17 00:00:00 2001
From: Madeesh Kannan <shadeMe@users.noreply.github.com>
Date: Mon, 4 Jul 2022 15:04:03 +0200
Subject: [PATCH 002/174] `StringStore`-related optimizations (#10938)

* `strings`: More roubust type checking of keys/IDs, coerce `int`-like types to `hash_t`

* Preserve existing public API behaviour

* Fix return type

* Replace `bool` with `bint`, rename to `_try_coerce_to_hash`, replace `id` with `hash`

* Avoid unnecessary re-encoding and re-calculation of strings and hashs respectively

* Rename variables named `hash`
Add comment on early return
---
 spacy/strings.pxd |   2 +-
 spacy/strings.pyx | 135 ++++++++++++++++++++++++++++------------------
 2 files changed, 83 insertions(+), 54 deletions(-)

diff --git a/spacy/strings.pxd b/spacy/strings.pxd
index 370180135..5f03a9a28 100644
--- a/spacy/strings.pxd
+++ b/spacy/strings.pxd
@@ -26,4 +26,4 @@ cdef class StringStore:
     cdef public PreshMap _map
 
     cdef const Utf8Str* intern_unicode(self, str py_string)
-    cdef const Utf8Str* _intern_utf8(self, char* utf8_string, int length)
+    cdef const Utf8Str* _intern_utf8(self, char* utf8_string, int length, hash_t* precalculated_hash)
diff --git a/spacy/strings.pyx b/spacy/strings.pyx
index 39fc441e9..c5f218342 100644
--- a/spacy/strings.pyx
+++ b/spacy/strings.pyx
@@ -14,6 +14,13 @@ from .symbols import NAMES as SYMBOLS_BY_INT
 from .errors import Errors
 from . import util
 
+# Not particularly elegant, but this is faster than `isinstance(key, numbers.Integral)`
+cdef inline bint _try_coerce_to_hash(object key, hash_t* out_hash):
+    try:
+        out_hash[0] = key
+        return True
+    except:
+        return False
 
 def get_string_id(key):
     """Get a string ID, handling the reserved symbols correctly. If the key is
@@ -22,15 +29,27 @@ def get_string_id(key):
     This function optimises for convenience over performance, so shouldn't be
     used in tight loops.
     """
-    if not isinstance(key, str):
-        return key
-    elif key in SYMBOLS_BY_STR:
-        return SYMBOLS_BY_STR[key]
-    elif not key:
-        return 0
+    cdef hash_t str_hash    
+    if isinstance(key, str):
+        if len(key) == 0:
+            return 0
+
+        symbol = SYMBOLS_BY_STR.get(key, None)
+        if symbol is not None:
+            return symbol
+        else:
+            chars = key.encode("utf8")
+            return hash_utf8(chars, len(chars))
+    elif _try_coerce_to_hash(key, &str_hash):
+        # Coerce the integral key to the expected primitive hash type.
+        # This ensures that custom/overloaded "primitive" data types
+        # such as those implemented by numpy are not inadvertently used 
+        # downsteam (as these are internally implemented as custom PyObjects 
+        # whose comparison operators can incur a significant overhead).
+        return str_hash
     else:
-        chars = key.encode("utf8")
-        return hash_utf8(chars, len(chars))
+        # TODO: Raise an error instead
+        return key
 
 
 cpdef hash_t hash_string(str string) except 0:
@@ -110,28 +129,36 @@ cdef class StringStore:
         string_or_id (bytes, str or uint64): The value to encode.
         Returns (str / uint64): The value to be retrieved.
         """
-        if isinstance(string_or_id, str) and len(string_or_id) == 0:
-            return 0
-        elif string_or_id == 0:
-            return ""
-        elif string_or_id in SYMBOLS_BY_STR:
-            return SYMBOLS_BY_STR[string_or_id]
-        cdef hash_t key
+        cdef hash_t str_hash
+        cdef Utf8Str* utf8str = NULL
+
         if isinstance(string_or_id, str):
-            key = hash_string(string_or_id)
-            return key
-        elif isinstance(string_or_id, bytes):
-            key = hash_utf8(string_or_id, len(string_or_id))
-            return key
-        elif string_or_id < len(SYMBOLS_BY_INT):
-            return SYMBOLS_BY_INT[string_or_id]
-        else:
-            key = string_or_id
-            utf8str = <Utf8Str*>self._map.get(key)
-            if utf8str is NULL:
-                raise KeyError(Errors.E018.format(hash_value=string_or_id))
+            if len(string_or_id) == 0:
+                return 0
+
+            # Return early if the string is found in the symbols LUT.
+            symbol = SYMBOLS_BY_STR.get(string_or_id, None)
+            if symbol is not None:
+                return symbol
             else:
-                return decode_Utf8Str(utf8str)
+                return hash_string(string_or_id)
+        elif isinstance(string_or_id, bytes):
+            return hash_utf8(string_or_id, len(string_or_id))
+        elif _try_coerce_to_hash(string_or_id, &str_hash):
+            if str_hash == 0:
+                return ""
+            elif str_hash < len(SYMBOLS_BY_INT):
+                return SYMBOLS_BY_INT[str_hash]
+            else:
+                utf8str = <Utf8Str*>self._map.get(str_hash)
+        else:
+            # TODO: Raise an error instead
+            utf8str = <Utf8Str*>self._map.get(string_or_id)
+
+        if utf8str is NULL:
+            raise KeyError(Errors.E018.format(hash_value=string_or_id))
+        else:
+            return decode_Utf8Str(utf8str)
 
     def as_int(self, key):
         """If key is an int, return it; otherwise, get the int value."""
@@ -153,19 +180,22 @@ cdef class StringStore:
         string (str): The string to add.
         RETURNS (uint64): The string's hash value.
         """
+        cdef hash_t str_hash
         if isinstance(string, str):
             if string in SYMBOLS_BY_STR:
                 return SYMBOLS_BY_STR[string]
-            key = hash_string(string)
-            self.intern_unicode(string)
+
+            string = string.encode("utf8")
+            str_hash = hash_utf8(string, len(string))
+            self._intern_utf8(string, len(string), &str_hash)
         elif isinstance(string, bytes):
             if string in SYMBOLS_BY_STR:
                 return SYMBOLS_BY_STR[string]
-            key = hash_utf8(string, len(string))
-            self._intern_utf8(string, len(string))
+            str_hash = hash_utf8(string, len(string))
+            self._intern_utf8(string, len(string), &str_hash)
         else:
             raise TypeError(Errors.E017.format(value_type=type(string)))
-        return key
+        return str_hash
 
     def __len__(self):
         """The number of strings in the store.
@@ -174,30 +204,29 @@ cdef class StringStore:
         """
         return self.keys.size()
 
-    def __contains__(self, string not None):
-        """Check whether a string is in the store.
+    def __contains__(self, string_or_id not None):
+        """Check whether a string or ID is in the store.
 
-        string (str): The string to check.
+        string_or_id (str or int): The string to check.
         RETURNS (bool): Whether the store contains the string.
         """
-        cdef hash_t key
-        if isinstance(string, int) or isinstance(string, long):
-            if string == 0:
+        cdef hash_t str_hash
+        if isinstance(string_or_id, str):
+            if len(string_or_id) == 0:
                 return True
-            key = string
-        elif len(string) == 0:
-            return True
-        elif string in SYMBOLS_BY_STR:
-            return True
-        elif isinstance(string, str):
-            key = hash_string(string)
+            elif string_or_id in SYMBOLS_BY_STR:
+                return True
+            str_hash = hash_string(string_or_id)
+        elif _try_coerce_to_hash(string_or_id, &str_hash):
+            pass
         else:
-            string = string.encode("utf8")
-            key = hash_utf8(string, len(string))
-        if key < len(SYMBOLS_BY_INT):
+            # TODO: Raise an error instead
+            return self._map.get(string_or_id) is not NULL
+
+        if str_hash < len(SYMBOLS_BY_INT):
             return True
         else:
-            return self._map.get(key) is not NULL
+            return self._map.get(str_hash) is not NULL
 
     def __iter__(self):
         """Iterate over the strings in the store, in order.
@@ -272,13 +301,13 @@ cdef class StringStore:
     cdef const Utf8Str* intern_unicode(self, str py_string):
         # 0 means missing, but we don't bother offsetting the index.
         cdef bytes byte_string = py_string.encode("utf8")
-        return self._intern_utf8(byte_string, len(byte_string))
+        return self._intern_utf8(byte_string, len(byte_string), NULL)
 
     @cython.final
-    cdef const Utf8Str* _intern_utf8(self, char* utf8_string, int length):
+    cdef const Utf8Str* _intern_utf8(self, char* utf8_string, int length, hash_t* precalculated_hash):
         # TODO: This function's API/behaviour is an unholy mess...
         # 0 means missing, but we don't bother offsetting the index.
-        cdef hash_t key = hash_utf8(utf8_string, length)
+        cdef hash_t key = precalculated_hash[0] if precalculated_hash is not NULL else hash_utf8(utf8_string, length)
         cdef Utf8Str* value = <Utf8Str*>self._map.get(key)
         if value is not NULL:
             return value

From 6c036d1e2595afd250829b64dba1ca609f9e536b Mon Sep 17 00:00:00 2001
From: schaeran <schaeran1994@gmail.com>
Date: Mon, 4 Jul 2022 16:03:30 +0200
Subject: [PATCH 003/174] remove universe object: spacy_hunspell

---
 website/meta/universe.json | 26 --------------------------
 1 file changed, 26 deletions(-)

diff --git a/website/meta/universe.json b/website/meta/universe.json
index ab64fe895..2cf12d51e 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -888,32 +888,6 @@
                 "github": "shigapov"
             }
         },
-        {
-            "id": "spacy_hunspell",
-            "slogan": "Add spellchecking and spelling suggestions to your spaCy pipeline using Hunspell",
-            "description": "This package uses the [spaCy 2.0 extensions](https://spacy.io/usage/processing-pipelines#extensions) to add [Hunspell](http://hunspell.github.io) support for spellchecking.",
-            "github": "tokestermw/spacy_hunspell",
-            "pip": "spacy_hunspell",
-            "code_example": [
-                "import spacy",
-                "from spacy_hunspell import spaCyHunSpell",
-                "",
-                "nlp = spacy.load('en_core_web_sm')",
-                "hunspell = spaCyHunSpell(nlp, 'mac')",
-                "nlp.add_pipe(hunspell)",
-                "doc = nlp('I can haz cheezeburger.')",
-                "haz = doc[2]",
-                "haz._.hunspell_spell  # False",
-                "haz._.hunspell_suggest  # ['ha', 'haze', 'hazy', 'has', 'hat', 'had', 'hag', 'ham', 'hap', 'hay', 'haw', 'ha z']"
-            ],
-            "author": "Motoki Wu",
-            "author_links": {
-                "github": "tokestermw",
-                "twitter": "plusepsilon"
-            },
-            "category": ["pipeline"],
-            "tags": ["spellcheck"]
-        },
         {
             "id": "spacy_grammar",
             "slogan": "Language Tool style grammar handling with spaCy",

From 880e7db44e73a3f20d9166039725d3c5e58b5b9e Mon Sep 17 00:00:00 2001
From: schaeran <schaeran1994@gmail.com>
Date: Mon, 4 Jul 2022 16:04:06 +0200
Subject: [PATCH 004/174] remove universe object: spacy_grammar

---
 website/meta/universe.json | 22 ----------------------
 1 file changed, 22 deletions(-)

diff --git a/website/meta/universe.json b/website/meta/universe.json
index 2cf12d51e..f51f2cd88 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -888,28 +888,6 @@
                 "github": "shigapov"
             }
         },
-        {
-            "id": "spacy_grammar",
-            "slogan": "Language Tool style grammar handling with spaCy",
-            "description": "This packages leverages the [Matcher API](https://spacy.io/docs/usage/rule-based-matching) in spaCy to quickly match on spaCy tokens not dissimilar to regex. It  reads a `grammar.yml` file to load up custom patterns and returns the results inside `Doc`, `Span`, and `Token`. It is extensible through adding rules to `grammar.yml` (though currently only the simple string matching is implemented).",
-            "github": "tokestermw/spacy_grammar",
-            "code_example": [
-                "import spacy",
-                "from spacy_grammar.grammar import Grammar",
-                "",
-                "nlp = spacy.load('en')",
-                "grammar = Grammar(nlp)",
-                "nlp.add_pipe(grammar)",
-                "doc = nlp('I can haz cheeseburger.')",
-                "doc._.has_grammar_error  # True"
-            ],
-            "author": "Motoki Wu",
-            "author_links": {
-                "github": "tokestermw",
-                "twitter": "plusepsilon"
-            },
-            "category": ["pipeline"]
-        },
         {
             "id": "spacy_kenlm",
             "slogan": "KenLM extension for spaCy 2.0",

From b94bcaa62f953c9d77948ba34750718bfef69a9a Mon Sep 17 00:00:00 2001
From: schaeran <schaeran1994@gmail.com>
Date: Mon, 4 Jul 2022 16:04:29 +0200
Subject: [PATCH 005/174] remove universe object: spacy-vis

---
 website/meta/universe.json | 15 ---------------
 1 file changed, 15 deletions(-)

diff --git a/website/meta/universe.json b/website/meta/universe.json
index f51f2cd88..9dae02a19 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -1274,21 +1274,6 @@
                 "github": "huggingface"
             }
         },
-        {
-            "id": "spacy-vis",
-            "slogan": "A visualisation tool for spaCy using Hierplane",
-            "description": "A visualiser for spaCy annotations. This visualisation uses the [Hierplane](https://allenai.github.io/hierplane/) Library to render the dependency parse from spaCy's models. It also includes visualisation of entities and POS tags within nodes.",
-            "github": "DeNeutoy/spacy-vis",
-            "url": "http://spacyvis.allennlp.org/spacy-parser",
-            "thumb": "https://i.imgur.com/DAG9QFd.jpg",
-            "image": "https://raw.githubusercontent.com/DeNeutoy/spacy-vis/master/img/example.gif",
-            "author": "Mark Neumann",
-            "author_links": {
-                "twitter": "MarkNeumannnn",
-                "github": "DeNeutoy"
-            },
-            "category": ["visualizers"]
-        },
         {
             "id": "matcher-explorer",
             "title": "Rule-based Matcher Explorer",

From 9b823fc9e9caad101c7ab32d484eb5babfae382f Mon Sep 17 00:00:00 2001
From: schaeran <schaeran1994@gmail.com>
Date: Mon, 4 Jul 2022 16:04:50 +0200
Subject: [PATCH 006/174] remove universe object: NeuroNER

---
 website/meta/universe.json | 13 -------------
 1 file changed, 13 deletions(-)

diff --git a/website/meta/universe.json b/website/meta/universe.json
index 9dae02a19..8697f361d 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -749,19 +749,6 @@
             "category": ["standalone", "research"],
             "tags": ["pytorch"]
         },
-        {
-            "id": "NeuroNER",
-            "title": "NeuroNER",
-            "slogan": "Named-entity recognition using neural networks",
-            "github": "Franck-Dernoncourt/NeuroNER",
-            "category": ["models"],
-            "pip": "pyneuroner[cpu]",
-            "code_example": [
-                "from neuroner import neuromodel",
-                "nn = neuromodel.NeuroNER(train_model=False, use_pretrained_model=True)"
-            ],
-            "tags": ["standalone"]
-        },
         {
             "id": "NLPre",
             "title": "NLPre",

From a9062ebf17e69f5f8d06098c3f0bb13e985cb0a7 Mon Sep 17 00:00:00 2001
From: schaeran <schaeran1994@gmail.com>
Date: Mon, 4 Jul 2022 16:05:11 +0200
Subject: [PATCH 007/174] remove universe object: spacy-lookup

---
 website/meta/universe.json | 28 ----------------------------
 1 file changed, 28 deletions(-)

diff --git a/website/meta/universe.json b/website/meta/universe.json
index 8697f361d..fb6564660 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -967,34 +967,6 @@
             },
             "category": ["pipeline"]
         },
-        {
-            "id": "spacy-lookup",
-            "slogan": "A powerful entity matcher for very large dictionaries, using the FlashText module",
-            "description": "spaCy v2.0 extension and pipeline component for adding Named Entities metadata to `Doc` objects. Detects Named Entities using dictionaries. The extension sets the custom `Doc`, `Token` and `Span` attributes `._.is_entity`, `._.entity_type`, `._.has_entities` and `._.entities`. Named Entities are matched using the python module `flashtext`, and looked up in the data provided by different dictionaries.",
-            "github": "mpuig/spacy-lookup",
-            "pip": "spacy-lookup",
-            "code_example": [
-                "import spacy",
-                "from spacy_lookup import Entity",
-                "",
-                "nlp = spacy.load('en')",
-                "entity = Entity(keywords_list=['python', 'product manager', 'java platform'])",
-                "nlp.add_pipe(entity, last=True)",
-                "",
-                "doc = nlp(\"I am a product manager for a java and python.\")",
-                "assert doc._.has_entities == True",
-                "assert doc[0]._.is_entity == False",
-                "assert doc[3]._.entity_desc == 'product manager'",
-                "assert doc[3]._.is_entity == True",
-                "",
-                "print([(token.text, token._.canonical) for token in doc if token._.is_entity])"
-            ],
-            "author": "Marc Puig",
-            "author_links": {
-                "github": "mpuig"
-            },
-            "category": ["pipeline"]
-        },
         {
             "id": "spacy-iwnlp",
             "slogan": "German lemmatization with IWNLP",

From 224f30c5636e52e7450a610487c523bea4e9491e Mon Sep 17 00:00:00 2001
From: schaeran <schaeran1994@gmail.com>
Date: Mon, 4 Jul 2022 16:05:34 +0200
Subject: [PATCH 008/174] remove universe object: spacy-raspberry

---
 website/meta/universe.json | 14 --------------
 1 file changed, 14 deletions(-)

diff --git a/website/meta/universe.json b/website/meta/universe.json
index fb6564660..fc3548c4a 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -2356,20 +2356,6 @@
             "category": ["nonpython"],
             "tags": ["javascript"]
         },
-        {
-            "id": "spacy-raspberry",
-            "title": "spacy-raspberry",
-            "slogan": "64bit Raspberry Pi image for spaCy and neuralcoref",
-            "github": "boehm-e/spacy-raspberry",
-            "thumb": "https://i.imgur.com/VCJMrE6.png",
-            "image": "https://raw.githubusercontent.com/boehm-e/spacy-raspberry/master/imgs/preview.png",
-            "author": "Erwan Boehm",
-            "author_links": {
-                "github": "boehm-e"
-            },
-            "category": ["apis"],
-            "tags": ["raspberrypi"]
-        },
         {
             "id": "spacy-wordnet",
             "title": "spacy-wordnet",

From 60a35a2bb2254564e169d91a19142f04cf93ba0e Mon Sep 17 00:00:00 2001
From: schaeran <schaeran1994@gmail.com>
Date: Mon, 4 Jul 2022 16:06:02 +0200
Subject: [PATCH 009/174] remove universe object: spacy_kenlm

---
 website/meta/universe.json | 24 ------------------------
 1 file changed, 24 deletions(-)

diff --git a/website/meta/universe.json b/website/meta/universe.json
index fc3548c4a..c2e06d2af 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -875,30 +875,6 @@
                 "github": "shigapov"
             }
         },
-        {
-            "id": "spacy_kenlm",
-            "slogan": "KenLM extension for spaCy 2.0",
-            "github": "tokestermw/spacy_kenlm",
-            "pip": "spacy_kenlm",
-            "code_example": [
-                "import spacy",
-                "from spacy_kenlm import spaCyKenLM",
-                "",
-                "nlp = spacy.load('en_core_web_sm')",
-                "spacy_kenlm = spaCyKenLM()  # default model from test.arpa",
-                "nlp.add_pipe(spacy_kenlm)",
-                "doc = nlp('How are you?')",
-                "doc._.kenlm_score # doc score",
-                "doc[:2]._.kenlm_score # span score",
-                "doc[2]._.kenlm_score # token score"
-            ],
-            "author": "Motoki Wu",
-            "author_links": {
-                "github": "tokestermw",
-                "twitter": "plusepsilon"
-            },
-            "category": ["pipeline"]
-        },
         {
             "id": "spacy_readability",
             "slogan": "Add text readability meta data to Doc objects",

From 5000a08a200cf6304bf83b0e73bb507bdc3c6a29 Mon Sep 17 00:00:00 2001
From: schaeran <schaeran1994@gmail.com>
Date: Mon, 4 Jul 2022 16:06:20 +0200
Subject: [PATCH 010/174] remove universe object: adam_qas

---
 website/meta/universe.json | 23 -----------------------
 1 file changed, 23 deletions(-)

diff --git a/website/meta/universe.json b/website/meta/universe.json
index c2e06d2af..253af126e 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -2212,29 +2212,6 @@
             "youtube": "8u57WSXVpmw",
             "category": ["videos"]
         },
-        {
-            "id": "adam_qas",
-            "title": "ADAM: Question Answering System",
-            "slogan": "A question answering system that extracts answers from Wikipedia to questions posed in natural language.",
-            "github": "5hirish/adam_qas",
-            "pip": "qas",
-            "code_example": [
-                "git clone https://github.com/5hirish/adam_qas.git",
-                "cd adam_qas",
-                "pip install -r requirements.txt",
-                "python -m qas.adam 'When was linux kernel version 4.0 released ?'"
-            ],
-            "code_language": "bash",
-            "thumb": "https://shirishkadam.files.wordpress.com/2018/04/mini_alleviate.png",
-            "author": "Shirish Kadam",
-            "author_links": {
-                "twitter": "5hirish",
-                "github": "5hirish",
-                "website": "https://shirishkadam.com/"
-            },
-            "category": ["standalone"],
-            "tags": ["question-answering", "elasticsearch"]
-        },
         {
             "id": "self-attentive-parser",
             "title": "Berkeley Neural Parser",

From 0e4a835468b644c7cc5cb2f13881372705e07618 Mon Sep 17 00:00:00 2001
From: schaeran <schaeran1994@gmail.com>
Date: Mon, 4 Jul 2022 16:06:38 +0200
Subject: [PATCH 011/174] remove universe object: num_fh

---
 website/meta/universe.json | 29 -----------------------------
 1 file changed, 29 deletions(-)

diff --git a/website/meta/universe.json b/website/meta/universe.json
index 253af126e..29fda2ae9 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -2906,35 +2906,6 @@
             ],
             "author": "Stefan Daniel Dumitrescu, Andrei-Marius Avram"
         },
-        {
-            "id": "num_fh",
-            "title": "Numeric Fused-Head",
-            "slogan": "Numeric Fused-Head Identificaiton and Resolution in English",
-            "description": "This package provide a wrapper for the Numeric Fused-Head in English. It provides another information layer on numbers that refer to another entity which is not obvious from the syntactic tree.",
-            "github": "yanaiela/num_fh",
-            "pip": "num_fh",
-            "category": ["pipeline", "research"],
-            "code_example": [
-                "import spacy",
-                "from num_fh import NFH",
-                "nlp = spacy.load('en_core_web_sm')",
-                "nfh = NFH(nlp)",
-                "nlp.add_pipe(nfh, first=False)",
-                "doc = nlp(\"I told you two, that only one of them is the one who will get 2 or 3 icecreams\")",
-                "",
-                "assert doc[16]._.is_nfh == True",
-                "assert doc[18]._.is_nfh == False",
-                "assert doc[3]._.is_deter_nfh == True",
-                "assert doc[16]._.is_deter_nfh == False",
-                "assert len(doc._.nfh) == 4"
-            ],
-            "author": "Yanai Elazar",
-            "author_links": {
-                "github": "yanaiela",
-                "twitter": "yanaiela",
-                "website": "https://yanaiela.github.io"
-            }
-        },
         {
             "id": "Healthsea",
             "title": "Healthsea",

From 4e8a5994df14dd14701d63cd316647dc5d95c2f3 Mon Sep 17 00:00:00 2001
From: schaeran <schaeran1994@gmail.com>
Date: Mon, 4 Jul 2022 16:06:58 +0200
Subject: [PATCH 012/174] remove universe object: NLPre

---
 website/meta/universe.json | 24 ------------------------
 1 file changed, 24 deletions(-)

diff --git a/website/meta/universe.json b/website/meta/universe.json
index 29fda2ae9..17619b906 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -749,30 +749,6 @@
             "category": ["standalone", "research"],
             "tags": ["pytorch"]
         },
-        {
-            "id": "NLPre",
-            "title": "NLPre",
-            "slogan": "Natural Language Preprocessing Library for health data and more",
-            "github": "NIHOPA/NLPre",
-            "pip": "nlpre",
-            "code_example": [
-                "from nlpre import titlecaps, dedash, identify_parenthetical_phrases",
-                "from nlpre import replace_acronyms, replace_from_dictionary",
-                "ABBR = identify_parenthetical_phrases()(text)",
-                "parsers = [dedash(), titlecaps(), replace_acronyms(ABBR),",
-                "        replace_from_dictionary(prefix='MeSH_')]",
-                "for f in parsers:",
-                "    text = f(text)",
-                "print(text)"
-            ],
-            "category": ["scientific", "biomedical"],
-            "author": "Travis Hoppe",
-            "author_links": {
-                "github": "thoppe",
-                "twitter": "metasemantic",
-                "website": "http://thoppe.github.io/"
-            }
-        },
         {
             "id": "Chatterbot",
             "title": "Chatterbot",

From b3165db41b35e2713badf37166f31a6a803f5515 Mon Sep 17 00:00:00 2001
From: schaeran <schaeran1994@gmail.com>
Date: Mon, 4 Jul 2022 16:07:18 +0200
Subject: [PATCH 013/174] remove universe object: spacy-langdetect

---
 website/meta/universe.json | 29 -----------------------------
 1 file changed, 29 deletions(-)

diff --git a/website/meta/universe.json b/website/meta/universe.json
index 17619b906..a6e407e93 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -2355,35 +2355,6 @@
             "category": ["standalone", "pipeline"],
             "tags": ["linguistics", "computational linguistics", "conll", "conll-u"]
         },
-        {
-            "id": "spacy-langdetect",
-            "title": "spacy-langdetect",
-            "slogan": "A fully customizable language detection pipeline for spaCy",
-            "description": "This module allows you to add language detection capabilites to your spaCy pipeline. Also supports custom language detectors!",
-            "pip": "spacy-langdetect",
-            "code_example": [
-                "import spacy",
-                "from spacy_langdetect import LanguageDetector",
-                "nlp = spacy.load('en')",
-                "nlp.add_pipe(LanguageDetector(), name='language_detector', last=True)",
-                "text = 'This is an english text.'",
-                "doc = nlp(text)",
-                "# document level language detection. Think of it like average language of the document!",
-                "print(doc._.language)",
-                "# sentence level language detection",
-                "for sent in doc.sents:",
-                "   print(sent, sent._.language)"
-            ],
-            "code_language": "python",
-            "author": "Abhijit Balaji",
-            "author_links": {
-                "github": "Abhijit-2592",
-                "website": "https://abhijit-2592.github.io/"
-            },
-            "github": "Abhijit-2592/spacy-langdetect",
-            "category": ["pipeline"],
-            "tags": ["language-detection"]
-        },
         {
             "id": "ludwig",
             "title": "Ludwig",

From e9eb59699f1b80c7a74b9e0f1bb2520d74b7bfd5 Mon Sep 17 00:00:00 2001
From: Raphael Mitsch <r.mitsch@outlook.com>
Date: Mon, 4 Jul 2022 17:05:21 +0200
Subject: [PATCH 014/174] NEL confidence threshold (#11016)

* Add base for NEL abstention threshold mechanism.

* Add abstention threshold to entity linker. Add test.

* Fix entity linking tests.

* Changed abstention default threshold from 0 to None.

* Fix default values for abstention thresholds.

* Fix mypy errors.

* Replace assertion with raise of proper error code.

* Simplify threshold check. Remove thresholding from EntityLinker_v1.

* Rename test.

* Update spacy/pipeline/entity_linker.py

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Update spacy/pipeline/entity_linker.py

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Make E1043 configurable.

* Update docs.

* Rephrase description in docs. Adjusting error code message.

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
---
 spacy/errors.py                            |  2 +
 spacy/pipeline/entity_linker.py            | 34 ++++++++---
 spacy/pipeline/legacy/entity_linker.py     |  7 +--
 spacy/tests/pipeline/test_entity_linker.py | 67 ++++++++++++++++++++--
 website/docs/api/entitylinker.md           | 55 +++++++++---------
 5 files changed, 122 insertions(+), 43 deletions(-)

diff --git a/spacy/errors.py b/spacy/errors.py
index dbebf09bd..fd412a4da 100644
--- a/spacy/errors.py
+++ b/spacy/errors.py
@@ -937,6 +937,8 @@ class Errors(metaclass=ErrorsWithCodes):
     E1041 = ("Expected a string, Doc, or bytes as input, but got: {type}")
     E1042 = ("Function was called with `{arg1}`={arg1_values} and "
              "`{arg2}`={arg2_values} but these arguments are conflicting.")
+    E1043 = ("Expected None or a value in range [{range_start}, {range_end}] for entity linker threshold, but got "
+             "{value}.")
 
 
 # Deprecated model shortcuts, only used in errors and warnings
diff --git a/spacy/pipeline/entity_linker.py b/spacy/pipeline/entity_linker.py
index aa7985a9c..73a90b268 100644
--- a/spacy/pipeline/entity_linker.py
+++ b/spacy/pipeline/entity_linker.py
@@ -56,6 +56,7 @@ DEFAULT_NEL_MODEL = Config().from_str(default_model_config)["model"]
         "overwrite": True,
         "scorer": {"@scorers": "spacy.entity_linker_scorer.v1"},
         "use_gold_ents": True,
+        "threshold": None,
     },
     default_score_weights={
         "nel_micro_f": 1.0,
@@ -77,6 +78,7 @@ def make_entity_linker(
     overwrite: bool,
     scorer: Optional[Callable],
     use_gold_ents: bool,
+    threshold: Optional[float] = None,
 ):
     """Construct an EntityLinker component.
 
@@ -91,6 +93,10 @@ def make_entity_linker(
     get_candidates (Callable[[KnowledgeBase, "Span"], Iterable[Candidate]]): Function that
         produces a list of candidates, given a certain knowledge base and a textual mention.
     scorer (Optional[Callable]): The scoring method.
+    use_gold_ents (bool): Whether to copy entities from gold docs or not. If false, another
+        component must provide entity annotations.
+    threshold (Optional[float]): Confidence threshold for entity predictions. If confidence is below the threshold,
+        prediction is discarded. If None, predictions are not filtered by any threshold.
     """
 
     if not model.attrs.get("include_span_maker", False):
@@ -121,6 +127,7 @@ def make_entity_linker(
         overwrite=overwrite,
         scorer=scorer,
         use_gold_ents=use_gold_ents,
+        threshold=threshold,
     )
 
 
@@ -156,6 +163,7 @@ class EntityLinker(TrainablePipe):
         overwrite: bool = BACKWARD_OVERWRITE,
         scorer: Optional[Callable] = entity_linker_score,
         use_gold_ents: bool,
+        threshold: Optional[float] = None,
     ) -> None:
         """Initialize an entity linker.
 
@@ -174,9 +182,20 @@ class EntityLinker(TrainablePipe):
             Scorer.score_links.
         use_gold_ents (bool): Whether to copy entities from gold docs or not. If false, another
             component must provide entity annotations.
-
+        threshold (Optional[float]): Confidence threshold for entity predictions. If confidence is below the
+            threshold, prediction is discarded. If None, predictions are not filtered by any threshold.
         DOCS: https://spacy.io/api/entitylinker#init
         """
+
+        if threshold is not None and not (0 <= threshold <= 1):
+            raise ValueError(
+                Errors.E1043.format(
+                    range_start=0,
+                    range_end=1,
+                    value=threshold,
+                )
+            )
+
         self.vocab = vocab
         self.model = model
         self.name = name
@@ -192,6 +211,7 @@ class EntityLinker(TrainablePipe):
         self.kb = empty_kb(entity_vector_length)(self.vocab)
         self.scorer = scorer
         self.use_gold_ents = use_gold_ents
+        self.threshold = threshold
 
     def set_kb(self, kb_loader: Callable[[Vocab], KnowledgeBase]):
         """Define the KB of this pipe by providing a function that will
@@ -424,9 +444,8 @@ class EntityLinker(TrainablePipe):
                     if not candidates:
                         # no prediction possible for this entity - setting to NIL
                         final_kb_ids.append(self.NIL)
-                    elif len(candidates) == 1:
+                    elif len(candidates) == 1 and self.threshold is None:
                         # shortcut for efficiency reasons: take the 1 candidate
-                        # TODO: thresholding
                         final_kb_ids.append(candidates[0].entity_)
                     else:
                         random.shuffle(candidates)
@@ -455,10 +474,11 @@ class EntityLinker(TrainablePipe):
                             if sims.shape != prior_probs.shape:
                                 raise ValueError(Errors.E161)
                             scores = prior_probs + sims - (prior_probs * sims)
-                        # TODO: thresholding
-                        best_index = scores.argmax().item()
-                        best_candidate = candidates[best_index]
-                        final_kb_ids.append(best_candidate.entity_)
+                        final_kb_ids.append(
+                            candidates[scores.argmax().item()].entity_
+                            if self.threshold is None or scores.max() >= self.threshold
+                            else EntityLinker.NIL
+                        )
         if not (len(final_kb_ids) == entity_count):
             err = Errors.E147.format(
                 method="predict", msg="result variables not of equal length"
diff --git a/spacy/pipeline/legacy/entity_linker.py b/spacy/pipeline/legacy/entity_linker.py
index d723bdbe5..2f8a1f8ea 100644
--- a/spacy/pipeline/legacy/entity_linker.py
+++ b/spacy/pipeline/legacy/entity_linker.py
@@ -7,7 +7,7 @@ from pathlib import Path
 from itertools import islice
 import srsly
 import random
-from thinc.api import CosineDistance, Model, Optimizer, Config
+from thinc.api import CosineDistance, Model, Optimizer
 from thinc.api import set_dropout_rate
 import warnings
 
@@ -20,7 +20,7 @@ from ...language import Language
 from ...vocab import Vocab
 from ...training import Example, validate_examples, validate_get_examples
 from ...errors import Errors, Warnings
-from ...util import SimpleFrozenList, registry
+from ...util import SimpleFrozenList
 from ... import util
 from ...scorer import Scorer
 
@@ -70,7 +70,6 @@ class EntityLinker_v1(TrainablePipe):
             produces a list of candidates, given a certain knowledge base and a textual mention.
         scorer (Optional[Callable]): The scoring method. Defaults to
             Scorer.score_links.
-
         DOCS: https://spacy.io/api/entitylinker#init
         """
         self.vocab = vocab
@@ -272,7 +271,6 @@ class EntityLinker_v1(TrainablePipe):
                             final_kb_ids.append(self.NIL)
                         elif len(candidates) == 1:
                             # shortcut for efficiency reasons: take the 1 candidate
-                            # TODO: thresholding
                             final_kb_ids.append(candidates[0].entity_)
                         else:
                             random.shuffle(candidates)
@@ -301,7 +299,6 @@ class EntityLinker_v1(TrainablePipe):
                                 if sims.shape != prior_probs.shape:
                                     raise ValueError(Errors.E161)
                                 scores = prior_probs + sims - (prior_probs * sims)
-                            # TODO: thresholding
                             best_index = scores.argmax().item()
                             best_candidate = candidates[best_index]
                             final_kb_ids.append(best_candidate.entity_)
diff --git a/spacy/tests/pipeline/test_entity_linker.py b/spacy/tests/pipeline/test_entity_linker.py
index a6cfead77..14995d7b8 100644
--- a/spacy/tests/pipeline/test_entity_linker.py
+++ b/spacy/tests/pipeline/test_entity_linker.py
@@ -1,4 +1,4 @@
-from typing import Callable, Iterable
+from typing import Callable, Iterable, Dict, Any
 
 import pytest
 from numpy.testing import assert_equal
@@ -207,7 +207,7 @@ def test_no_entities():
     nlp.add_pipe("sentencizer", first=True)
 
     # this will run the pipeline on the examples and shouldn't crash
-    results = nlp.evaluate(train_examples)
+    nlp.evaluate(train_examples)
 
 
 def test_partial_links():
@@ -1063,7 +1063,7 @@ def test_no_gold_ents(patterns):
         "entity_linker", config={"use_gold_ents": False}, last=True
     )
     entity_linker.set_kb(create_kb)
-    assert entity_linker.use_gold_ents == False
+    assert entity_linker.use_gold_ents is False
 
     optimizer = nlp.initialize(get_examples=lambda: train_examples)
     for i in range(2):
@@ -1074,7 +1074,7 @@ def test_no_gold_ents(patterns):
     nlp.add_pipe("sentencizer", first=True)
 
     # this will run the pipeline on the examples and shouldn't crash
-    results = nlp.evaluate(train_examples)
+    nlp.evaluate(train_examples)
 
 
 @pytest.mark.issue(9575)
@@ -1114,4 +1114,61 @@ def test_tokenization_mismatch():
         nlp.update(train_examples, sgd=optimizer, losses=losses)
 
     nlp.add_pipe("sentencizer", first=True)
-    results = nlp.evaluate(train_examples)
+    nlp.evaluate(train_examples)
+
+
+# fmt: off
+@pytest.mark.parametrize(
+    "meet_threshold,config",
+    [
+        (False, {"@architectures": "spacy.EntityLinker.v2", "tok2vec": DEFAULT_TOK2VEC_MODEL}),
+        (True, {"@architectures": "spacy.EntityLinker.v2", "tok2vec": DEFAULT_TOK2VEC_MODEL}),
+    ],
+)
+# fmt: on
+def test_threshold(meet_threshold: bool, config: Dict[str, Any]):
+    """Tests abstention threshold.
+    meet_threshold (bool): Whether to configure NEL setup so that confidence threshold is met.
+    config (Dict[str, Any]): NEL architecture config.
+    """
+    nlp = English()
+    nlp.add_pipe("sentencizer")
+    text = "Mahler's Symphony No. 8 was beautiful."
+    entities = [(0, 6, "PERSON")]
+    links = {(0, 6): {"Q7304": 1.0}}
+    sent_starts = [1, -1, 0, 0, 0, 0, 0, 0, 0]
+    entity_id = "Q7304"
+    doc = nlp(text)
+    train_examples = [
+        Example.from_dict(
+            doc, {"entities": entities, "links": links, "sent_starts": sent_starts}
+        )
+    ]
+
+    def create_kb(vocab):
+        # create artificial KB
+        mykb = KnowledgeBase(vocab, entity_vector_length=3)
+        mykb.add_entity(entity=entity_id, freq=12, entity_vector=[6, -4, 3])
+        mykb.add_alias(
+            alias="Mahler",
+            entities=[entity_id],
+            probabilities=[1 if meet_threshold else 0.01],
+        )
+        return mykb
+
+    # Create the Entity Linker component and add it to the pipeline
+    entity_linker = nlp.add_pipe(
+        "entity_linker",
+        last=True,
+        config={"threshold": 0.99, "model": config},
+    )
+    entity_linker.set_kb(create_kb)  # type: ignore
+    nlp.initialize(get_examples=lambda: train_examples)
+
+    # Add a custom rule-based component to mimick NER
+    ruler = nlp.add_pipe("entity_ruler", before="entity_linker")
+    ruler.add_patterns([{"label": "PERSON", "pattern": [{"LOWER": "mahler"}]}])  # type: ignore
+    doc = nlp(text)
+
+    assert len(doc.ents) == 1
+    assert doc.ents[0].kb_id_ == entity_id if meet_threshold else EntityLinker.NIL
diff --git a/website/docs/api/entitylinker.md b/website/docs/api/entitylinker.md
index 8e0d6087a..a55cce352 100644
--- a/website/docs/api/entitylinker.md
+++ b/website/docs/api/entitylinker.md
@@ -47,22 +47,24 @@ architectures and their arguments and hyperparameters.
 >    "model": DEFAULT_NEL_MODEL,
 >    "entity_vector_length": 64,
 >    "get_candidates": {'@misc': 'spacy.CandidateGenerator.v1'},
+>    "threshold": None,
 > }
 > nlp.add_pipe("entity_linker", config=config)
 > ```
 
-| Setting                                  | Description                                                                                                                                                                                                                                                              |
-| ---------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
-| `labels_discard`                         | NER labels that will automatically get a "NIL" prediction. Defaults to `[]`. ~~Iterable[str]~~                                                                                                                                                                           |
-| `n_sents`                                | The number of neighbouring sentences to take into account. Defaults to 0. ~~int~~                                                                                                                                                                                        |
-| `incl_prior`                             | Whether or not to include prior probabilities from the KB in the model. Defaults to `True`. ~~bool~~                                                                                                                                                                     |
-| `incl_context`                           | Whether or not to include the local context in the model. Defaults to `True`. ~~bool~~                                                                                                                                                                                   |
-| `model`                                  | The [`Model`](https://thinc.ai/docs/api-model) powering the pipeline component. Defaults to [EntityLinker](/api/architectures#EntityLinker). ~~Model~~                                                                                                                   |
-| `entity_vector_length`                   | Size of encoding vectors in the KB. Defaults to `64`. ~~int~~                                                                                                                                                                                                            |
-| `use_gold_ents`                          | Whether to copy entities from the gold docs or not. Defaults to `True`. If `False`, entities must be set in the training data or by an annotating component in the pipeline. ~~int~~                                                                                     |
-| `get_candidates`                         | Function that generates plausible candidates for a given `Span` object. Defaults to [CandidateGenerator](/api/architectures#CandidateGenerator), a function looking up exact, case-dependent aliases in the KB. ~~Callable[[KnowledgeBase, Span], Iterable[Candidate]]~~ |
-| `overwrite` <Tag variant="new">3.2</Tag> | Whether existing annotation is overwritten. Defaults to `True`. ~~bool~~                                                                                                                                                                                                 |
-| `scorer` <Tag variant="new">3.2</Tag>    | The scoring method. Defaults to [`Scorer.score_links`](/api/scorer#score_links). ~~Optional[Callable]~~                                                                                                                                                                  |
+| Setting                                  | Description                                                                                                                                                                                                                                                                                 |
+| ---------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `labels_discard`                         | NER labels that will automatically get a "NIL" prediction. Defaults to `[]`. ~~Iterable[str]~~                                                                                                                                                                                              |
+| `n_sents`                                | The number of neighbouring sentences to take into account. Defaults to 0. ~~int~~                                                                                                                                                                                                           |
+| `incl_prior`                             | Whether or not to include prior probabilities from the KB in the model. Defaults to `True`. ~~bool~~                                                                                                                                                                                        |
+| `incl_context`                           | Whether or not to include the local context in the model. Defaults to `True`. ~~bool~~                                                                                                                                                                                                      |
+| `model`                                  | The [`Model`](https://thinc.ai/docs/api-model) powering the pipeline component. Defaults to [EntityLinker](/api/architectures#EntityLinker). ~~Model~~                                                                                                                                      |
+| `entity_vector_length`                   | Size of encoding vectors in the KB. Defaults to `64`. ~~int~~                                                                                                                                                                                                                               |
+| `use_gold_ents`                          | Whether to copy entities from the gold docs or not. Defaults to `True`. If `False`, entities must be set in the training data or by an annotating component in the pipeline. ~~int~~                                                                                                        |
+| `get_candidates`                         | Function that generates plausible candidates for a given `Span` object. Defaults to [CandidateGenerator](/api/architectures#CandidateGenerator), a function looking up exact, case-dependent aliases in the KB. ~~Callable[[KnowledgeBase, Span], Iterable[Candidate]]~~                    |
+| `overwrite` <Tag variant="new">3.2</Tag> | Whether existing annotation is overwritten. Defaults to `True`. ~~bool~~                                                                                                                                                                                                                    |
+| `scorer` <Tag variant="new">3.2</Tag>    | The scoring method. Defaults to [`Scorer.score_links`](/api/scorer#score_links). ~~Optional[Callable]~~                                                                                                                                                                                     |
+| `threshold` <Tag variant="new">3.4</Tag> | Confidence threshold for entity predictions. The default of `None` implies that all predictions are accepted, otherwise those with a score beneath the treshold are discarded. If there are no predictions with scores above the threshold, the linked entity is `NIL`. ~~Optional[float]~~ |
 
 ```python
 %%GITHUB_SPACY/spacy/pipeline/entity_linker.py
@@ -95,20 +97,21 @@ custom knowledge base, you should either call
 [`set_kb`](/api/entitylinker#set_kb) or provide a `kb_loader` in the
 [`initialize`](/api/entitylinker#initialize) call.
 
-| Name                                     | Description                                                                                                                      |
-| ---------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------- |
-| `vocab`                                  | The shared vocabulary. ~~Vocab~~                                                                                                 |
-| `model`                                  | The [`Model`](https://thinc.ai/docs/api-model) powering the pipeline component. ~~Model~~                                        |
-| `name`                                   | String name of the component instance. Used to add entries to the `losses` during training. ~~str~~                              |
-| _keyword-only_                           |                                                                                                                                  |
-| `entity_vector_length`                   | Size of encoding vectors in the KB. ~~int~~                                                                                      |
-| `get_candidates`                         | Function that generates plausible candidates for a given `Span` object. ~~Callable[[KnowledgeBase, Span], Iterable[Candidate]]~~ |
-| `labels_discard`                         | NER labels that will automatically get a `"NIL"` prediction. ~~Iterable[str]~~                                                   |
-| `n_sents`                                | The number of neighbouring sentences to take into account. ~~int~~                                                               |
-| `incl_prior`                             | Whether or not to include prior probabilities from the KB in the model. ~~bool~~                                                 |
-| `incl_context`                           | Whether or not to include the local context in the model. ~~bool~~                                                               |
-| `overwrite` <Tag variant="new">3.2</Tag> | Whether existing annotation is overwritten. Defaults to `True`. ~~bool~~                                                         |
-| `scorer` <Tag variant="new">3.2</Tag>    | The scoring method. Defaults to [`Scorer.score_links`](/api/scorer#score_links). ~~Optional[Callable]~~                          |
+| Name                                     | Description                                                                                                                                                                                                                                                                                 |
+| ---------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `vocab`                                  | The shared vocabulary. ~~Vocab~~                                                                                                                                                                                                                                                            |
+| `model`                                  | The [`Model`](https://thinc.ai/docs/api-model) powering the pipeline component. ~~Model~~                                                                                                                                                                                                   |
+| `name`                                   | String name of the component instance. Used to add entries to the `losses` during training. ~~str~~                                                                                                                                                                                         |
+| _keyword-only_                           |                                                                                                                                                                                                                                                                                             |
+| `entity_vector_length`                   | Size of encoding vectors in the KB. ~~int~~                                                                                                                                                                                                                                                 |
+| `get_candidates`                         | Function that generates plausible candidates for a given `Span` object. ~~Callable[[KnowledgeBase, Span], Iterable[Candidate]]~~                                                                                                                                                            |
+| `labels_discard`                         | NER labels that will automatically get a `"NIL"` prediction. ~~Iterable[str]~~                                                                                                                                                                                                              |
+| `n_sents`                                | The number of neighbouring sentences to take into account. ~~int~~                                                                                                                                                                                                                          |
+| `incl_prior`                             | Whether or not to include prior probabilities from the KB in the model. ~~bool~~                                                                                                                                                                                                            |
+| `incl_context`                           | Whether or not to include the local context in the model. ~~bool~~                                                                                                                                                                                                                          |
+| `overwrite` <Tag variant="new">3.2</Tag> | Whether existing annotation is overwritten. Defaults to `True`. ~~bool~~                                                                                                                                                                                                                    |
+| `scorer` <Tag variant="new">3.2</Tag>    | The scoring method. Defaults to [`Scorer.score_links`](/api/scorer#score_links). ~~Optional[Callable]~~                                                                                                                                                                                     |
+| `threshold` <Tag variant="new">3.4</Tag> | Confidence threshold for entity predictions. The default of `None` implies that all predictions are accepted, otherwise those with a score beneath the treshold are discarded. If there are no predictions with scores above the threshold, the linked entity is `NIL`. ~~Optional[float]~~ |
 
 ## EntityLinker.\_\_call\_\_ {#call tag="method"}
 

From 5240baccfee33af84c3b92813da827f4c5bbd7fa Mon Sep 17 00:00:00 2001
From: kadarakos <kadar.akos@gmail.com>
Date: Mon, 4 Jul 2022 17:15:33 +0200
Subject: [PATCH 015/174] dont use get_array_module (#11056)

---
 spacy/pipeline/textcat.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/spacy/pipeline/textcat.py b/spacy/pipeline/textcat.py
index bc3f127fc..c45f819fc 100644
--- a/spacy/pipeline/textcat.py
+++ b/spacy/pipeline/textcat.py
@@ -192,7 +192,7 @@ class TextCategorizer(TrainablePipe):
         if not any(len(doc) for doc in docs):
             # Handle cases where there are no tokens in any docs.
             tensors = [doc.tensor for doc in docs]
-            xp = get_array_module(tensors)
+            xp = self.model.ops.xp
             scores = xp.zeros((len(list(docs)), len(self.labels)))
             return scores
         scores = self.model.predict(docs)

From d36d66b7ca491976e2c7da2cde76fdac16229637 Mon Sep 17 00:00:00 2001
From: Madeesh Kannan <shadeMe@users.noreply.github.com>
Date: Mon, 4 Jul 2022 18:37:09 +0200
Subject: [PATCH 016/174] Increase test deadline to 30 minutes to prevent
 spurious test failures (#11070)

* Increase test deadline to 30 minutes to prevent spurious test failures

* Reduce deadline to 2 minutes
---
 spacy/tests/conftest.py | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/spacy/tests/conftest.py b/spacy/tests/conftest.py
index db17f1a8f..1117c6cf6 100644
--- a/spacy/tests/conftest.py
+++ b/spacy/tests/conftest.py
@@ -1,6 +1,11 @@
 import pytest
 from spacy.util import get_lang_class
+from hypothesis import settings
 
+# Functionally disable deadline settings for tests
+# to prevent spurious test failures in CI builds.
+settings.register_profile("no_deadlines", deadline=2*60*1000) # in ms
+settings.load_profile("no_deadlines")
 
 def pytest_addoption(parser):
     try:

From 78a84f0d78630a6a2849bb95f7dabfad4a513aea Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Mon, 4 Jul 2022 20:50:16 +0200
Subject: [PATCH 017/174] Support env var for num build jobs (#11073)

---
 setup.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/setup.py b/setup.py
index 9023b9fa3..377a7689d 100755
--- a/setup.py
+++ b/setup.py
@@ -126,6 +126,8 @@ class build_ext_options:
 
 class build_ext_subclass(build_ext, build_ext_options):
     def build_extensions(self):
+        if not self.parallel:
+            self.parallel = int(os.environ.get("SPACY_NUM_BUILD_JOBS", 1))
         build_ext_options.build_options(self)
         build_ext.build_extensions(self)
 

From a06cbae70dd96c3f709fa0dadf95c41292b170fb Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Dani=C3=ABl=20de=20Kok?= <me@danieldk.eu>
Date: Tue, 5 Jul 2022 10:53:42 +0200
Subject: [PATCH 018/174] precompute_hiddens/Parser: do not look up CPU ops
 (3.4) (#11069)

* precompute_hiddens/Parser: do not look up CPU ops

`get_ops("cpu")` is quite expensive. To avoid this, we want to cache the
result as in #11068. However, for 3.x we do not want to change the ABI.
So we avoid the expensive lookup by using NumpyOps. This should have a
minimal impact, since `get_ops("cpu")` was only used when the model ops
were `CupyOps`. If the ops are `AppleOps`, we are still passing through
the correct BLAS implementation.

* _NUMPY_OPS -> NUMPY_OPS
---
 spacy/ml/parser_model.pyx            | 2 +-
 spacy/pipeline/transition_parser.pyx | 7 +++++--
 2 files changed, 6 insertions(+), 3 deletions(-)

diff --git a/spacy/ml/parser_model.pyx b/spacy/ml/parser_model.pyx
index e045dc3b7..961bf4d70 100644
--- a/spacy/ml/parser_model.pyx
+++ b/spacy/ml/parser_model.pyx
@@ -441,7 +441,7 @@ cdef class precompute_hiddens:
 
         cdef CBlas cblas
         if isinstance(self.ops, CupyOps):
-            cblas = get_ops("cpu").cblas()
+            cblas = NUMPY_OPS.cblas()
         else:
             cblas = self.ops.cblas()
 
diff --git a/spacy/pipeline/transition_parser.pyx b/spacy/pipeline/transition_parser.pyx
index 98628f3c8..1327db2ce 100644
--- a/spacy/pipeline/transition_parser.pyx
+++ b/spacy/pipeline/transition_parser.pyx
@@ -9,7 +9,7 @@ from libc.stdlib cimport calloc, free
 import random
 
 import srsly
-from thinc.api import get_ops, set_dropout_rate, CupyOps
+from thinc.api import get_ops, set_dropout_rate, CupyOps, NumpyOps
 from thinc.extra.search cimport Beam
 import numpy.random
 import numpy
@@ -30,6 +30,9 @@ from ..errors import Errors, Warnings
 from .. import util
 
 
+NUMPY_OPS = NumpyOps()
+
+
 cdef class Parser(TrainablePipe):
     """
     Base class of the DependencyParser and EntityRecognizer.
@@ -262,7 +265,7 @@ cdef class Parser(TrainablePipe):
         ops = self.model.ops
         cdef CBlas cblas
         if isinstance(ops, CupyOps):
-            cblas = get_ops("cpu").cblas()
+            cblas = NUMPY_OPS.cblas()
         else:
             cblas = ops.cblas()
         self._ensure_labels_are_added(docs)

From 7b220afc29ae5eec25adef258a36abdc118636ba Mon Sep 17 00:00:00 2001
From: Kenneth Enevoldsen <kennethcenevoldsen@gmail.com>
Date: Thu, 7 Jul 2022 06:25:25 +0200
Subject: [PATCH 019/174] Added asent to spacy universe (#11078)

* Added asent to spacy universe

* Update addition of asent following correction
---
 website/meta/universe.json | 40 ++++++++++++++++++++++++++++++++++++++
 1 file changed, 40 insertions(+)

diff --git a/website/meta/universe.json b/website/meta/universe.json
index a6e407e93..01ed91c67 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -1120,6 +1120,46 @@
             "category": ["pipeline", "models", "training"],
             "tags": ["pipeline", "models", "transformers"]
         },
+        {
+            "id": "asent",
+            "title": "Asent",
+            "slogan": "Fast, flexible and transparent sentiment analysis",
+            "description": "Asent is a rule-based sentiment analysis library for Python made using spaCy. It is inspired by VADER, but uses a more modular ruleset, that allows the user to change e.g. the method for finding negations. Furthermore it includes visualisers to visualize the model predictions, making the model easily interpretable.",
+            "github": "kennethenevoldsen/asent",
+            "pip": "aseny",
+            "code_example": [
+                "import spacy",
+                "import asent",
+                "",
+                "# load spacy pipeline",
+                "nlp = spacy.blank('en')",
+                "nlp.add_pipe('sentencizer')",
+                "",
+                "# add the rule-based sentiment model",
+                "nlp.add_pipe('asent_en_v1')",
+                "",
+                "# try an example",
+                "text = 'I am not very happy, but I am also not especially sad'",
+                "doc = nlp(text)",
+                "",
+                "# print polarity of document, scaled to be between -1, and 1",
+                "print(doc._.polarity)",
+                "# neg=0.0 neu=0.631 pos=0.369 compound=0.7526",
+                "",
+                "# Naturally, a simple score can be quite unsatisfying, thus Asent implements a series of visualizer to interpret the results:",
+                "asent.visualize(doc, style='prediction')",
+                " # or",
+                "asent.visualize(doc[:5], style='analysis')"
+            ],
+            "thumb": "https://github.com/KennethEnevoldsen/asent/raw/main/docs/img/logo_black_font.png?raw=true",
+            "author": "Kenneth Enevoldsen",
+            "author_links": {
+                "github": "KennethEnevoldsen",
+                "website": "https://www.kennethenevoldsen.com"
+            },
+            "category": ["pipeline", "models"],
+            "tags": ["pipeline", "models", "sentiment"]
+        },
         {
             "id": "textdescriptives",
             "title": "TextDescriptives",

From bb3e11b9a10699dda1e38b0384176c8df04caa2a Mon Sep 17 00:00:00 2001
From: Nipun Sadvilkar <nipunsadvilkar@gmail.com>
Date: Thu, 7 Jul 2022 17:50:30 +0530
Subject: [PATCH 020/174] Github Action for spaCy universe project alert
 (#11090)

---
 .github/spacy_universe_alert.py            | 67 ++++++++++++++++++++++
 .github/workflows/spacy_universe_alert.yml | 30 ++++++++++
 website/meta/universe.json                 |  1 +
 3 files changed, 98 insertions(+)
 create mode 100644 .github/spacy_universe_alert.py
 create mode 100644 .github/workflows/spacy_universe_alert.yml

diff --git a/.github/spacy_universe_alert.py b/.github/spacy_universe_alert.py
new file mode 100644
index 000000000..99ffabe93
--- /dev/null
+++ b/.github/spacy_universe_alert.py
@@ -0,0 +1,67 @@
+import os
+import sys
+import json
+from datetime import datetime
+
+from slack_sdk.web.client import WebClient
+
+CHANNEL = "#alerts-universe"
+SLACK_TOKEN = os.environ.get("SLACK_BOT_TOKEN", "ENV VAR not available!")
+DATETIME_FORMAT = "%Y-%m-%dT%H:%M:%SZ"
+
+client = WebClient(SLACK_TOKEN)
+github_context = json.loads(sys.argv[1])
+
+event = github_context['event']
+pr_title = event['pull_request']["title"]
+pr_link = event['pull_request']["patch_url"].replace(".patch", "")
+pr_author_url = event['sender']["html_url"]
+pr_author_name = pr_author_url.rsplit('/')[-1]
+pr_created_at_dt = datetime.strptime(
+    event['pull_request']["created_at"],
+    DATETIME_FORMAT
+)
+pr_created_at = pr_created_at_dt.strftime("%c")
+pr_updated_at_dt = datetime.strptime(
+    event['pull_request']["updated_at"],
+    DATETIME_FORMAT
+)
+pr_updated_at = pr_updated_at_dt.strftime("%c")
+
+blocks = [
+    {
+      "type": "section",
+      "text": {
+        "type": "mrkdwn",
+        "text": "📣 New spaCy Universe Project Alert ✨"
+      }
+    },
+    {
+      "type": "section",
+      "fields": [
+        {
+          "type": "mrkdwn",
+          "text": f"*Pull Request:*\n<{pr_link}|{pr_title}>"
+        },
+        {
+          "type": "mrkdwn",
+          "text": f"*Author:*\n<{pr_author_url}|{pr_author_name}>"
+        },
+        {
+          "type": "mrkdwn",
+          "text": f"*Created at:*\n {pr_created_at}"
+        },
+        {
+          "type": "mrkdwn",
+          "text": f"*Last Updated:*\n {pr_updated_at}"
+        }
+      ]
+    }
+  ]
+
+
+client.chat_postMessage(
+    channel=CHANNEL,
+    text="spaCy universe project PR alert",
+    blocks=blocks
+)
diff --git a/.github/workflows/spacy_universe_alert.yml b/.github/workflows/spacy_universe_alert.yml
new file mode 100644
index 000000000..e02d93985
--- /dev/null
+++ b/.github/workflows/spacy_universe_alert.yml
@@ -0,0 +1,30 @@
+name: spaCy universe project alert
+
+on:
+  pull_request:
+    paths:
+      - "website/meta/universe.json"
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Dump GitHub context
+        env:
+          GITHUB_CONTEXT: ${{ toJson(github) }}
+          PR_NUMBER: ${{github.event.number}}
+        run: |
+          echo "$GITHUB_CONTEXT"
+
+      - uses: actions/checkout@v1
+      - uses: actions/setup-python@v1
+      - name: Install Bernadette app dependency and send an alert
+        env:
+          SLACK_BOT_TOKEN: ${{ secrets.SLACK_BOT_TOKEN }}
+          GITHUB_CONTEXT: ${{ toJson(github) }}
+          CHANNEL: "#alerts-universe"
+        run: |
+          pip install slack-sdk==3.17.2 aiohttp==3.8.1
+          echo "$CHANNEL"
+          python .github/spacy_universe_alert.py "$GITHUB_CONTEXT"
diff --git a/website/meta/universe.json b/website/meta/universe.json
index 01ed91c67..b11d829ec 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -2983,6 +2983,7 @@
                 "from pysbd.utils import PySBDFactory",
                 "",
                 "nlp = spacy.blank('en')",
+                "# Caution: works with spaCy<=2.x.x",
                 "nlp.add_pipe(PySBDFactory(nlp))",
                 "",
                 "doc = nlp('My name is Jonas E. Smith. Please turn to p. 55.')",

From 86ee26e3c29aae7a5bb56517de1e1c4ec98f41be Mon Sep 17 00:00:00 2001
From: Nipun Sadvilkar <nipunsadvilkar@gmail.com>
Date: Thu, 7 Jul 2022 19:43:50 +0530
Subject: [PATCH 021/174] Use `pull_request_target` event for spaCy universe GA
 trigger (#11097)

---
 .github/workflows/spacy_universe_alert.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/spacy_universe_alert.yml b/.github/workflows/spacy_universe_alert.yml
index e02d93985..cbbf14c6e 100644
--- a/.github/workflows/spacy_universe_alert.yml
+++ b/.github/workflows/spacy_universe_alert.yml
@@ -1,7 +1,7 @@
 name: spaCy universe project alert
 
 on:
-  pull_request:
+  pull_request_target:
     paths:
       - "website/meta/universe.json"
 

From e7fd06bdbe45ea406df437ab0f0cb6a3c85193f0 Mon Sep 17 00:00:00 2001
From: "github-actions[bot]"
 <41898282+github-actions[bot]@users.noreply.github.com>
Date: Fri, 8 Jul 2022 18:43:25 +0900
Subject: [PATCH 022/174] Auto-format code with black (#11099)

Co-authored-by: explosion-bot <explosion-bot@users.noreply.github.com>
---
 spacy/tests/conftest.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/spacy/tests/conftest.py b/spacy/tests/conftest.py
index 1117c6cf6..eb643ec2f 100644
--- a/spacy/tests/conftest.py
+++ b/spacy/tests/conftest.py
@@ -4,9 +4,10 @@ from hypothesis import settings
 
 # Functionally disable deadline settings for tests
 # to prevent spurious test failures in CI builds.
-settings.register_profile("no_deadlines", deadline=2*60*1000) # in ms
+settings.register_profile("no_deadlines", deadline=2 * 60 * 1000)  # in ms
 settings.load_profile("no_deadlines")
 
+
 def pytest_addoption(parser):
     try:
         parser.addoption("--slow", action="store_true", help="include slow tests")

From be9e17c0e41988ddd53a68f5239cc182026ad499 Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Fri, 8 Jul 2022 11:45:56 +0200
Subject: [PATCH 023/174] Add docs for compiling with build constraints
 (#11081)

---
 website/docs/usage/index.md | 36 ++++++++++++++++++++++++++++++++++++
 1 file changed, 36 insertions(+)

diff --git a/website/docs/usage/index.md b/website/docs/usage/index.md
index d2aa08d73..2dfe2acaa 100644
--- a/website/docs/usage/index.md
+++ b/website/docs/usage/index.md
@@ -195,6 +195,42 @@ How to install compilers and related build tools:
   [Visual Studio Express](https://www.visualstudio.com/vs/visual-studio-express/)
   that matches the version that was used to compile your Python interpreter.
 
+#### Using build constraints when compiling from source
+
+If you install spaCy from source or with `pip` for platforms where there are not
+binary wheels on PyPI, you may need to use build constraints if any package in
+your environment requires an older version of `numpy`.
+
+If `numpy` gets downgraded from the most recent release at any point after
+you've compiled `spacy`, you might see an error that looks like this:
+
+```none
+numpy.ndarray size changed, may indicate binary incompatibility.
+```
+
+To fix this, create a new virtual environment and install `spacy` and all of its
+dependencies using build constraints.
+[Build constraints](https://pip.pypa.io/en/stable/user_guide/#constraints-files)
+specify an older version of `numpy` that is only used while compiling `spacy`,
+and then your runtime environment can use any newer version of `numpy` and still
+be compatible. In addition, use `--no-cache-dir` to ignore any previously cached
+wheels so that all relevant packages are recompiled from scratch:
+
+```shell
+PIP_CONSTRAINT=https://raw.githubusercontent.com/explosion/spacy/master/build-constraints.txt \
+pip install spacy --no-cache-dir
+```
+
+Our build constraints currently specify the oldest supported `numpy` available
+on PyPI for `x86_64` and `aarch64`. Depending on your platform and environment,
+you may want to customize the specific versions of `numpy`. For other platforms,
+you can have a look at SciPy's
+[`oldest-supported-numpy`](https://github.com/scipy/oldest-supported-numpy/blob/main/setup.cfg)
+package to see what the oldest recommended versions of `numpy` are.
+
+(_Warning_: don't use `pip install -c constraints.txt` instead of
+`PIP_CONSTRAINT`, since this isn't applied to the isolated build environments.)
+
 #### Additional options for developers {#source-developers}
 
 Some additional options may be useful for spaCy developers who are editing the

From f38aff4ec9a5022dad0f216e1b6cd74699b1d8a6 Mon Sep 17 00:00:00 2001
From: Madeesh Kannan <shadeMe@users.noreply.github.com>
Date: Fri, 8 Jul 2022 13:36:12 +0200
Subject: [PATCH 024/174] Add examples for new explosion bot commands (#11082)

* Add examples for new explosion bot commands

* Update extra/DEVELOPER_DOCS/ExplosionBot.md

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
---
 extra/DEVELOPER_DOCS/ExplosionBot.md | 44 ++++++++++++++++++++--------
 1 file changed, 32 insertions(+), 12 deletions(-)

diff --git a/extra/DEVELOPER_DOCS/ExplosionBot.md b/extra/DEVELOPER_DOCS/ExplosionBot.md
index eebec1a06..791b1f229 100644
--- a/extra/DEVELOPER_DOCS/ExplosionBot.md
+++ b/extra/DEVELOPER_DOCS/ExplosionBot.md
@@ -16,21 +16,41 @@ To summon the robot, write a github comment on the issue/PR you wish to test. Th
 
 Some things to note:
 
-* The `@explosion-bot please` must be the beginning of the command - you cannot add anything in front of this or else the robot won't know how to parse it. Adding anything at the end aside from the test name will also confuse the robot, so keep it simple!
-* The command name (such as `test_gpu`) must be one of the tests that the bot knows how to run. The available commands are documented in the bot's [workflow config](https://github.com/explosion/spaCy/blob/master/.github/workflows/explosionbot.yml#L26) and must match exactly one of the commands listed there.
-* The robot can't do multiple things at once, so if you want it to run multiple tests, you'll have to summon it with one comment per test.
-* For the `test_gpu` command, you can specify an optional thinc branch (from the spaCy repo) or a spaCy branch (from the thinc repo) with either the `--thinc-branch` or `--spacy-branch` flags. By default, the bot will pull in the PR branch from the repo where the command was issued, and the main branch of the other repository. However, if you need to run against another branch, you can say (for example):
+- The `@explosion-bot please` must be the beginning of the command - you cannot add anything in front of this or else the robot won't know how to parse it. Adding anything at the end aside from the test name will also confuse the robot, so keep it simple!
+- The command name (such as `test_gpu`) must be one of the tests that the bot knows how to run. The available commands are documented in the bot's [workflow config](https://github.com/explosion/spaCy/blob/master/.github/workflows/explosionbot.yml#L26) and must match exactly one of the commands listed there.
+- The robot can't do multiple things at once, so if you want it to run multiple tests, you'll have to summon it with one comment per test.
 
-```
-@explosion-bot please test_gpu --thinc-branch develop
-```
-You can also specify a branch from an unmerged PR:
-```
-@explosion-bot please test_gpu --thinc-branch refs/pull/633/head
-```
+### Examples
+
+- Execute spaCy slow GPU tests with a custom thinc branch from a spaCy PR:
+
+  ```
+  @explosion-bot please test_slow_gpu --thinc-branch <branch_name>
+  ```
+
+  `branch_name` can either be a named branch, e.g: `develop`, or an unmerged PR, e.g: `refs/pull/<pr_number>/head`.
+
+- Execute spaCy Transformers GPU tests from a spaCy PR:
+
+  ```
+  @explosion-bot please test_gpu --run-on spacy-transformers --run-on-branch master --spacy-branch current_pr
+  ```
+
+  This will launch the GPU pipeline for the `spacy-transformers` repo on its `master` branch, using the current spaCy PR's branch to build spaCy.
+
+- General info about supported commands.
+
+  ```
+  @explosion-bot please info
+  ```
+
+- Help text for a specific command
+  ```
+  @explosion-bot please <command> --help
+  ```
 
 ## Troubleshooting
 
-If the robot isn't responding to commands as expected, you can check its logs in the [Github Action](https://github.com/explosion/spaCy/actions/workflows/explosionbot.yml). 
+If the robot isn't responding to commands as expected, you can check its logs in the [Github Action](https://github.com/explosion/spaCy/actions/workflows/explosionbot.yml).
 
 For each command sent to the bot, there should be a run of the `explosion-bot` workflow. In the `Install and run explosion-bot` step, towards the ends of the logs you should see info about the configuration that the bot was run with, as well as any errors that the bot encountered.

From 397197ec0e6ad73c2878c29bf525e3fca7604d6d Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Fri, 8 Jul 2022 14:58:01 +0200
Subject: [PATCH 025/174] Extend to mypy<0.970 (#11100)

---
 requirements.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/requirements.txt b/requirements.txt
index 3b77140f6..2d0c91f67 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -30,7 +30,7 @@ pytest-timeout>=1.3.0,<2.0.0
 mock>=2.0.0,<3.0.0
 flake8>=3.8.0,<3.10.0
 hypothesis>=3.27.0,<7.0.0
-mypy>=0.910,<=0.960
+mypy>=0.910,<0.970
 types-dataclasses>=0.1.3; python_version < "3.7"
 types-mock>=0.1.1
 types-requests

From 66d6461c8ff01d5691a62a8eafb31efef90cf91d Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Fri, 8 Jul 2022 17:52:41 +0200
Subject: [PATCH 026/174] Use thinc v8.1 (#11101)

---
 pyproject.toml   | 2 +-
 requirements.txt | 2 +-
 setup.cfg        | 4 ++--
 3 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 4e388e54f..317c5fdbe 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -5,7 +5,7 @@ requires = [
     "cymem>=2.0.2,<2.1.0",
     "preshed>=3.0.2,<3.1.0",
     "murmurhash>=0.28.0,<1.1.0",
-    "thinc>=8.1.0.dev3,<8.2.0",
+    "thinc>=8.1.0,<8.2.0",
     "pathy",
     "numpy>=1.15.0",
 ]
diff --git a/requirements.txt b/requirements.txt
index 2d0c91f67..f81a8f631 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -3,7 +3,7 @@ spacy-legacy>=3.0.9,<3.1.0
 spacy-loggers>=1.0.0,<2.0.0
 cymem>=2.0.2,<2.1.0
 preshed>=3.0.2,<3.1.0
-thinc>=8.1.0.dev3,<8.2.0
+thinc>=8.1.0,<8.2.0
 ml_datasets>=0.2.0,<0.3.0
 murmurhash>=0.28.0,<1.1.0
 wasabi>=0.9.1,<1.1.0
diff --git a/setup.cfg b/setup.cfg
index 68d9cdd67..61bf36f8a 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -38,7 +38,7 @@ setup_requires =
     cymem>=2.0.2,<2.1.0
     preshed>=3.0.2,<3.1.0
     murmurhash>=0.28.0,<1.1.0
-    thinc>=8.1.0.dev3,<8.2.0
+    thinc>=8.1.0,<8.2.0
 install_requires =
     # Our libraries
     spacy-legacy>=3.0.9,<3.1.0
@@ -46,7 +46,7 @@ install_requires =
     murmurhash>=0.28.0,<1.1.0
     cymem>=2.0.2,<2.1.0
     preshed>=3.0.2,<3.1.0
-    thinc>=8.1.0.dev3,<8.2.0
+    thinc>=8.1.0,<8.2.0
     wasabi>=0.9.1,<1.1.0
     srsly>=2.4.3,<3.0.0
     catalogue>=2.0.6,<2.1.0

From dc38a0f07979c5148e8278c79c63ccf6f797ed22 Mon Sep 17 00:00:00 2001
From: Richard Hudson <richard@explosion.ai>
Date: Fri, 8 Jul 2022 19:19:48 +0200
Subject: [PATCH 027/174] Change demo URL (#11102)

---
 website/meta/universe.json | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/website/meta/universe.json b/website/meta/universe.json
index b11d829ec..29d436ec4 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -2695,7 +2695,7 @@
             "slogan": "Information extraction from English and German texts based on predicate logic",
             "github": "explosion/holmes-extractor",
             "url": "https://github.com/explosion/holmes-extractor",
-            "description": "Holmes is a Python 3 library that supports a number of use cases involving information extraction from English and German texts, including chatbot, structural extraction, topic matching and supervised document classification. There is a [website demonstrating intelligent search based on topic matching](https://demo.holmes.prod.demos.explosion.services).",
+            "description": "Holmes is a Python 3 library that supports a number of use cases involving information extraction from English and German texts, including chatbot, structural extraction, topic matching and supervised document classification. There is a [website demonstrating intelligent search based on topic matching](https://holmes-demo.explosion.services).",
             "pip": "holmes-extractor",
             "category": ["pipeline", "standalone"],
             "tags": ["chatbots", "text-processing"],

From 36cb2029a9accea40285f62c4af365cb974b2ccd Mon Sep 17 00:00:00 2001
From: Peter Baumgartner <5107405+pmbaumgartner@users.noreply.github.com>
Date: Fri, 8 Jul 2022 13:20:13 -0400
Subject: [PATCH 028/174] displaCy Spans Vertical Alignment Fix 2 (#11092)

* add in span render slot fix

* fix spacing off by one

* rm demo

* adjust comments

* fix whitespace and overlap issue
---
 spacy/displacy/render.py | 61 ++++++++++++++++++++++++++++++++++------
 1 file changed, 53 insertions(+), 8 deletions(-)

diff --git a/spacy/displacy/render.py b/spacy/displacy/render.py
index a730ce522..50dc3466c 100644
--- a/spacy/displacy/render.py
+++ b/spacy/displacy/render.py
@@ -130,26 +130,56 @@ class SpanRenderer:
         title (str / None): Document title set in Doc.user_data['title'].
         """
         per_token_info = []
+        # we must sort so that we can correctly describe when spans need to "stack"
+        # which is determined by their start token, then span length (longer spans on top),
+        # then break any remaining ties with the span label
+        spans = sorted(
+            spans,
+            key=lambda s: (
+                s["start_token"],
+                -(s["end_token"] - s["start_token"]),
+                s["label"],
+            ),
+        )
+        for s in spans:
+            # this is the vertical 'slot' that the span will be rendered in
+            # vertical_position = span_label_offset + (offset_step * (slot - 1))
+            s["render_slot"] = 0
         for idx, token in enumerate(tokens):
             # Identify if a token belongs to a Span (and which) and if it's a
             # start token of said Span. We'll use this for the final HTML render
             token_markup: Dict[str, Any] = {}
             token_markup["text"] = token
+            concurrent_spans = 0
             entities = []
             for span in spans:
                 ent = {}
                 if span["start_token"] <= idx < span["end_token"]:
+                    concurrent_spans += 1
+                    span_start = idx == span["start_token"]
                     ent["label"] = span["label"]
-                    ent["is_start"] = True if idx == span["start_token"] else False
+                    ent["is_start"] = span_start
+                    if span_start:
+                        # When the span starts, we need to know how many other
+                        # spans are on the 'span stack' and will be rendered.
+                        # This value becomes the vertical render slot for this entire span
+                        span["render_slot"] = concurrent_spans
+                    ent["render_slot"] = span["render_slot"]
                     kb_id = span.get("kb_id", "")
                     kb_url = span.get("kb_url", "#")
                     ent["kb_link"] = (
                         TPL_KB_LINK.format(kb_id=kb_id, kb_url=kb_url) if kb_id else ""
                     )
                     entities.append(ent)
+                else:
+                    # We don't specifically need to do this since we loop
+                    # over tokens and spans sorted by their start_token,
+                    # so we'll never use a span again after the last token it appears in,
+                    # but if we were to use these spans again we'd want to make sure
+                    # this value was reset correctly.
+                    span["render_slot"] = 0
             token_markup["entities"] = entities
             per_token_info.append(token_markup)
-
         markup = self._render_markup(per_token_info)
         markup = TPL_SPANS.format(content=markup, dir=self.direction)
         if title:
@@ -160,8 +190,12 @@ class SpanRenderer:
         """Render the markup from per-token information"""
         markup = ""
         for token in per_token_info:
-            entities = sorted(token["entities"], key=lambda d: d["label"])
-            if entities:
+            entities = sorted(token["entities"], key=lambda d: d["render_slot"])
+            # Whitespace tokens disrupt the vertical space (no line height) so that the
+            # span indicators get misaligned. We don't render them as individual
+            # tokens anyway, so we'll just not display a span indicator either.
+            is_whitespace = token["text"].strip() == ""
+            if entities and not is_whitespace:
                 slices = self._get_span_slices(token["entities"])
                 starts = self._get_span_starts(token["entities"])
                 total_height = (
@@ -182,10 +216,18 @@ class SpanRenderer:
     def _get_span_slices(self, entities: List[Dict]) -> str:
         """Get the rendered markup of all Span slices"""
         span_slices = []
-        for entity, step in zip(entities, itertools.count(step=self.offset_step)):
+        for entity in entities:
+            # rather than iterate over multiples of offset_step, we use entity['render_slot']
+            # to determine the vertical position, since that tells where
+            # the span starts vertically so we can extend it horizontally,
+            # past other spans that might have already ended
             color = self.colors.get(entity["label"].upper(), self.default_color)
+            top_offset = self.top_offset + (
+                self.offset_step * (entity["render_slot"] - 1)
+            )
             span_slice = self.span_slice_template.format(
-                bg=color, top_offset=self.top_offset + step
+                bg=color,
+                top_offset=top_offset,
             )
             span_slices.append(span_slice)
         return "".join(span_slices)
@@ -193,12 +235,15 @@ class SpanRenderer:
     def _get_span_starts(self, entities: List[Dict]) -> str:
         """Get the rendered markup of all Span start tokens"""
         span_starts = []
-        for entity, step in zip(entities, itertools.count(step=self.offset_step)):
+        for entity in entities:
             color = self.colors.get(entity["label"].upper(), self.default_color)
+            top_offset = self.top_offset + (
+                self.offset_step * (entity["render_slot"] - 1)
+            )
             span_start = (
                 self.span_start_template.format(
                     bg=color,
-                    top_offset=self.top_offset + step,
+                    top_offset=top_offset,
                     label=entity["label"],
                     kb_link=entity["kb_link"],
                 )

From 3701039c1f688b2296499944087a581e02fc041a Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Fri, 8 Jul 2022 19:21:17 +0200
Subject: [PATCH 029/174] Tweak build jobs setting, update install docs
 (#11077)

* Restrict SPACY_NUM_BUILD_JOBS to only override if set

* Update install docs
---
 setup.py                    | 10 +++++++---
 website/docs/usage/index.md | 30 +++++++++++++++++++-----------
 2 files changed, 26 insertions(+), 14 deletions(-)

diff --git a/setup.py b/setup.py
index 377a7689d..ec1bd35fa 100755
--- a/setup.py
+++ b/setup.py
@@ -126,8 +126,8 @@ class build_ext_options:
 
 class build_ext_subclass(build_ext, build_ext_options):
     def build_extensions(self):
-        if not self.parallel:
-            self.parallel = int(os.environ.get("SPACY_NUM_BUILD_JOBS", 1))
+        if self.parallel is None and os.environ.get("SPACY_NUM_BUILD_JOBS") is not None:
+            self.parallel = int(os.environ.get("SPACY_NUM_BUILD_JOBS"))
         build_ext_options.build_options(self)
         build_ext.build_extensions(self)
 
@@ -208,7 +208,11 @@ def setup_package():
     for name in MOD_NAMES:
         mod_path = name.replace(".", "/") + ".pyx"
         ext = Extension(
-            name, [mod_path], language="c++", include_dirs=include_dirs, extra_compile_args=["-std=c++11"]
+            name,
+            [mod_path],
+            language="c++",
+            include_dirs=include_dirs,
+            extra_compile_args=["-std=c++11"],
         )
         ext_modules.append(ext)
     print("Cythonizing sources")
diff --git a/website/docs/usage/index.md b/website/docs/usage/index.md
index 2dfe2acaa..1f4869606 100644
--- a/website/docs/usage/index.md
+++ b/website/docs/usage/index.md
@@ -130,8 +130,8 @@ grateful to use the work of Chainer's [CuPy](https://cupy.chainer.org) module,
 which provides a numpy-compatible interface for GPU arrays.
 
 spaCy can be installed for a CUDA-compatible GPU by specifying `spacy[cuda]`,
-`spacy[cuda102]`, `spacy[cuda112]`, `spacy[cuda113]`, etc. If you know your
-CUDA version, using the more explicit specifier allows CuPy to be installed via
+`spacy[cuda102]`, `spacy[cuda112]`, `spacy[cuda113]`, etc. If you know your CUDA
+version, using the more explicit specifier allows CuPy to be installed via
 wheel, saving some compilation time. The specifiers should install
 [`cupy`](https://cupy.chainer.org).
 
@@ -236,24 +236,32 @@ package to see what the oldest recommended versions of `numpy` are.
 Some additional options may be useful for spaCy developers who are editing the
 source code and recompiling frequently.
 
-- Install in editable mode. Changes to `.py` files will be reflected as soon as
-  the files are saved, but edits to Cython files (`.pxd`, `.pyx`) will require
-  the `pip install` or `python setup.py build_ext` command below to be run
-  again. Before installing in editable mode, be sure you have removed any
-  previous installs with `pip uninstall spacy`, which you may need to run
-  multiple times to remove all traces of earlier installs.
+- Install in editable mode. Changes to `.py` files will be reflected as soon
+  as the files are saved, but edits to Cython files (`.pxd`, `.pyx`) will
+  require the `pip install` command below to be run again. Before installing in
+  editable mode, be sure you have removed any previous installs with
+  `pip uninstall spacy`, which you may need to run multiple times to remove all
+  traces of earlier installs.
 
   ```bash
   $ pip install -r requirements.txt
   $ pip install --no-build-isolation --editable .
   ```
 
-- Build in parallel using `N` CPUs to speed up compilation and then install in
-  editable mode:
+- Build in parallel. Starting in v3.4.0, you can specify the number of
+  build jobs with the environment variable `SPACY_NUM_BUILD_JOBS`:
 
   ```bash
   $ pip install -r requirements.txt
-  $ python setup.py build_ext --inplace -j N
+  $ SPACY_NUM_BUILD_JOBS=4 pip install --no-build-isolation --editable .
+  ```
+
+- For editable mode and parallel builds with `python setup.py` instead of `pip`
+  (no longer recommended):
+
+  ```bash
+  $ pip install -r requirements.txt
+  $ python setup.py build_ext --inplace -j 4
   $ python setup.py develop
   ```
 

From 5cb6f1ae51118cc200c09fa225c053bd78376db9 Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Mon, 11 Jul 2022 12:20:00 +0200
Subject: [PATCH 030/174] CI: Install with two parallel build jobs (#11111)

---
 .github/azure-steps.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/azure-steps.yml b/.github/azure-steps.yml
index 1f886161a..5d865b452 100644
--- a/.github/azure-steps.yml
+++ b/.github/azure-steps.yml
@@ -40,7 +40,7 @@ steps:
 
   - bash: |
       ${{ parameters.prefix }} SDIST=$(python -c "import os;print(os.listdir('./dist')[-1])" 2>&1)
-      ${{ parameters.prefix }} python -m pip install dist/$SDIST
+      ${{ parameters.prefix }} SPACY_NUM_BUILD_JOBS=2 python -m pip install dist/$SDIST
     displayName: "Install from sdist"
 
   - script: |

From d583626a826c00dfba55f42dc7911d1a4b0b7032 Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Mon, 11 Jul 2022 13:29:35 +0200
Subject: [PATCH 031/174] Update build setup for aarch64 (#11112)

* Extend build constraints for aarch64

* Skip mypy for aarch64
---
 build-constraints.txt | 6 ++++--
 requirements.txt      | 2 +-
 2 files changed, 5 insertions(+), 3 deletions(-)

diff --git a/build-constraints.txt b/build-constraints.txt
index cf5fe3284..956973abf 100644
--- a/build-constraints.txt
+++ b/build-constraints.txt
@@ -1,6 +1,8 @@
 # build version constraints for use with wheelwright + multibuild
-numpy==1.15.0; python_version<='3.7'
-numpy==1.17.3; python_version=='3.8'
+numpy==1.15.0; python_version<='3.7' and platform_machine!='aarch64'
+numpy==1.19.2; python_version<='3.7' and platform_machine=='aarch64'
+numpy==1.17.3; python_version=='3.8' and platform_machine!='aarch64'
+numpy==1.19.2; python_version=='3.8' and platform_machine=='aarch64'
 numpy==1.19.3; python_version=='3.9'
 numpy==1.21.3; python_version=='3.10'
 numpy; python_version>='3.11'
diff --git a/requirements.txt b/requirements.txt
index f81a8f631..437dd415a 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -30,7 +30,7 @@ pytest-timeout>=1.3.0,<2.0.0
 mock>=2.0.0,<3.0.0
 flake8>=3.8.0,<3.10.0
 hypothesis>=3.27.0,<7.0.0
-mypy>=0.910,<0.970
+mypy>=0.910,<0.970; platform_machine!='aarch64'
 types-dataclasses>=0.1.3; python_version < "3.7"
 types-mock>=0.1.1
 types-requests

From 11f859c1323e0e1889c59dfabfd207946bf5207b Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Mon, 11 Jul 2022 15:36:31 +0200
Subject: [PATCH 032/174] Docs for v3.4 (#11057)

* Add draft of v3.4 usage

* Add Croatian models

* Add Matcher min/max

* Update release notes

* Minor edits

* Add updates, tables

* Update pydantic/mypy versions

* Update version in README

* Fix sidebar
---
 README.md                      |   2 +-
 website/docs/usage/v3-4.md     | 143 +++++++++++++++++++++++++++++++++
 website/meta/languages.json    |   7 +-
 website/meta/sidebars.json     |   4 +-
 website/src/templates/index.js |   4 +-
 5 files changed, 155 insertions(+), 5 deletions(-)
 create mode 100644 website/docs/usage/v3-4.md

diff --git a/README.md b/README.md
index bcdf0f844..d9ef83e01 100644
--- a/README.md
+++ b/README.md
@@ -16,7 +16,7 @@ production-ready [**training system**](https://spacy.io/usage/training) and easy
 model packaging, deployment and workflow management. spaCy is commercial
 open-source software, released under the MIT license.
 
-💫 **Version 3.3.1 out now!**
+💫 **Version 3.4.0 out now!**
 [Check out the release notes here.](https://github.com/explosion/spaCy/releases)
 
 [![Azure Pipelines](https://img.shields.io/azure-devops/build/explosion-ai/public/8/master.svg?logo=azure-pipelines&style=flat-square&label=build)](https://dev.azure.com/explosion-ai/public/_build?definitionId=8)
diff --git a/website/docs/usage/v3-4.md b/website/docs/usage/v3-4.md
new file mode 100644
index 000000000..7cc4570d5
--- /dev/null
+++ b/website/docs/usage/v3-4.md
@@ -0,0 +1,143 @@
+---
+title: What's New in v3.4
+teaser: New features and how to upgrade
+menu:
+  - ['New Features', 'features']
+  - ['Upgrading Notes', 'upgrading']
+---
+
+## New features {#features hidden="true"}
+
+spaCy v3.4 brings typing and speed improvements along with new vectors for
+English CNN pipelines and new trained pipelines for Croatian. This release also
+includes prebuilt linux aarch64 wheels for all spaCy dependencies distributed by
+Explosion.
+
+### Typing improvements {#typing}
+
+spaCy v3.4 supports pydantic v1.9 and mypy 0.950+ through extensive updates to
+types in Thinc v8.1.
+
+### Speed improvements {#speed}
+
+- For the parser, use C `saxpy`/`sgemm` provided by the `Ops` implementation in
+  order to use Accelerate through `thinc-apple-ops`.
+- Improved speed of vector lookups.
+- Improved speed for `Example.get_aligned_parse` and `Example.get_aligned`.
+
+## Additional features and improvements
+
+- Min/max `{n,m}` operator for `Matcher` patterns.
+- Language updates:
+  - Improve tokenization for Cyrillic combining diacritics.
+  - Improve English tokenizer exceptions for contractions with
+    this/that/these/those.
+- Updated `spacy project clone` to try both `main` and `master` branches by
+  default.
+- Added confidence threshold for named entity linker.
+- Improved handling of Typer optional default values for `init_config_cli`.
+- Added cycle detection in parser projectivization methods.
+- Added counts for NER labels in `debug data`.
+- Support for adding NVTX ranges to `TrainablePipe` components.
+- Support env variable `SPACY_NUM_BUILD_JOBS` to specify the number of build
+  jobs to run in parallel with `pip`.
+
+## Trained pipelines {#pipelines}
+
+### New trained pipelines {#new-pipelines}
+
+v3.4 introduces new CPU/CNN pipelines for Croatian, which use the trainable
+lemmatizer and [floret vectors](https://github.com/explosion/floret). Due to the
+use of [Bloom embeddings](https://explosion.ai/blog/bloom-embeddings) and
+subwords, the pipelines have compact vectors with no out-of-vocabulary words.
+
+| Package                                         | UPOS | Parser LAS | NER F |
+| ----------------------------------------------- | ---: | ---------: | ----: |
+| [`hr_core_news_sm`](/models/hr#hr_core_news_sm) | 96.6 |       77.5 |  76.1 |
+| [`hr_core_news_md`](/models/hr#hr_core_news_md) | 97.3 |       80.1 |  81.8 |
+| [`hr_core_news_lg`](/models/hr#hr_core_news_lg) | 97.5 |       80.4 |  83.0 |
+
+### Pipeline updates {#pipeline-updates}
+
+All CNN pipelines have been extended with whitespace augmentation.
+
+The English CNN pipelines have new word vectors:
+
+| Package                                         | Model Version |  TAG | Parser LAS | NER F |
+| ----------------------------------------------- | ------------- | ---: | ---------: | ----: |
+| [`en_core_news_md`](/models/en#en_core_news_md) | v3.3.0        | 97.3 |       90.1 |  84.6 |
+| [`en_core_news_md`](/models/en#en_core_news_lg) | v3.4.0        | 97.2 |       90.3 |  85.5 |
+| [`en_core_news_lg`](/models/en#en_core_news_md) | v3.3.0        | 97.4 |       90.1 |  85.3 |
+| [`en_core_news_lg`](/models/en#en_core_news_lg) | v3.4.0        | 97.3 |       90.2 |  85.6 |
+
+## Notes about upgrading from v3.3 {#upgrading}
+
+### Doc.has_vector
+
+`Doc.has_vector` now matches `Token.has_vector` and `Span.has_vector`: it
+returns `True` if at least one token in the doc has a vector rather than
+checking only whether the vocab contains vectors.
+
+### Using trained pipelines with floret vectors
+
+If you're using a trained pipeline for Croatian, Finnish, Korean or Swedish with
+new texts and working with `Doc` objects, you shouldn't notice any difference
+between floret vectors and default vectors.
+
+If you use vectors for similarity comparisons, there are a few differences,
+mainly because a floret pipeline doesn't include any kind of frequency-based
+word list similar to the list of in-vocabulary vector keys with default vectors.
+
+- If your workflow iterates over the vector keys, you should use an external
+  word list instead:
+
+  ```diff
+  - lexemes = [nlp.vocab[orth] for orth in nlp.vocab.vectors]
+  + lexemes = [nlp.vocab[word] for word in external_word_list]
+  ```
+
+- `Vectors.most_similar` is not supported because there's no fixed list of
+  vectors to compare your vectors to.
+
+### Pipeline package version compatibility {#version-compat}
+
+> #### Using legacy implementations
+>
+> In spaCy v3, you'll still be able to load and reference legacy implementations
+> via [`spacy-legacy`](https://github.com/explosion/spacy-legacy), even if the
+> components or architectures change and newer versions are available in the
+> core library.
+
+When you're loading a pipeline package trained with an earlier version of spaCy
+v3, you will see a warning telling you that the pipeline may be incompatible.
+This doesn't necessarily have to be true, but we recommend running your
+pipelines against your test suite or evaluation data to make sure there are no
+unexpected results.
+
+If you're using one of the [trained pipelines](/models) we provide, you should
+run [`spacy download`](/api/cli#download) to update to the latest version. To
+see an overview of all installed packages and their compatibility, you can run
+[`spacy validate`](/api/cli#validate).
+
+If you've trained your own custom pipeline and you've confirmed that it's still
+working as expected, you can update the spaCy version requirements in the
+[`meta.json`](/api/data-formats#meta):
+
+```diff
+- "spacy_version": ">=3.3.0,<3.4.0",
++ "spacy_version": ">=3.3.0,<3.5.0",
+```
+
+### Updating v3.3 configs
+
+To update a config from spaCy v3.3 with the new v3.4 settings, run
+[`init fill-config`](/api/cli#init-fill-config):
+
+```cli
+$ python -m spacy init fill-config config-v3.3.cfg config-v3.4.cfg
+```
+
+In many cases ([`spacy train`](/api/cli#train),
+[`spacy.load`](/api/top-level#spacy.load)), the new defaults will be filled in
+automatically, but you'll need to fill in the new settings to run
+[`debug config`](/api/cli#debug) and [`debug data`](/api/cli#debug-data).
diff --git a/website/meta/languages.json b/website/meta/languages.json
index 64ca7a082..6bc2309ed 100644
--- a/website/meta/languages.json
+++ b/website/meta/languages.json
@@ -162,7 +162,12 @@
         {
             "code": "hr",
             "name": "Croatian",
-            "has_examples": true
+            "has_examples": true,
+            "models": [
+                "hr_core_news_sm",
+                "hr_core_news_md",
+                "hr_core_news_lg"
+            ]
         },
         {
             "code": "hsb",
diff --git a/website/meta/sidebars.json b/website/meta/sidebars.json
index 1bc395a66..1b743636c 100644
--- a/website/meta/sidebars.json
+++ b/website/meta/sidebars.json
@@ -12,7 +12,9 @@
                     { "text": "New in v3.0", "url": "/usage/v3" },
                     { "text": "New in v3.1", "url": "/usage/v3-1" },
                     { "text": "New in v3.2", "url": "/usage/v3-2" },
-                    { "text": "New in v3.3", "url": "/usage/v3-3" }
+                    { "text": "New in v3.2", "url": "/usage/v3-2" },
+                    { "text": "New in v3.3", "url": "/usage/v3-3" },
+                    { "text": "New in v3.4", "url": "/usage/v3-4" }
                 ]
             },
             {
diff --git a/website/src/templates/index.js b/website/src/templates/index.js
index bdbdbd431..a0ba4503e 100644
--- a/website/src/templates/index.js
+++ b/website/src/templates/index.js
@@ -120,8 +120,8 @@ const AlertSpace = ({ nightly, legacy }) => {
 }
 
 const navAlert = (
-    <Link to="/usage/v3-3" hidden>
-        <strong>💥 Out now:</strong> spaCy v3.3
+    <Link to="/usage/v3-4" hidden>
+        <strong>💥 Out now:</strong> spaCy v3.4
     </Link>
 )
 

From 2fa983aa2e746bbd71ac9935483ab99c6322d85e Mon Sep 17 00:00:00 2001
From: Nicolai Bjerre Pedersen <mr.bjerre@gmail.com>
Date: Tue, 12 Jul 2022 13:47:35 +0200
Subject: [PATCH 033/174] Fix span typings (#11119)

Add id, id_ to span.pyi.
---
 spacy/tokens/span.pyi | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/spacy/tokens/span.pyi b/spacy/tokens/span.pyi
index 4a4149652..617e3d19d 100644
--- a/spacy/tokens/span.pyi
+++ b/spacy/tokens/span.pyi
@@ -120,6 +120,10 @@ class Span:
     ent_id: int
     ent_id_: str
     @property
+    def id(self) -> int: ...
+    @property
+    def id_(self) -> str: ...
+    @property
     def orth_(self) -> str: ...
     @property
     def lemma_(self) -> str: ...

From 2235e3520c763fd3e25118e6cc104def3f75330f Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Tue, 12 Jul 2022 15:20:33 +0200
Subject: [PATCH 034/174] Update binder version in docs (#11124)

---
 website/meta/site.json | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/website/meta/site.json b/website/meta/site.json
index 97051011f..360a72178 100644
--- a/website/meta/site.json
+++ b/website/meta/site.json
@@ -28,7 +28,7 @@
     },
     "binderUrl": "explosion/spacy-io-binder",
     "binderBranch": "spacy.io",
-    "binderVersion": "3.0",
+    "binderVersion": "3.4",
     "sections": [
         { "id": "usage", "title": "Usage Documentation", "theme": "blue" },
         { "id": "models", "title": "Models Documentation", "theme": "blue" },

From 1caa2d1d16babb43b346e3eebcf229367bcc47f5 Mon Sep 17 00:00:00 2001
From: Maarten Grootendorst <maartengrootendorst@gmail.com>
Date: Tue, 19 Jul 2022 12:37:18 +0200
Subject: [PATCH 035/174] Added BERTopic to Spacy Universe (#11159)

* Added BERTopic to Spacy Universe

* Fix no render of visualization
---
 website/meta/universe.json | 31 +++++++++++++++++++++++++++++++
 1 file changed, 31 insertions(+)

diff --git a/website/meta/universe.json b/website/meta/universe.json
index 29d436ec4..53cc53024 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -544,6 +544,37 @@
                 "website": "https://koaning.io"
             }
         },
+        {
+            "id": "bertopic",
+            "title": "BERTopic",
+            "slogan": "Leveraging BERT and c-TF-IDF to create easily interpretable topics.",
+            "description": "BERTopic is a topic modeling technique that leverages embedding models and c-TF-IDF to create dense clusters allowing for easily interpretable topics whilst keeping important words in the topic descriptions. BERTopic supports guided, (semi-) supervised, hierarchical, and dynamic topic modeling.",
+            "github": "maartengr/bertopic",
+            "pip": "bertopic",
+            "thumb": "https://i.imgur.com/Rx2LfBm.png",
+            "image": "https://raw.githubusercontent.com/MaartenGr/BERTopic/master/images/topic_visualization.gif",
+            "code_example": [
+                "import spacy",
+                "from bertopic import BERTopic",
+                "from sklearn.datasets import fetch_20newsgroups",
+                "",
+                "docs = fetch_20newsgroups(subset='all',  remove=('headers', 'footers', 'quotes'))['data']",
+                "nlp = spacy.load('en_core_web_md', exclude=['tagger', 'parser', 'ner', 'attribute_ruler', 'lemmatizer'])",
+                "",
+                "topic_model = BERTopic(embedding_model=nlp)",
+                "topics, probs = topic_model.fit_transform(docs)",
+                "",
+                "fig = topic_model.visualize_topics()",
+                "fig.show()"
+            ],
+            "category": ["visualizers", "training"],
+            "author": "Maarten Grootendorst",
+            "author_links": {
+                "twitter": "maartengr",
+                "github": "maartengr",
+                "website": "https://maartengrootendorst.com"
+            }
+        },
         {
             "id": "tokenwiser",
             "title": "tokenwiser",

From 7ff52c02a11ba80128e55a98b3213d6c9f5aa80a Mon Sep 17 00:00:00 2001
From: Lucas Terriel <44713216+Lucaterre@users.noreply.github.com>
Date: Sun, 24 Jul 2022 10:10:29 +0200
Subject: [PATCH 036/174] Update meta for spacyfishing in spaCy Universe
 (#11185)

* add new logo for spacyfishing to update spacy universe

* change logo location
---
 website/meta/universe.json | 1 +
 1 file changed, 1 insertion(+)

diff --git a/website/meta/universe.json b/website/meta/universe.json
index 53cc53024..6a981e9f0 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -22,6 +22,7 @@
                 "## Set parameter `extra_info` to `True` and check also span._.description, span._.src_description, span._.normal_term, span._.other_ids"
             ],
             "category": ["models", "pipeline"],
+            "image": "https://raw.githubusercontent.com/Lucaterre/spacyfishing/main/docs/spacyfishing-logo-resized.png",
             "tags": ["NER", "NEL"],
             "author": "Lucas Terriel",
             "author_links": {

From a5aa3a818fba61cffa7b5738ec24a03700f18468 Mon Sep 17 00:00:00 2001
From: Dan Radenkovic <bogdan.radenkovic@gmail.com>
Date: Sun, 24 Jul 2022 10:16:36 +0200
Subject: [PATCH 037/174] fix docs (#11123)

---
 website/docs/api/matcher.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/website/docs/api/matcher.md b/website/docs/api/matcher.md
index ab88c4194..8cc446c6a 100644
--- a/website/docs/api/matcher.md
+++ b/website/docs/api/matcher.md
@@ -199,7 +199,7 @@ will be overwritten.
 >    [{"LOWER": "hello"}, {"LOWER": "world"}],
 >    [{"ORTH": "Google"}, {"ORTH": "Maps"}]
 > ]
-> matcher.add("TEST_PATTERNS", patterns)
+> matcher.add("TEST_PATTERNS", patterns, on_match=on_match)
 > doc = nlp("HELLO WORLD on Google Maps.")
 > matches = matcher(doc)
 > ```

From 93960dc4b59510b011c12079fbba09eb8219f74e Mon Sep 17 00:00:00 2001
From: 0xpeIpeI <63499912+lll-lll-lll-lll@users.noreply.github.com>
Date: Sun, 24 Jul 2022 19:01:04 +0900
Subject: [PATCH 038/174] [universe project] create English interpretation
 project  (#11184)

* [add] my universe  project setting

* [modify] A few adjustments

* [Modify] change package description
---
 website/meta/universe.json | 31 +++++++++++++++++++++++++++++++
 1 file changed, 31 insertions(+)

diff --git a/website/meta/universe.json b/website/meta/universe.json
index 6a981e9f0..3c8afbd9a 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -4023,6 +4023,37 @@
                     "description": "Episodes about spaCy or interviews with the spaCy team"
                 }
             ]
+        },
+        {
+            "id": "sent-pattern",
+            "title": "English Interpretation Sentence Pattern",
+            "slogan": "English interpretation for accurate translation from English to Japanese",
+            "description": "This package categorizes English sentences into one of five basic sentence patterns and identifies the subject, verb, object, and other components. The five basic sentence patterns are based on C. T. Onions's Advanced English Syntax and are frequently used when teaching English in Japan.",
+            "github": "lll-lll-lll-lll/sent-pattern",
+            "pip": "sent-pattern",
+            "code_example": [
+                "import spacy",
+                "nlp = spacy.load('en_core_web_lg')",
+                "",
+                "nlp.add_pipe('sent_pattern')",
+                "text = 'he gives me something'",
+                "pattern = doc._.sentpattern",
+                "",
+                "print(pattern)",
+                "# FourthSentencePattern (class)",
+                "print(pattern.subject.root)",
+                "# he (Token)",
+                "print(pattern.verb.root)",
+                "# give (Token)"
+            ],
+            "code_language": "python",
+            "author": "Shunpei Nakayama",
+            "author_links": {
+                "twitter": "ExZ79575296",
+                "github": "lll-lll-lll-lll"
+            },
+            "category": ["pipeline"],
+            "tags": ["interpretation", "ja"]
         }
     ]
 }

From 7a99fe3c65074eb70bfac96d1f0c83cbdb7ec2c7 Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Mon, 25 Jul 2022 09:14:50 +0200
Subject: [PATCH 039/174] Move sent-patterns to correct section of
 universe.json (#11192)

---
 website/meta/universe.json | 46 +++++++++++++-------------------------
 1 file changed, 15 insertions(+), 31 deletions(-)

diff --git a/website/meta/universe.json b/website/meta/universe.json
index 3c8afbd9a..a128f0795 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -3935,6 +3935,21 @@
             },
             "category": ["biomedical", "scientific", "research", "pipeline"],
             "tags": ["clinical"]
+        },
+        {
+            "id": "sent-pattern",
+            "title": "English Interpretation Sentence Pattern",
+            "slogan": "English interpretation for accurate translation from English to Japanese",
+            "description": "This package categorizes English sentences into one of five basic sentence patterns and identifies the subject, verb, object, and other components. The five basic sentence patterns are based on C. T. Onions's Advanced English Syntax and are frequently used when teaching English in Japan.",
+            "github": "lll-lll-lll-lll/sent-pattern",
+            "pip": "sent-pattern",
+            "author": "Shunpei Nakayama",
+            "author_links": {
+                "twitter": "ExZ79575296",
+                "github": "lll-lll-lll-lll"
+            },
+            "category": ["pipeline"],
+            "tags": ["interpretation", "ja"]
         }
     ],
 
@@ -4023,37 +4038,6 @@
                     "description": "Episodes about spaCy or interviews with the spaCy team"
                 }
             ]
-        },
-        {
-            "id": "sent-pattern",
-            "title": "English Interpretation Sentence Pattern",
-            "slogan": "English interpretation for accurate translation from English to Japanese",
-            "description": "This package categorizes English sentences into one of five basic sentence patterns and identifies the subject, verb, object, and other components. The five basic sentence patterns are based on C. T. Onions's Advanced English Syntax and are frequently used when teaching English in Japan.",
-            "github": "lll-lll-lll-lll/sent-pattern",
-            "pip": "sent-pattern",
-            "code_example": [
-                "import spacy",
-                "nlp = spacy.load('en_core_web_lg')",
-                "",
-                "nlp.add_pipe('sent_pattern')",
-                "text = 'he gives me something'",
-                "pattern = doc._.sentpattern",
-                "",
-                "print(pattern)",
-                "# FourthSentencePattern (class)",
-                "print(pattern.subject.root)",
-                "# he (Token)",
-                "print(pattern.verb.root)",
-                "# give (Token)"
-            ],
-            "code_language": "python",
-            "author": "Shunpei Nakayama",
-            "author_links": {
-                "twitter": "ExZ79575296",
-                "github": "lll-lll-lll-lll"
-            },
-            "category": ["pipeline"],
-            "tags": ["interpretation", "ja"]
         }
     ]
 }

From 1c12812d1a218f505ccfcd4d958f88ab895ed83e Mon Sep 17 00:00:00 2001
From: Paul O'Leary McCann <polm@dampfkraft.com>
Date: Mon, 25 Jul 2022 16:39:34 +0900
Subject: [PATCH 040/174] Replace link to old label (#11188)

---
 website/src/templates/universe.js | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/website/src/templates/universe.js b/website/src/templates/universe.js
index 10f2520d9..48ffa3add 100644
--- a/website/src/templates/universe.js
+++ b/website/src/templates/universe.js
@@ -142,10 +142,10 @@ const UniverseContent = ({ content = [], categories, theme, pageContext, mdxComp
                         The Universe database is open-source and collected in a simple JSON file.
                         For more details on the formats and available fields, see the documentation.
                         Looking for inspiration your own spaCy plugin or extension? Check out the
-                        <Link to={github() + '/labels/project%20idea'} hideIcon ws>
-                            <InlineCode>project idea</InlineCode>
+                        <Link to={"https://github.com/explosion/spaCy/discussions/categories/new-features-project-ideas/"} hideIcon ws>
+                            project idea
                         </Link>
-                        label on the issue tracker.
+                        section in Discussions.
                     </p>
 
                     <InlineList>

From e5990db71358a4d5f3ad146faf6b33b87d0c231f Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Mon, 25 Jul 2022 18:12:18 +0200
Subject: [PATCH 041/174] Revert "Temporarily skip tests that require
 models/compat"

This reverts commit d9320db7db74b970b3751e38ed6f14de5b7d16d5.
---
 .github/azure-steps.yml | 34 +++++++++++++++++-----------------
 spacy/tests/test_cli.py |  2 --
 2 files changed, 17 insertions(+), 19 deletions(-)

diff --git a/.github/azure-steps.yml b/.github/azure-steps.yml
index 5d865b452..aae08c7f3 100644
--- a/.github/azure-steps.yml
+++ b/.github/azure-steps.yml
@@ -63,12 +63,12 @@ steps:
     displayName: "Run GPU tests"
     condition: eq(${{ parameters.gpu }}, true)
 
-#  - script: |
-#      python -m spacy download ca_core_news_sm
-#      python -m spacy download ca_core_news_md
-#      python -c "import spacy; nlp=spacy.load('ca_core_news_sm'); doc=nlp('test')"
-#    displayName: 'Test download CLI'
-#    condition: eq(variables['python_version'], '3.8')
+  - script: |
+      python -m spacy download ca_core_news_sm
+      python -m spacy download ca_core_news_md
+      python -c "import spacy; nlp=spacy.load('ca_core_news_sm'); doc=nlp('test')"
+    displayName: 'Test download CLI'
+    condition: eq(variables['python_version'], '3.8')
 
   - script: |
       python -m spacy convert extra/example_data/ner_example_data/ner-token-per-line-conll2003.json .
@@ -92,17 +92,17 @@ steps:
     displayName: 'Test train CLI'
     condition: eq(variables['python_version'], '3.8')
 
-#  - script: |
-#      python -c "import spacy; config = spacy.util.load_config('ner.cfg'); config['components']['ner'] = {'source': 'ca_core_news_sm'}; config.to_disk('ner_source_sm.cfg')"
-#      PYTHONWARNINGS="error,ignore::DeprecationWarning" python -m spacy assemble ner_source_sm.cfg output_dir
-#    displayName: 'Test assemble CLI'
-#    condition: eq(variables['python_version'], '3.8')
-#
-#  - script: |
-#      python -c "import spacy; config = spacy.util.load_config('ner.cfg'); config['components']['ner'] = {'source': 'ca_core_news_md'}; config.to_disk('ner_source_md.cfg')"
-#      python -m spacy assemble ner_source_md.cfg output_dir 2>&1 | grep -q W113
-#    displayName: 'Test assemble CLI vectors warning'
-#    condition: eq(variables['python_version'], '3.8')
+  - script: |
+      python -c "import spacy; config = spacy.util.load_config('ner.cfg'); config['components']['ner'] = {'source': 'ca_core_news_sm'}; config.to_disk('ner_source_sm.cfg')"
+      PYTHONWARNINGS="error,ignore::DeprecationWarning" python -m spacy assemble ner_source_sm.cfg output_dir
+    displayName: 'Test assemble CLI'
+    condition: eq(variables['python_version'], '3.8')
+
+  - script: |
+      python -c "import spacy; config = spacy.util.load_config('ner.cfg'); config['components']['ner'] = {'source': 'ca_core_news_md'}; config.to_disk('ner_source_md.cfg')"
+      python -m spacy assemble ner_source_md.cfg output_dir 2>&1 | grep -q W113
+    displayName: 'Test assemble CLI vectors warning'
+    condition: eq(variables['python_version'], '3.8')
 
   - script: |
       python .github/validate_universe_json.py website/meta/universe.json
diff --git a/spacy/tests/test_cli.py b/spacy/tests/test_cli.py
index fe8b3a8a1..838e00369 100644
--- a/spacy/tests/test_cli.py
+++ b/spacy/tests/test_cli.py
@@ -589,7 +589,6 @@ def test_string_to_list_intify(value):
     assert string_to_list(value, intify=True) == [1, 2, 3]
 
 
-@pytest.mark.skip(reason="Temporarily skip for dev version")
 def test_download_compatibility():
     spec = SpecifierSet("==" + about.__version__)
     spec.prereleases = False
@@ -600,7 +599,6 @@ def test_download_compatibility():
         assert get_minor_version(about.__version__) == get_minor_version(version)
 
 
-@pytest.mark.skip(reason="Temporarily skip for dev version")
 def test_validate_compatibility_table():
     spec = SpecifierSet("==" + about.__version__)
     spec.prereleases = False

From 4ee8a061497ed24ded0fdcaf9b89ba4b28f49e96 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Dani=C3=ABl=20de=20Kok?= <me@danieldk.eu>
Date: Tue, 26 Jul 2022 10:52:01 +0200
Subject: [PATCH 042/174] Fix compatibility with CuPy 9.x (#11194)

After the precomputable affine table of shape [nB, nF, nO, nP] is
computed, padding with shape [1, nF, nO, nP] is assigned to the first
row of the precomputed affine table. However, when we are indexing the
precomputed table, we get a row of shape [nF, nO, nP]. CuPy versions
before 10.0 cannot paper over this shape difference.

This change fixes compatibility with CuPy < 10.0 by squeezing the first
dimension of the padding before assignment.
---
 spacy/ml/_precomputable_affine.py | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/spacy/ml/_precomputable_affine.py b/spacy/ml/_precomputable_affine.py
index 7a25e7574..1c20c622b 100644
--- a/spacy/ml/_precomputable_affine.py
+++ b/spacy/ml/_precomputable_affine.py
@@ -26,7 +26,11 @@ def forward(model, X, is_train):
     Yf = model.ops.alloc2f(X.shape[0] + 1, nF * nO * nP, zeros=False)
     model.ops.gemm(X, W.reshape((nF * nO * nP, nI)), trans2=True, out=Yf[1:])
     Yf = Yf.reshape((Yf.shape[0], nF, nO, nP))
-    Yf[0] = model.get_param("pad")
+
+    # Set padding. Padding has shape (1, nF, nO, nP). Unfortunately, we cannot
+    # change its shape to (nF, nO, nP) without breaking existing models. So
+    # we'll squeeze the first dimension here.
+    Yf[0] = model.ops.xp.squeeze(model.get_param("pad"), 0)
 
     def backward(dY_ids):
         # This backprop is particularly tricky, because we get back a different

From c8f5b752bb00e4d83a92e4919ec2688d47b9aada Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Tue, 26 Jul 2022 10:56:53 +0200
Subject: [PATCH 043/174] Add link to developer docs code conventions (#11171)

---
 CONTRIBUTING.md | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
index ddd833be1..1f396bd71 100644
--- a/CONTRIBUTING.md
+++ b/CONTRIBUTING.md
@@ -271,7 +271,8 @@ except:  # noqa: E722
 
 ### Python conventions
 
-All Python code must be written **compatible with Python 3.6+**.
+All Python code must be written **compatible with Python 3.6+**. More detailed
+code conventions can be found in the [developer docs](https://github.com/explosion/spaCy/blob/master/extra/DEVELOPER_DOCS/Code%20Conventions.md).
 
 #### I/O and handling paths
 

From 5c2a00cef04b8c6e93e81cd1ca1d752f320c6e5d Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Tue, 26 Jul 2022 12:52:38 +0200
Subject: [PATCH 044/174] Set version to v3.4.1 (#11209)

---
 spacy/about.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/spacy/about.py b/spacy/about.py
index ef0358e1a..843c15aba 100644
--- a/spacy/about.py
+++ b/spacy/about.py
@@ -1,6 +1,6 @@
 # fmt: off
 __title__ = "spacy"
-__version__ = "3.4.0"
+__version__ = "3.4.1"
 __download_url__ = "https://github.com/explosion/spacy-models/releases/download"
 __compatibility__ = "https://raw.githubusercontent.com/explosion/spacy-models/master/compatibility.json"
 __projects__ = "https://github.com/explosion/projects"

From 360a702ecdf468bcdc7e14906d09cdfe1860e764 Mon Sep 17 00:00:00 2001
From: Edward <43848523+thomashacker@users.noreply.github.com>
Date: Tue, 26 Jul 2022 14:35:18 +0200
Subject: [PATCH 045/174] Add parent argument (#11210)

---
 spacy/cli/pretrain.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/spacy/cli/pretrain.py b/spacy/cli/pretrain.py
index fe3ce0dad..381d589cf 100644
--- a/spacy/cli/pretrain.py
+++ b/spacy/cli/pretrain.py
@@ -61,7 +61,7 @@ def pretrain_cli(
         # TODO: What's the solution here? How do we handle optional blocks?
         msg.fail("The [pretraining] block in your config is empty", exits=1)
     if not output_dir.exists():
-        output_dir.mkdir()
+        output_dir.mkdir(parents=True)
         msg.good(f"Created output directory: {output_dir}")
     # Save non-interpolated config
     raw_config.to_disk(output_dir / "config.cfg")

From 1829d7120a86c85f440d753a89e5e60d1faea1f0 Mon Sep 17 00:00:00 2001
From: Madeesh Kannan <shadeMe@users.noreply.github.com>
Date: Wed, 27 Jul 2022 07:24:22 +0200
Subject: [PATCH 046/174] `ExplosionBot`: Add note about case-sensitivity
 (#11211)

---
 extra/DEVELOPER_DOCS/ExplosionBot.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/extra/DEVELOPER_DOCS/ExplosionBot.md b/extra/DEVELOPER_DOCS/ExplosionBot.md
index 791b1f229..606fe93a0 100644
--- a/extra/DEVELOPER_DOCS/ExplosionBot.md
+++ b/extra/DEVELOPER_DOCS/ExplosionBot.md
@@ -36,7 +36,7 @@ Some things to note:
   @explosion-bot please test_gpu --run-on spacy-transformers --run-on-branch master --spacy-branch current_pr
   ```
 
-  This will launch the GPU pipeline for the `spacy-transformers` repo on its `master` branch, using the current spaCy PR's branch to build spaCy.
+  This will launch the GPU pipeline for the `spacy-transformers` repo on its `master` branch, using the current spaCy PR's branch to build spaCy. The name of the repository passed to `--run-on` is case-sensitive, e.g: use `spaCy` instead of `spacy`.
 
 - General info about supported commands.
 

From 95a1b8aca626f4a4825af7b7aed79489c4d451b4 Mon Sep 17 00:00:00 2001
From: ninjalu <46543912+ninjalu@users.noreply.github.com>
Date: Wed, 27 Jul 2022 12:16:44 +0100
Subject: [PATCH 047/174] add additional  REL_OP (#10371)

* add additional  REL_OP

* change to condition and new rel_op symbols

* add operators to docs

* add the anchor while we're in here

* add tests

Co-authored-by: Peter Baumgartner <5107405+pmbaumgartner@users.noreply.github.com>
---
 spacy/matcher/dependencymatcher.pyx           | 20 +++++++++++++++++++
 .../tests/matcher/test_dependency_matcher.py  | 14 +++++++++++++
 website/docs/api/dependencymatcher.md         |  7 ++++++-
 3 files changed, 40 insertions(+), 1 deletion(-)

diff --git a/spacy/matcher/dependencymatcher.pyx b/spacy/matcher/dependencymatcher.pyx
index a602ba737..74c2d002f 100644
--- a/spacy/matcher/dependencymatcher.pyx
+++ b/spacy/matcher/dependencymatcher.pyx
@@ -82,6 +82,10 @@ cdef class DependencyMatcher:
             "$-": self._imm_left_sib,
             "$++": self._right_sib,
             "$--": self._left_sib,
+            ">++": self._right_child,
+            ">--": self._left_child,
+            "<++": self._right_parent,
+            "<--": self._left_parent,
         }
 
     def __reduce__(self):
@@ -423,6 +427,22 @@ cdef class DependencyMatcher:
     def _left_sib(self, doc, node):
         return [doc[child.i] for child in doc[node].head.children if child.i < node]
 
+    def _right_child(self, doc, node):
+        return [doc[child.i] for child in doc[node].children if child.i > node]
+    
+    def _left_child(self, doc, node):
+        return [doc[child.i] for child in doc[node].children if child.i < node]
+
+    def _right_parent(self, doc, node):
+        if doc[node].head.i > node:
+            return [doc[node].head]
+        return []
+    
+    def _left_parent(self, doc, node):
+        if doc[node].head.i < node:
+            return [doc[node].head]
+        return []
+
     def _normalize_key(self, key):
         if isinstance(key, str):
             return self.vocab.strings.add(key)
diff --git a/spacy/tests/matcher/test_dependency_matcher.py b/spacy/tests/matcher/test_dependency_matcher.py
index 1728c82af..b4e19d69d 100644
--- a/spacy/tests/matcher/test_dependency_matcher.py
+++ b/spacy/tests/matcher/test_dependency_matcher.py
@@ -316,6 +316,20 @@ def test_dependency_matcher_precedence_ops(en_vocab, op, num_matches):
         ("the", "brown", "$--", 0),
         ("brown", "the", "$--", 1),
         ("brown", "brown", "$--", 0),
+        ("quick", "fox", "<++", 1),
+        ("quick", "over", "<++", 0),
+        ("over", "jumped", "<++", 0),
+        ("the", "fox", "<++", 2),
+        ("brown", "fox", "<--", 0),
+        ("fox", "jumped", "<--", 0),
+        ("fox", "over", "<--", 1),
+        ("jumped", "over", ">++", 1),
+        ("fox", "lazy", ">++", 0),
+        ("over", "the", ">++", 0),
+        ("brown", "fox", ">--", 0),
+        ("fox", "brown", ">--", 1),
+        ("jumped", "fox", ">--", 1),
+        ("fox", "the", ">--", 2),
     ],
 )
 def test_dependency_matcher_ops(en_vocab, doc, left, right, op, num_matches):
diff --git a/website/docs/api/dependencymatcher.md b/website/docs/api/dependencymatcher.md
index 356adcda7..cae4221bf 100644
--- a/website/docs/api/dependencymatcher.md
+++ b/website/docs/api/dependencymatcher.md
@@ -62,7 +62,7 @@ of relations, see the usage guide on
 
 </Infobox>
 
-### Operators
+### Operators {#operators}
 
 The following operators are supported by the `DependencyMatcher`, most of which
 come directly from
@@ -82,6 +82,11 @@ come directly from
 | `A $- B`  | `B` is a left immediate sibling of `A`, i.e. `A` and `B` have the same parent and `A.i == B.i + 1`.                  |
 | `A $++ B` | `B` is a right sibling of `A`, i.e. `A` and `B` have the same parent and `A.i < B.i`.                                |
 | `A $-- B` | `B` is a left sibling of `A`, i.e. `A` and `B` have the same parent and `A.i > B.i`.                                 |
+| `A >++ B` | `B` is a right child of `A`, i.e. `A` is a parent of `B` and `A.i < B.i` _(not in Semgrex)_.                         |
+| `A >-- B` | `B` is a left child of `A`, i.e. `A` is a parent of `B` and `A.i > B.i` _(not in Semgrex)_.                          |
+| `A <++ B` | `B` is a right parent of `A`, i.e. `A` is a child of `B` and `A.i < B.i` _(not in Semgrex)_.                         |
+| `A <-- B` | `B` is a left parent of `A`, i.e. `A` is a child of `B` and `A.i > B.i` _(not in Semgrex)_.                          |
+
 
 ## DependencyMatcher.\_\_init\_\_ {#init tag="method"}
 

From 2d89dd9db898e66058bf965e1b483b0019ce1b35 Mon Sep 17 00:00:00 2001
From: Paul O'Leary McCann <polm@dampfkraft.com>
Date: Thu, 28 Jul 2022 14:45:02 +0900
Subject: [PATCH 048/174] Update natto-py version spec (#11222)

* Update natto-py version spec

* Update setup.cfg

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
---
 setup.cfg | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/setup.cfg b/setup.cfg
index 61bf36f8a..708300b04 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -114,7 +114,7 @@ ja =
     sudachipy>=0.5.2,!=0.6.1
     sudachidict_core>=20211220
 ko =
-    natto-py==0.9.0
+    natto-py>=0.9.0
 th =
     pythainlp>=2.0
 

From d0578c2ede80890ed610573c95f11ad30b2f8cd2 Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Wed, 3 Aug 2022 16:41:20 +0200
Subject: [PATCH 049/174] Add scorer to textcat API docs config settings
 (#11263)

---
 website/docs/api/textcategorizer.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/website/docs/api/textcategorizer.md b/website/docs/api/textcategorizer.md
index 2ff569bad..5bc40fa9e 100644
--- a/website/docs/api/textcategorizer.md
+++ b/website/docs/api/textcategorizer.md
@@ -84,6 +84,7 @@ architectures and their arguments and hyperparameters.
 | ----------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------- |
 | `threshold` | Cutoff to consider a prediction "positive", relevant when printing accuracy results. ~~float~~                                                                   |
 | `model`     | A model instance that predicts scores for each category. Defaults to [TextCatEnsemble](/api/architectures#TextCatEnsemble). ~~Model[List[Doc], List[Floats2d]]~~ |
+| `scorer`    | The scoring method. Defaults to [`Scorer.score_cats`](/api/scorer#score_cats) for the attribute `"cats"`. ~~Optional[Callable]~~                                 |
 
 ```python
 %%GITHUB_SPACY/spacy/pipeline/textcat.py

From d993df41e5af01a2524fa436d27bc349ecb212b3 Mon Sep 17 00:00:00 2001
From: Lj Miranda <12949683+ljvmiranda921@users.noreply.github.com>
Date: Wed, 3 Aug 2022 22:53:02 +0800
Subject: [PATCH 050/174] Update docs for pipeline initialize() methods
 (#11221)

* Update documentation for dependency parser

* Update documentation for trainable_lemmatizer

* Update documentation for entity_linker

* Update documentation for ner

* Update documentation for morphologizer

* Update documentation for senter

* Update documentation for spancat

* Update documentation for tagger

* Update documentation for textcat

* Update documentation for tok2vec

* Run prettier on edited files

* Apply similar changes in transformer docs

* Remove need to say annotated example explicitly

I removed the need to say "Must contain at least one annotated Example"
because it's often a given that Examples will contain some gold-standard
annotation.

* Run prettier on transformer docs
---
 website/docs/api/dependencyparser.md   | 12 ++++++------
 website/docs/api/edittreelemmatizer.md | 12 ++++++------
 website/docs/api/entitylinker.md       | 22 +++++++++++-----------
 website/docs/api/entityrecognizer.md   | 12 ++++++------
 website/docs/api/morphologizer.md      | 12 ++++++------
 website/docs/api/sentencerecognizer.md | 20 ++++++++++----------
 website/docs/api/spancategorizer.md    | 16 ++++++++--------
 website/docs/api/tagger.md             | 12 ++++++------
 website/docs/api/textcategorizer.md    | 12 ++++++------
 website/docs/api/tok2vec.md            | 20 ++++++++++----------
 website/docs/api/transformer.md        | 20 ++++++++++----------
 11 files changed, 85 insertions(+), 85 deletions(-)

diff --git a/website/docs/api/dependencyparser.md b/website/docs/api/dependencyparser.md
index 103e0826e..27e315592 100644
--- a/website/docs/api/dependencyparser.md
+++ b/website/docs/api/dependencyparser.md
@@ -158,10 +158,10 @@ applied to the `Doc` in order. Both [`__call__`](/api/dependencyparser#call) and
 ## DependencyParser.initialize {#initialize tag="method" new="3"}
 
 Initialize the component for training. `get_examples` should be a function that
-returns an iterable of [`Example`](/api/example) objects. The data examples are
-used to **initialize the model** of the component and can either be the full
-training data or a representative sample. Initialization includes validating the
-network,
+returns an iterable of [`Example`](/api/example) objects. **At least one example
+should be supplied.** The data examples are used to **initialize the model** of
+the component and can either be the full training data or a representative
+sample. Initialization includes validating the network,
 [inferring missing shapes](https://thinc.ai/docs/usage-models#validation) and
 setting up the label scheme based on the data. This method is typically called
 by [`Language.initialize`](/api/language#initialize) and lets you customize
@@ -179,7 +179,7 @@ This method was previously called `begin_training`.
 >
 > ```python
 > parser = nlp.add_pipe("parser")
-> parser.initialize(lambda: [], nlp=nlp)
+> parser.initialize(lambda: examples, nlp=nlp)
 > ```
 >
 > ```ini
@@ -193,7 +193,7 @@ This method was previously called `begin_training`.
 
 | Name           | Description                                                                                                                                                                                                                                                                                                                                                                                                            |
 | -------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `get_examples` | Function that returns gold-standard annotations in the form of [`Example`](/api/example) objects. ~~Callable[[], Iterable[Example]]~~                                                                                                                                                                                                                                                                                  |
+| `get_examples` | Function that returns gold-standard annotations in the form of [`Example`](/api/example) objects. Must contain at least one `Example`. ~~Callable[[], Iterable[Example]]~~                                                                                                                                                                                                                                             |
 | _keyword-only_ |                                                                                                                                                                                                                                                                                                                                                                                                                        |
 | `nlp`          | The current `nlp` object. Defaults to `None`. ~~Optional[Language]~~                                                                                                                                                                                                                                                                                                                                                   |
 | `labels`       | The label information to add to the component, as provided by the [`label_data`](#label_data) property after initialization. To generate a reusable JSON file from your data, you should run the [`init labels`](/api/cli#init-labels) command. If no labels are provided, the `get_examples` callback is used to extract the labels from the data, which may be a lot slower. ~~Optional[Dict[str, Dict[str, int]]]~~ |
diff --git a/website/docs/api/edittreelemmatizer.md b/website/docs/api/edittreelemmatizer.md
index 99a705f5e..63e4bf910 100644
--- a/website/docs/api/edittreelemmatizer.md
+++ b/website/docs/api/edittreelemmatizer.md
@@ -141,10 +141,10 @@ and [`pipe`](/api/edittreelemmatizer#pipe) delegate to the
 ## EditTreeLemmatizer.initialize {#initialize tag="method" new="3"}
 
 Initialize the component for training. `get_examples` should be a function that
-returns an iterable of [`Example`](/api/example) objects. The data examples are
-used to **initialize the model** of the component and can either be the full
-training data or a representative sample. Initialization includes validating the
-network,
+returns an iterable of [`Example`](/api/example) objects. **At least one example
+should be supplied.** The data examples are used to **initialize the model** of
+the component and can either be the full training data or a representative
+sample. Initialization includes validating the network,
 [inferring missing shapes](https://thinc.ai/docs/usage-models#validation) and
 setting up the label scheme based on the data. This method is typically called
 by [`Language.initialize`](/api/language#initialize) and lets you customize
@@ -156,7 +156,7 @@ config.
 >
 > ```python
 > lemmatizer = nlp.add_pipe("trainable_lemmatizer", name="lemmatizer")
-> lemmatizer.initialize(lambda: [], nlp=nlp)
+> lemmatizer.initialize(lambda: examples, nlp=nlp)
 > ```
 >
 > ```ini
@@ -170,7 +170,7 @@ config.
 
 | Name           | Description                                                                                                                                                                                                                                                                                                                                                                                                |
 | -------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `get_examples` | Function that returns gold-standard annotations in the form of [`Example`](/api/example) objects. ~~Callable[[], Iterable[Example]]~~                                                                                                                                                                                                                                                                      |
+| `get_examples` | Function that returns gold-standard annotations in the form of [`Example`](/api/example) objects. Must contain at least one `Example`. ~~Callable[[], Iterable[Example]]~~                                                                                                                                                                                                                                 |
 | _keyword-only_ |                                                                                                                                                                                                                                                                                                                                                                                                            |
 | `nlp`          | The current `nlp` object. Defaults to `None`. ~~Optional[Language]~~                                                                                                                                                                                                                                                                                                                                       |
 | `labels`       | The label information to add to the component, as provided by the [`label_data`](#label_data) property after initialization. To generate a reusable JSON file from your data, you should run the [`init labels`](/api/cli#init-labels) command. If no labels are provided, the `get_examples` callback is used to extract the labels from the data, which may be a lot slower. ~~Optional[Iterable[str]]~~ |
diff --git a/website/docs/api/entitylinker.md b/website/docs/api/entitylinker.md
index a55cce352..43e08a39c 100644
--- a/website/docs/api/entitylinker.md
+++ b/website/docs/api/entitylinker.md
@@ -185,10 +185,10 @@ with the current vocab.
 ## EntityLinker.initialize {#initialize tag="method" new="3"}
 
 Initialize the component for training. `get_examples` should be a function that
-returns an iterable of [`Example`](/api/example) objects. The data examples are
-used to **initialize the model** of the component and can either be the full
-training data or a representative sample. Initialization includes validating the
-network,
+returns an iterable of [`Example`](/api/example) objects. **At least one example
+should be supplied.** The data examples are used to **initialize the model** of
+the component and can either be the full training data or a representative
+sample. Initialization includes validating the network,
 [inferring missing shapes](https://thinc.ai/docs/usage-models#validation) and
 setting up the label scheme based on the data. This method is typically called
 by [`Language.initialize`](/api/language#initialize).
@@ -208,15 +208,15 @@ This method was previously called `begin_training`.
 >
 > ```python
 > entity_linker = nlp.add_pipe("entity_linker")
-> entity_linker.initialize(lambda: [], nlp=nlp, kb_loader=my_kb)
+> entity_linker.initialize(lambda: examples, nlp=nlp, kb_loader=my_kb)
 > ```
 
-| Name           | Description                                                                                                                           |
-| -------------- | ------------------------------------------------------------------------------------------------------------------------------------- |
-| `get_examples` | Function that returns gold-standard annotations in the form of [`Example`](/api/example) objects. ~~Callable[[], Iterable[Example]]~~ |
-| _keyword-only_ |                                                                                                                                       |
-| `nlp`          | The current `nlp` object. Defaults to `None`. ~~Optional[Language]~~                                                                  |
-| `kb_loader`    | Function that creates a [`KnowledgeBase`](/api/kb) from a `Vocab` instance. ~~Callable[[Vocab], KnowledgeBase]~~                      |
+| Name           | Description                                                                                                                                                                |
+| -------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `get_examples` | Function that returns gold-standard annotations in the form of [`Example`](/api/example) objects. Must contain at least one `Example`. ~~Callable[[], Iterable[Example]]~~ |
+| _keyword-only_ |                                                                                                                                                                            |
+| `nlp`          | The current `nlp` object. Defaults to `None`. ~~Optional[Language]~~                                                                                                       |
+| `kb_loader`    | Function that creates a [`KnowledgeBase`](/api/kb) from a `Vocab` instance. ~~Callable[[Vocab], KnowledgeBase]~~                                                           |
 
 ## EntityLinker.predict {#predict tag="method"}
 
diff --git a/website/docs/api/entityrecognizer.md b/website/docs/api/entityrecognizer.md
index 7c153f064..a535e8316 100644
--- a/website/docs/api/entityrecognizer.md
+++ b/website/docs/api/entityrecognizer.md
@@ -154,10 +154,10 @@ applied to the `Doc` in order. Both [`__call__`](/api/entityrecognizer#call) and
 ## EntityRecognizer.initialize {#initialize tag="method" new="3"}
 
 Initialize the component for training. `get_examples` should be a function that
-returns an iterable of [`Example`](/api/example) objects. The data examples are
-used to **initialize the model** of the component and can either be the full
-training data or a representative sample. Initialization includes validating the
-network,
+returns an iterable of [`Example`](/api/example) objects. **At least one example
+should be supplied.** The data examples are used to **initialize the model** of
+the component and can either be the full training data or a representative
+sample. Initialization includes validating the network,
 [inferring missing shapes](https://thinc.ai/docs/usage-models#validation) and
 setting up the label scheme based on the data. This method is typically called
 by [`Language.initialize`](/api/language#initialize) and lets you customize
@@ -175,7 +175,7 @@ This method was previously called `begin_training`.
 >
 > ```python
 > ner = nlp.add_pipe("ner")
-> ner.initialize(lambda: [], nlp=nlp)
+> ner.initialize(lambda: examples, nlp=nlp)
 > ```
 >
 > ```ini
@@ -189,7 +189,7 @@ This method was previously called `begin_training`.
 
 | Name           | Description                                                                                                                                                                                                                                                                                                                                                                                                            |
 | -------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `get_examples` | Function that returns gold-standard annotations in the form of [`Example`](/api/example) objects. ~~Callable[[], Iterable[Example]]~~                                                                                                                                                                                                                                                                                  |
+| `get_examples` | Function that returns gold-standard annotations in the form of [`Example`](/api/example) objects. Must contain at least one `Example`. ~~Callable[[], Iterable[Example]]~~                                                                                                                                                                                                                                             |
 | _keyword-only_ |                                                                                                                                                                                                                                                                                                                                                                                                                        |
 | `nlp`          | The current `nlp` object. Defaults to `None`. ~~Optional[Language]~~                                                                                                                                                                                                                                                                                                                                                   |
 | `labels`       | The label information to add to the component, as provided by the [`label_data`](#label_data) property after initialization. To generate a reusable JSON file from your data, you should run the [`init labels`](/api/cli#init-labels) command. If no labels are provided, the `get_examples` callback is used to extract the labels from the data, which may be a lot slower. ~~Optional[Dict[str, Dict[str, int]]]~~ |
diff --git a/website/docs/api/morphologizer.md b/website/docs/api/morphologizer.md
index 434c56833..f874e8bea 100644
--- a/website/docs/api/morphologizer.md
+++ b/website/docs/api/morphologizer.md
@@ -147,10 +147,10 @@ applied to the `Doc` in order. Both [`__call__`](/api/morphologizer#call) and
 ## Morphologizer.initialize {#initialize tag="method"}
 
 Initialize the component for training. `get_examples` should be a function that
-returns an iterable of [`Example`](/api/example) objects. The data examples are
-used to **initialize the model** of the component and can either be the full
-training data or a representative sample. Initialization includes validating the
-network,
+returns an iterable of [`Example`](/api/example) objects. **At least one example
+should be supplied.** The data examples are used to **initialize the model** of
+the component and can either be the full training data or a representative
+sample. Initialization includes validating the network,
 [inferring missing shapes](https://thinc.ai/docs/usage-models#validation) and
 setting up the label scheme based on the data. This method is typically called
 by [`Language.initialize`](/api/language#initialize) and lets you customize
@@ -162,7 +162,7 @@ config.
 >
 > ```python
 > morphologizer = nlp.add_pipe("morphologizer")
-> morphologizer.initialize(lambda: [], nlp=nlp)
+> morphologizer.initialize(lambda: examples, nlp=nlp)
 > ```
 >
 > ```ini
@@ -176,7 +176,7 @@ config.
 
 | Name           | Description                                                                                                                                                                                                                                                                                                                                                                                       |
 | -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `get_examples` | Function that returns gold-standard annotations in the form of [`Example`](/api/example) objects. ~~Callable[[], Iterable[Example]]~~                                                                                                                                                                                                                                                             |
+| `get_examples` | Function that returns gold-standard annotations in the form of [`Example`](/api/example) objects. Must contain at least one `Example`. ~~Callable[[], Iterable[Example]]~~                                                                                                                                                                                                                        |
 | _keyword-only_ |                                                                                                                                                                                                                                                                                                                                                                                                   |
 | `nlp`          | The current `nlp` object. Defaults to `None`. ~~Optional[Language]~~                                                                                                                                                                                                                                                                                                                              |
 | `labels`       | The label information to add to the component, as provided by the [`label_data`](#label_data) property after initialization. To generate a reusable JSON file from your data, you should run the [`init labels`](/api/cli#init-labels) command. If no labels are provided, the `get_examples` callback is used to extract the labels from the data, which may be a lot slower. ~~Optional[dict]~~ |
diff --git a/website/docs/api/sentencerecognizer.md b/website/docs/api/sentencerecognizer.md
index 29bf10393..2f50350ae 100644
--- a/website/docs/api/sentencerecognizer.md
+++ b/website/docs/api/sentencerecognizer.md
@@ -132,10 +132,10 @@ and [`pipe`](/api/sentencerecognizer#pipe) delegate to the
 ## SentenceRecognizer.initialize {#initialize tag="method"}
 
 Initialize the component for training. `get_examples` should be a function that
-returns an iterable of [`Example`](/api/example) objects. The data examples are
-used to **initialize the model** of the component and can either be the full
-training data or a representative sample. Initialization includes validating the
-network,
+returns an iterable of [`Example`](/api/example) objects. **At least one example
+should be supplied.** The data examples are used to **initialize the model** of
+the component and can either be the full training data or a representative
+sample. Initialization includes validating the network,
 [inferring missing shapes](https://thinc.ai/docs/usage-models#validation) and
 setting up the label scheme based on the data. This method is typically called
 by [`Language.initialize`](/api/language#initialize).
@@ -144,14 +144,14 @@ by [`Language.initialize`](/api/language#initialize).
 >
 > ```python
 > senter = nlp.add_pipe("senter")
-> senter.initialize(lambda: [], nlp=nlp)
+> senter.initialize(lambda: examples, nlp=nlp)
 > ```
 
-| Name           | Description                                                                                                                           |
-| -------------- | ------------------------------------------------------------------------------------------------------------------------------------- |
-| `get_examples` | Function that returns gold-standard annotations in the form of [`Example`](/api/example) objects. ~~Callable[[], Iterable[Example]]~~ |
-| _keyword-only_ |                                                                                                                                       |
-| `nlp`          | The current `nlp` object. Defaults to `None`. ~~Optional[Language]~~                                                                  |
+| Name           | Description                                                                                                                                                                |
+| -------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `get_examples` | Function that returns gold-standard annotations in the form of [`Example`](/api/example) objects. Must contain at least one `Example`. ~~Callable[[], Iterable[Example]]~~ |
+| _keyword-only_ |                                                                                                                                                                            |
+| `nlp`          | The current `nlp` object. Defaults to `None`. ~~Optional[Language]~~                                                                                                       |
 
 ## SentenceRecognizer.predict {#predict tag="method"}
 
diff --git a/website/docs/api/spancategorizer.md b/website/docs/api/spancategorizer.md
index f09ac8bdb..58a06bcf5 100644
--- a/website/docs/api/spancategorizer.md
+++ b/website/docs/api/spancategorizer.md
@@ -56,7 +56,7 @@ architectures and their arguments and hyperparameters.
 | -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
 | `suggester`    | A function that [suggests spans](#suggesters). Spans are returned as a ragged array with two integer columns, for the start and end positions. Defaults to [`ngram_suggester`](#ngram_suggester). ~~Callable[[Iterable[Doc], Optional[Ops]], Ragged]~~                                                  |
 | `model`        | A model instance that is given a a list of documents and `(start, end)` indices representing candidate span offsets. The model predicts a probability for each category for each span. Defaults to [SpanCategorizer](/api/architectures#SpanCategorizer). ~~Model[Tuple[List[Doc], Ragged], Floats2d]~~ |
-| `spans_key`    | Key of the [`Doc.spans`](/api/doc#spans) dict to save the spans under. During initialization and training, the component will look for spans on the reference document under the same key. Defaults to `"sc"`. ~~str~~                                                                               |
+| `spans_key`    | Key of the [`Doc.spans`](/api/doc#spans) dict to save the spans under. During initialization and training, the component will look for spans on the reference document under the same key. Defaults to `"sc"`. ~~str~~                                                                                  |
 | `threshold`    | Minimum probability to consider a prediction positive. Spans with a positive prediction will be saved on the Doc. Defaults to `0.5`. ~~float~~                                                                                                                                                          |
 | `max_positive` | Maximum number of labels to consider positive per span. Defaults to `None`, indicating no limit. ~~Optional[int]~~                                                                                                                                                                                      |
 | `scorer`       | The scoring method. Defaults to [`Scorer.score_spans`](/api/scorer#score_spans) for `Doc.spans[spans_key]` with overlapping spans allowed. ~~Optional[Callable]~~                                                                                                                                       |
@@ -93,7 +93,7 @@ shortcut for this and instantiate the component using its string name and
 | `suggester`    | A function that [suggests spans](#suggesters). Spans are returned as a ragged array with two integer columns, for the start and end positions. ~~Callable[[Iterable[Doc], Optional[Ops]], Ragged]~~                                  |
 | `name`         | String name of the component instance. Used to add entries to the `losses` during training. ~~str~~                                                                                                                                  |
 | _keyword-only_ |                                                                                                                                                                                                                                      |
-| `spans_key`    | Key of the [`Doc.spans`](/api/doc#sans) dict to save the spans under. During initialization and training, the component will look for spans on the reference document under the same key. Defaults to `"sc"`. ~~str~~             |
+| `spans_key`    | Key of the [`Doc.spans`](/api/doc#sans) dict to save the spans under. During initialization and training, the component will look for spans on the reference document under the same key. Defaults to `"sc"`. ~~str~~                |
 | `threshold`    | Minimum probability to consider a prediction positive. Spans with a positive prediction will be saved on the Doc. Defaults to `0.5`. ~~float~~                                                                                       |
 | `max_positive` | Maximum number of labels to consider positive per span. Defaults to `None`, indicating no limit. ~~Optional[int]~~                                                                                                                   |
 
@@ -147,10 +147,10 @@ applied to the `Doc` in order. Both [`__call__`](/api/spancategorizer#call) and
 ## SpanCategorizer.initialize {#initialize tag="method"}
 
 Initialize the component for training. `get_examples` should be a function that
-returns an iterable of [`Example`](/api/example) objects. The data examples are
-used to **initialize the model** of the component and can either be the full
-training data or a representative sample. Initialization includes validating the
-network,
+returns an iterable of [`Example`](/api/example) objects. **At least one example
+should be supplied.** The data examples are used to **initialize the model** of
+the component and can either be the full training data or a representative
+sample. Initialization includes validating the network,
 [inferring missing shapes](https://thinc.ai/docs/usage-models#validation) and
 setting up the label scheme based on the data. This method is typically called
 by [`Language.initialize`](/api/language#initialize) and lets you customize
@@ -162,7 +162,7 @@ config.
 >
 > ```python
 > spancat = nlp.add_pipe("spancat")
-> spancat.initialize(lambda: [], nlp=nlp)
+> spancat.initialize(lambda: examples, nlp=nlp)
 > ```
 >
 > ```ini
@@ -176,7 +176,7 @@ config.
 
 | Name           | Description                                                                                                                                                                                                                                                                                                                                                                                                |
 | -------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `get_examples` | Function that returns gold-standard annotations in the form of [`Example`](/api/example) objects. ~~Callable[[], Iterable[Example]]~~                                                                                                                                                                                                                                                                      |
+| `get_examples` | Function that returns gold-standard annotations in the form of [`Example`](/api/example) objects. Must contain at least one `Example`. ~~Callable[[], Iterable[Example]]~~                                                                                                                                                                                                                                 |
 | _keyword-only_ |                                                                                                                                                                                                                                                                                                                                                                                                            |
 | `nlp`          | The current `nlp` object. Defaults to `None`. ~~Optional[Language]~~                                                                                                                                                                                                                                                                                                                                       |
 | `labels`       | The label information to add to the component, as provided by the [`label_data`](#label_data) property after initialization. To generate a reusable JSON file from your data, you should run the [`init labels`](/api/cli#init-labels) command. If no labels are provided, the `get_examples` callback is used to extract the labels from the data, which may be a lot slower. ~~Optional[Iterable[str]]~~ |
diff --git a/website/docs/api/tagger.md b/website/docs/api/tagger.md
index b51864d3a..90a49b197 100644
--- a/website/docs/api/tagger.md
+++ b/website/docs/api/tagger.md
@@ -130,10 +130,10 @@ applied to the `Doc` in order. Both [`__call__`](/api/tagger#call) and
 ## Tagger.initialize {#initialize tag="method" new="3"}
 
 Initialize the component for training. `get_examples` should be a function that
-returns an iterable of [`Example`](/api/example) objects. The data examples are
-used to **initialize the model** of the component and can either be the full
-training data or a representative sample. Initialization includes validating the
-network,
+returns an iterable of [`Example`](/api/example) objects. **At least one example
+should be supplied.** The data examples are used to **initialize the model** of
+the component and can either be the full training data or a representative
+sample. Initialization includes validating the network,
 [inferring missing shapes](https://thinc.ai/docs/usage-models#validation) and
 setting up the label scheme based on the data. This method is typically called
 by [`Language.initialize`](/api/language#initialize) and lets you customize
@@ -151,7 +151,7 @@ This method was previously called `begin_training`.
 >
 > ```python
 > tagger = nlp.add_pipe("tagger")
-> tagger.initialize(lambda: [], nlp=nlp)
+> tagger.initialize(lambda: examples, nlp=nlp)
 > ```
 >
 > ```ini
@@ -165,7 +165,7 @@ This method was previously called `begin_training`.
 
 | Name           | Description                                                                                                                                                                                                                                                                                                                                                                                                |
 | -------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `get_examples` | Function that returns gold-standard annotations in the form of [`Example`](/api/example) objects. ~~Callable[[], Iterable[Example]]~~                                                                                                                                                                                                                                                                      |
+| `get_examples` | Function that returns gold-standard annotations in the form of [`Example`](/api/example) objects. Must contain at least one `Example`. ~~Callable[[], Iterable[Example]]~~                                                                                                                                                                                                                                 |
 | _keyword-only_ |                                                                                                                                                                                                                                                                                                                                                                                                            |
 | `nlp`          | The current `nlp` object. Defaults to `None`. ~~Optional[Language]~~                                                                                                                                                                                                                                                                                                                                       |
 | `labels`       | The label information to add to the component, as provided by the [`label_data`](#label_data) property after initialization. To generate a reusable JSON file from your data, you should run the [`init labels`](/api/cli#init-labels) command. If no labels are provided, the `get_examples` callback is used to extract the labels from the data, which may be a lot slower. ~~Optional[Iterable[str]]~~ |
diff --git a/website/docs/api/textcategorizer.md b/website/docs/api/textcategorizer.md
index 5bc40fa9e..042b4ab76 100644
--- a/website/docs/api/textcategorizer.md
+++ b/website/docs/api/textcategorizer.md
@@ -176,10 +176,10 @@ applied to the `Doc` in order. Both [`__call__`](/api/textcategorizer#call) and
 ## TextCategorizer.initialize {#initialize tag="method" new="3"}
 
 Initialize the component for training. `get_examples` should be a function that
-returns an iterable of [`Example`](/api/example) objects. The data examples are
-used to **initialize the model** of the component and can either be the full
-training data or a representative sample. Initialization includes validating the
-network,
+returns an iterable of [`Example`](/api/example) objects. **At least one example
+should be supplied.** The data examples are used to **initialize the model** of
+the component and can either be the full training data or a representative
+sample. Initialization includes validating the network,
 [inferring missing shapes](https://thinc.ai/docs/usage-models#validation) and
 setting up the label scheme based on the data. This method is typically called
 by [`Language.initialize`](/api/language#initialize) and lets you customize
@@ -197,7 +197,7 @@ This method was previously called `begin_training`.
 >
 > ```python
 > textcat = nlp.add_pipe("textcat")
-> textcat.initialize(lambda: [], nlp=nlp)
+> textcat.initialize(lambda: examples, nlp=nlp)
 > ```
 >
 > ```ini
@@ -212,7 +212,7 @@ This method was previously called `begin_training`.
 
 | Name             | Description                                                                                                                                                                                                                                                                                                                                                                                                |
 | ---------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `get_examples`   | Function that returns gold-standard annotations in the form of [`Example`](/api/example) objects. ~~Callable[[], Iterable[Example]]~~                                                                                                                                                                                                                                                                      |
+| `get_examples`   | Function that returns gold-standard annotations in the form of [`Example`](/api/example) objects. Must contain at least one `Example`. ~~Callable[[], Iterable[Example]]~~                                                                                                                                                                                                                                 |
 | _keyword-only_   |                                                                                                                                                                                                                                                                                                                                                                                                            |
 | `nlp`            | The current `nlp` object. Defaults to `None`. ~~Optional[Language]~~                                                                                                                                                                                                                                                                                                                                       |
 | `labels`         | The label information to add to the component, as provided by the [`label_data`](#label_data) property after initialization. To generate a reusable JSON file from your data, you should run the [`init labels`](/api/cli#init-labels) command. If no labels are provided, the `get_examples` callback is used to extract the labels from the data, which may be a lot slower. ~~Optional[Iterable[str]]~~ |
diff --git a/website/docs/api/tok2vec.md b/website/docs/api/tok2vec.md
index 70c352b4d..2dcb1a013 100644
--- a/website/docs/api/tok2vec.md
+++ b/website/docs/api/tok2vec.md
@@ -127,10 +127,10 @@ and [`set_annotations`](/api/tok2vec#set_annotations) methods.
 
 Initialize the component for training and return an
 [`Optimizer`](https://thinc.ai/docs/api-optimizers). `get_examples` should be a
-function that returns an iterable of [`Example`](/api/example) objects. The data
-examples are used to **initialize the model** of the component and can either be
-the full training data or a representative sample. Initialization includes
-validating the network,
+function that returns an iterable of [`Example`](/api/example) objects. **At
+least one example should be supplied.** The data examples are used to
+**initialize the model** of the component and can either be the full training
+data or a representative sample. Initialization includes validating the network,
 [inferring missing shapes](https://thinc.ai/docs/usage-models#validation) and
 setting up the label scheme based on the data. This method is typically called
 by [`Language.initialize`](/api/language#initialize).
@@ -139,14 +139,14 @@ by [`Language.initialize`](/api/language#initialize).
 >
 > ```python
 > tok2vec = nlp.add_pipe("tok2vec")
-> tok2vec.initialize(lambda: [], nlp=nlp)
+> tok2vec.initialize(lambda: examples, nlp=nlp)
 > ```
 
-| Name           | Description                                                                                                                           |
-| -------------- | ------------------------------------------------------------------------------------------------------------------------------------- |
-| `get_examples` | Function that returns gold-standard annotations in the form of [`Example`](/api/example) objects. ~~Callable[[], Iterable[Example]]~~ |
-| _keyword-only_ |                                                                                                                                       |
-| `nlp`          | The current `nlp` object. Defaults to `None`. ~~Optional[Language]~~                                                                  |
+| Name           | Description                                                                                                                                                                |
+| -------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `get_examples` | Function that returns gold-standard annotations in the form of [`Example`](/api/example) objects. Must contain at least one `Example`. ~~Callable[[], Iterable[Example]]~~ |
+| _keyword-only_ |                                                                                                                                                                            |
+| `nlp`          | The current `nlp` object. Defaults to `None`. ~~Optional[Language]~~                                                                                                       |
 
 ## Tok2Vec.predict {#predict tag="method"}
 
diff --git a/website/docs/api/transformer.md b/website/docs/api/transformer.md
index b1673cdbe..e747ad383 100644
--- a/website/docs/api/transformer.md
+++ b/website/docs/api/transformer.md
@@ -175,10 +175,10 @@ applied to the `Doc` in order. Both [`__call__`](/api/transformer#call) and
 
 Initialize the component for training and return an
 [`Optimizer`](https://thinc.ai/docs/api-optimizers). `get_examples` should be a
-function that returns an iterable of [`Example`](/api/example) objects. The data
-examples are used to **initialize the model** of the component and can either be
-the full training data or a representative sample. Initialization includes
-validating the network,
+function that returns an iterable of [`Example`](/api/example) objects. **At
+least one example should be supplied.** The data examples are used to
+**initialize the model** of the component and can either be the full training
+data or a representative sample. Initialization includes validating the network,
 [inferring missing shapes](https://thinc.ai/docs/usage-models#validation) and
 setting up the label scheme based on the data. This method is typically called
 by [`Language.initialize`](/api/language#initialize).
@@ -187,14 +187,14 @@ by [`Language.initialize`](/api/language#initialize).
 >
 > ```python
 > trf = nlp.add_pipe("transformer")
-> trf.initialize(lambda: iter([]), nlp=nlp)
+> trf.initialize(lambda: examples, nlp=nlp)
 > ```
 
-| Name           | Description                                                                                                                           |
-| -------------- | ------------------------------------------------------------------------------------------------------------------------------------- |
-| `get_examples` | Function that returns gold-standard annotations in the form of [`Example`](/api/example) objects. ~~Callable[[], Iterable[Example]]~~ |
-| _keyword-only_ |                                                                                                                                       |
-| `nlp`          | The current `nlp` object. Defaults to `None`. ~~Optional[Language]~~                                                                  |
+| Name           | Description                                                                                                                                                                |
+| -------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `get_examples` | Function that returns gold-standard annotations in the form of [`Example`](/api/example) objects. Must contain at least one `Example`. ~~Callable[[], Iterable[Example]]~~ |
+| _keyword-only_ |                                                                                                                                                                            |
+| `nlp`          | The current `nlp` object. Defaults to `None`. ~~Optional[Language]~~                                                                                                       |
 
 ## Transformer.predict {#predict tag="method"}
 

From cd09614ab2be485a796a572274d336c1c47ca4a9 Mon Sep 17 00:00:00 2001
From: Jules Belveze <32683010+JulesBelveze@users.noreply.github.com>
Date: Thu, 4 Aug 2022 08:42:38 +0200
Subject: [PATCH 051/174] chore: add 'concepCy' to spacy universe (#11255)

* chore: add 'concepCy' to spacy universe

* docs: add 'slogan' to concepCy
---
 website/meta/universe.json | 42 ++++++++++++++++++++++++++++++++++----
 1 file changed, 38 insertions(+), 4 deletions(-)

diff --git a/website/meta/universe.json b/website/meta/universe.json
index a128f0795..6c8caa6a6 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -1,5 +1,39 @@
 {
     "resources": [
+        {
+            "id": "concepcy",
+            "title": "concepCy",
+            "slogan": "A multilingual knowledge graph in spaCy",
+            "description": "A spaCy wrapper for ConceptNet, a freely-available semantic network designed to help computers understand the meaning of words.",
+            "github": "JulesBelveze/concepcy",
+            "pip": "concepcy",
+            "code_example": [
+                "import spacy",
+                "import concepcy",
+                "",
+                "nlp = spacy.load('en_core_web_sm')",
+                "# Using default concepCy configuration",
+                "nlp.add_pipe('concepcy')",
+                "",
+                "doc = nlp('WHO is a lovely company')",
+                "",
+                "# Access all the 'RelatedTo' relations from the Doc",
+                "for word, relations in doc._.relatedto.items():",
+                "    print(f'Word: {word}\n{relations}')",
+                "",
+                "# Access the 'RelatedTo' relations word by word",
+                "for token in doc:",
+                "    print(f'Word: {token}\n{token._.relatedto}')"
+            ],
+            "category": ["pipeline"],
+            "image": "https://github.com/JulesBelveze/concepcy/blob/main/figures/concepcy.png",
+            "tags": ["semantic", "ConceptNet"],
+            "author": "Jules Belveze",
+            "author_links": {
+                "github": "JulesBelveze",
+                "website": "https://www.linkedin.com/in/jules-belveze/"
+            }
+        },
         {
             "id": "spacyfishing",
             "title": "spaCy fishing",
@@ -2604,7 +2638,7 @@
                 "    Add the courgette, garlic, red peppers and oregano and cook for 2–3 minutes.",
                 "    Later, add some oranges and chickens.\"\"\"",
                 "",
-                "# use any model that has internal spacy embeddings", 
+                "# use any model that has internal spacy embeddings",
                 "nlp = spacy.load('en_core_web_lg')",
                 "nlp.add_pipe(\"concise_concepts\", ",
                 "    config={\"data\": data}",
@@ -2650,7 +2684,7 @@
                 "    At that location, Nissin was founded.",
                 "    Many students survived by eating these noodles, but they don't even know him.\"\"\"",
                 "",
-                "# use any model that has internal spacy embeddings", 
+                "# use any model that has internal spacy embeddings",
                 "nlp = spacy.load('en_core_web_sm')",
                 "nlp.add_pipe(",
                 "    \"xx_coref\", config={\"chunk_size\": 2500, \"chunk_overlap\": 2, \"device\": 0})",
@@ -2833,7 +2867,7 @@
                 "doc = nlp(\"AE died in Princeton in 1955.\")",
                 "",
                 "print(doc._.clauses)",
-                "# Output:",       
+                "# Output:",
                 "# <SV, AE, died, None, None, None, [in Princeton, in 1955]>",
                 "",
                 "propositions = doc._.clauses[0].to_propositions(as_text=True)",
@@ -3599,7 +3633,7 @@
                 "",
                 "#Lexico Semantic (LxSem) Features",
                 "TTRF = LingFeat.TTRF_() #Type Token Ratio Features",
-                "VarF = LingFeat.VarF_() #Noun/Verb/Adj/Adv Variation Features", 
+                "VarF = LingFeat.VarF_() #Noun/Verb/Adj/Adv Variation Features",
                 "PsyF = LingFeat.PsyF_() #Psycholinguistic Difficulty of Words (AoA Kuperman)",
                 "WoLF = LingFeat.WorF_() #Word Familiarity from Frequency Count (SubtlexUS)",
                 "",

From b07708d5d073bf1af55d0b50eb11760e48221500 Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Thu, 4 Aug 2022 15:14:19 +0200
Subject: [PATCH 052/174] Support full prerelease versions in the compat table
 (#11228)

* Support full prerelease versions in the compat table

* Fix types
---
 spacy/cli/download.py | 6 +++++-
 spacy/util.py         | 9 +++++++++
 2 files changed, 14 insertions(+), 1 deletion(-)

diff --git a/spacy/cli/download.py b/spacy/cli/download.py
index 4ea9a8f0e..b7de88729 100644
--- a/spacy/cli/download.py
+++ b/spacy/cli/download.py
@@ -7,6 +7,7 @@ import typer
 from ._util import app, Arg, Opt, WHEEL_SUFFIX, SDIST_SUFFIX
 from .. import about
 from ..util import is_package, get_minor_version, run_command
+from ..util import is_prerelease_version
 from ..errors import OLD_MODEL_SHORTCUTS
 
 
@@ -74,7 +75,10 @@ def download(model: str, direct: bool = False, sdist: bool = False, *pip_args) -
 
 
 def get_compatibility() -> dict:
-    version = get_minor_version(about.__version__)
+    if is_prerelease_version(about.__version__):
+        version: Optional[str] = about.__version__
+    else:
+        version = get_minor_version(about.__version__)
     r = requests.get(about.__compatibility__)
     if r.status_code != 200:
         msg.fail(
diff --git a/spacy/util.py b/spacy/util.py
index 4f21d618a..d170fc15b 100644
--- a/spacy/util.py
+++ b/spacy/util.py
@@ -795,6 +795,15 @@ def get_model_lower_version(constraint: str) -> Optional[str]:
     return None
 
 
+def is_prerelease_version(version: str) -> bool:
+    """Check whether a version is a prerelease version.
+
+    version (str): The version, e.g. "3.0.0.dev1".
+    RETURNS (bool): Whether the version is a prerelease version.
+    """
+    return Version(version).is_prerelease
+
+
 def get_base_version(version: str) -> str:
     """Generate the base version without any prerelease identifiers.
 

From b64243ed557a1cc591a2f436449072b27f432de7 Mon Sep 17 00:00:00 2001
From: Luka Dragar <lukc.orglce@gmail.com>
Date: Fri, 5 Aug 2022 10:10:18 +0200
Subject: [PATCH 053/174] Updates to Slovenian language (#11162)

* Added examples for Slovene

* Update spacy/lang/sl/examples.py

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

* Corrected a typo in one of the sentences

* Updated support for Slovenian

* Some minor changes to corrections

* Added forint currency

* Corrected HYPHENS_PERMITTED regex and some formatting

* Minor changes

* Un-xfail tokenizer test

* Format

Co-authored-by: Luka Dragar <D20124481@mytudublin.ie>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
---
 spacy/lang/sl/__init__.py             |   8 +
 spacy/lang/sl/lex_attrs.py            | 145 ++++++++++
 spacy/lang/sl/punctuation.py          |  84 ++++++
 spacy/lang/sl/stop_words.py           | 394 +++++---------------------
 spacy/lang/sl/tokenizer_exceptions.py | 272 ++++++++++++++++++
 spacy/tests/lang/sl/test_text.py      |   1 -
 6 files changed, 585 insertions(+), 319 deletions(-)
 create mode 100644 spacy/lang/sl/lex_attrs.py
 create mode 100644 spacy/lang/sl/punctuation.py
 create mode 100644 spacy/lang/sl/tokenizer_exceptions.py

diff --git a/spacy/lang/sl/__init__.py b/spacy/lang/sl/__init__.py
index 9ddd676bf..0070e9fa1 100644
--- a/spacy/lang/sl/__init__.py
+++ b/spacy/lang/sl/__init__.py
@@ -1,9 +1,17 @@
+from .lex_attrs import LEX_ATTRS
+from .punctuation import TOKENIZER_INFIXES, TOKENIZER_SUFFIXES, TOKENIZER_PREFIXES
 from .stop_words import STOP_WORDS
+from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
 from ...language import Language, BaseDefaults
 
 
 class SlovenianDefaults(BaseDefaults):
     stop_words = STOP_WORDS
+    tokenizer_exceptions = TOKENIZER_EXCEPTIONS
+    prefixes = TOKENIZER_PREFIXES
+    infixes = TOKENIZER_INFIXES
+    suffixes = TOKENIZER_SUFFIXES
+    lex_attr_getters = LEX_ATTRS
 
 
 class Slovenian(Language):
diff --git a/spacy/lang/sl/lex_attrs.py b/spacy/lang/sl/lex_attrs.py
new file mode 100644
index 000000000..958152e37
--- /dev/null
+++ b/spacy/lang/sl/lex_attrs.py
@@ -0,0 +1,145 @@
+from ...attrs import LIKE_NUM
+from ...attrs import IS_CURRENCY
+import unicodedata
+
+
+_num_words = set(
+    """
+	nula ničla nič ena dva tri štiri pet šest sedem osem
+	devet deset enajst dvanajst trinajst štirinajst petnajst
+	šestnajst sedemnajst osemnajst devetnajst dvajset trideset štirideset
+	petdeset šestdest sedemdeset osemdeset devedeset sto tisoč
+	milijon bilijon trilijon kvadrilijon nešteto
+	
+	en eden enega enemu ennem enim enih enima enimi ene eni eno
+	dveh dvema dvem dvoje trije treh trem tremi troje štirje štirih štirim štirimi
+	petih petim petimi šestih šestim šestimi sedmih sedmim sedmimi osmih osmim osmimi
+	devetih devetim devetimi desetih desetim desetimi enajstih enajstim enajstimi
+	dvanajstih dvanajstim dvanajstimi trinajstih trinajstim trinajstimi
+	šestnajstih šestnajstim šestnajstimi petnajstih petnajstim petnajstimi
+	sedemnajstih sedemnajstim sedemnajstimi osemnajstih osemnajstim osemnajstimi
+	devetnajstih devetnajstim devetnajstimi dvajsetih dvajsetim dvajsetimi  
+	""".split()
+)
+
+_ordinal_words = set(
+    """
+	prvi drugi tretji četrti peti šesti sedmi osmi
+	deveti deseti enajsti dvanajsti trinajsti štirinajsti
+	petnajsti šestnajsti sedemnajsti osemnajsti devetnajsti
+	dvajseti trideseti štirideseti petdeseti šestdeseti sedemdeseti
+	osemdeseti devetdeseti stoti tisoči milijonti bilijonti
+	trilijonti kvadrilijonti nešteti
+	
+	prva druga tretja četrta peta šesta sedma osma
+	deveta deseta enajsta dvanajsta trinajsta štirnajsta
+	petnajsta šestnajsta sedemnajsta osemnajsta devetnajsta
+	dvajseta trideseta štirideseta petdeseta šestdeseta sedemdeseta
+	osemdeseta devetdeseta stota tisoča milijonta bilijonta
+	trilijonta kvadrilijonta nešteta
+	
+	prvo drugo tretje četrto peto šestro sedmo osmo
+	deveto deseto enajsto dvanajsto trinajsto štirnajsto
+	petnajsto šestnajsto sedemnajsto osemnajsto devetnajsto
+	dvajseto trideseto štirideseto petdeseto šestdeseto sedemdeseto
+	osemdeseto devetdeseto stoto tisočo milijonto bilijonto
+	trilijonto kvadrilijonto nešteto
+	
+	prvega drugega tretjega četrtega petega šestega sedmega osmega 
+	devega desetega enajstega dvanajstega trinajstega štirnajstega
+	petnajstega šestnajstega sedemnajstega osemnajstega devetnajstega
+	dvajsetega tridesetega štiridesetega petdesetega šestdesetega sedemdesetega
+	osemdesetega devetdesetega stotega tisočega milijontega bilijontega
+	trilijontega kvadrilijontega neštetega
+	
+	prvemu drugemu tretjemu četrtemu petemu šestemu sedmemu osmemu devetemu desetemu 
+	enajstemu dvanajstemu trinajstemu štirnajstemu petnajstemu šestnajstemu sedemnajstemu
+	osemnajstemu devetnajstemu dvajsetemu tridesetemu štiridesetemu petdesetemu šestdesetemu
+	sedemdesetemu osemdesetemu devetdesetemu stotemu tisočemu milijontemu bilijontemu
+	trilijontemu kvadrilijontemu neštetemu
+	
+	prvem drugem tretjem četrtem petem šestem sedmem osmem devetem desetem
+	enajstem dvanajstem trinajstem štirnajstem petnajstem šestnajstem sedemnajstem
+	osemnajstem devetnajstem dvajsetem tridesetem štiridesetem petdesetem šestdesetem
+	sedemdesetem osemdesetem devetdesetem stotem tisočem milijontem bilijontem
+	trilijontem kvadrilijontem neštetem
+	
+	prvim drugim tretjim četrtim petim šestim sedtim osmim devetim desetim
+	enajstim dvanajstim trinajstim štirnajstim petnajstim šestnajstim sedemnajstim
+	osemnajstim devetnajstim dvajsetim tridesetim štiridesetim petdesetim šestdesetim
+	sedemdesetim osemdesetim devetdesetim stotim tisočim milijontim bilijontim
+	trilijontim kvadrilijontim neštetim
+	    
+	prvih drugih tretjih četrthih petih šestih sedmih osmih deveth desetih
+	enajstih dvanajstih trinajstih štirnajstih petnajstih šestnajstih sedemnajstih
+	osemnajstih devetnajstih dvajsetih tridesetih štiridesetih petdesetih šestdesetih
+	sedemdesetih osemdesetih devetdesetih stotih tisočih milijontih bilijontih
+	trilijontih kvadrilijontih nešteth
+	
+	prvima drugima tretjima četrtima petima šestima sedmima osmima devetima desetima
+	enajstima dvanajstima trinajstima štirnajstima petnajstima šestnajstima sedemnajstima
+	osemnajstima devetnajstima dvajsetima tridesetima štiridesetima petdesetima šestdesetima
+	sedemdesetima osemdesetima devetdesetima stotima tisočima milijontima bilijontima
+	trilijontima kvadrilijontima neštetima
+	
+	prve druge četrte pete šeste sedme osme devete desete
+	enajste dvanajste trinajste štirnajste petnajste šestnajste sedemnajste
+	osemnajste devetnajste dvajsete tridesete štiridesete petdesete šestdesete
+	sedemdesete osemdesete devetdesete stote tisoče milijonte bilijonte 
+	trilijonte kvadrilijonte neštete
+	
+	prvimi drugimi tretjimi četrtimi petimi šestimi sedtimi osmimi devetimi desetimi
+	enajstimi dvanajstimi trinajstimi štirnajstimi petnajstimi šestnajstimi sedemnajstimi
+	osemnajstimi devetnajstimi dvajsetimi tridesetimi štiridesetimi petdesetimi šestdesetimi
+	sedemdesetimi osemdesetimi devetdesetimi stotimi tisočimi milijontimi bilijontimi
+	trilijontimi kvadrilijontimi neštetimi
+	""".split()
+)
+
+_currency_words = set(
+    """
+	evro evra evru evrom evrov evroma evrih evrom evre evri evr eur
+	cent centa centu cenom centov centoma centih centom cente centi
+	dolar dolarja dolarji dolarju dolarjem dolarjev dolarjema dolarjih dolarje usd
+	tolar tolarja tolarji tolarju tolarjem tolarjev tolarjema tolarjih tolarje tol
+	dinar dinarja dinarji dinarju dinarjem dinarjev dinarjema dinarjih dinarje din
+	funt funta funti funtu funtom funtov funtoma funtih funte gpb
+	forint forinta forinti forintu forintom forintov forintoma forintih forinte
+	zlot zlota zloti zlotu zlotom zlotov zlotoma zlotih zlote 
+	rupij rupija rupiji rupiju rupijem rupijev rupijema rupijih rupije
+	jen jena jeni jenu jenom jenov jenoma jenih jene
+	kuna kuni kune kuno kun kunama kunah kunam kunami
+	marka marki marke markama markah markami 
+	""".split()
+)
+
+
+def like_num(text):
+    if text.startswith(("+", "-", "±", "~")):
+        text = text[1:]
+    text = text.replace(",", "").replace(".", "")
+    if text.isdigit():
+        return True
+    if text.count("/") == 1:
+        num, denom = text.split("/")
+        if num.isdigit() and denom.isdigit():
+            return True
+    text_lower = text.lower()
+    if text_lower in _num_words:
+        return True
+    if text_lower in _ordinal_words:
+        return True
+    return False
+
+
+def is_currency(text):
+    text_lower = text.lower()
+    if text in _currency_words:
+        return True
+    for char in text:
+        if unicodedata.category(char) != "Sc":
+            return False
+    return True
+
+
+LEX_ATTRS = {LIKE_NUM: like_num, IS_CURRENCY: is_currency}
diff --git a/spacy/lang/sl/punctuation.py b/spacy/lang/sl/punctuation.py
new file mode 100644
index 000000000..b6ca1830e
--- /dev/null
+++ b/spacy/lang/sl/punctuation.py
@@ -0,0 +1,84 @@
+from ..char_classes import (
+    LIST_ELLIPSES,
+    LIST_ICONS,
+    HYPHENS,
+    LIST_PUNCT,
+    LIST_QUOTES,
+    CURRENCY,
+    UNITS,
+    PUNCT,
+    LIST_CURRENCY,
+    CONCAT_QUOTES,
+)
+from ..char_classes import CONCAT_QUOTES, ALPHA_LOWER, ALPHA_UPPER, ALPHA
+from ..char_classes import merge_chars
+from ..punctuation import TOKENIZER_PREFIXES as BASE_TOKENIZER_PREFIXES
+
+
+INCLUDE_SPECIAL = ["\\+", "\\/", "\\•", "\\¯", "\\=", "\\×"] + HYPHENS.split("|")
+
+_prefixes = INCLUDE_SPECIAL + BASE_TOKENIZER_PREFIXES
+
+_suffixes = (
+    INCLUDE_SPECIAL
+    + LIST_PUNCT
+    + LIST_ELLIPSES
+    + LIST_QUOTES
+    + LIST_ICONS
+    + [
+        r"(?<=°[FfCcKk])\.",
+        r"(?<=[0-9])(?:{c})".format(c=CURRENCY),
+        r"(?<=[0-9])(?:{u})".format(u=UNITS),
+        r"(?<=[{al}{e}{p}(?:{q})])\.".format(
+            al=ALPHA_LOWER, e=r"%²\-\+", q=CONCAT_QUOTES, p=PUNCT
+        ),
+        r"(?<=[{au}][{au}])\.".format(au=ALPHA_UPPER),
+        # split initials like J.K. Rowling
+        r"(?<=[A-Z]\.)(?:[A-Z].)",
+    ]
+)
+
+# a list of all suffixes following a hyphen that are shouldn't split (eg. BTC-jev)
+# source: Obeliks tokenizer - https://github.com/clarinsi/obeliks/blob/master/obeliks/res/TokRulesPart1.txt
+CONCAT_QUOTES = CONCAT_QUOTES.replace("'", "")
+HYPHENS_PERMITTED = (
+    "((a)|(evemu)|(evskega)|(i)|(jevega)|(jevska)|(jevskimi)|(jinemu)|(oma)|(ovim)|"
+    "(ovski)|(e)|(evi)|(evskem)|(ih)|(jevem)|(jevske)|(jevsko)|(jini)|(ov)|(ovima)|"
+    "(ovskih)|(em)|(evih)|(evskemu)|(ja)|(jevemu)|(jevskega)|(ji)|(jinih)|(ova)|"
+    "(ovimi)|(ovskim)|(ema)|(evim)|(evski)|(je)|(jevi)|(jevskem)|(jih)|(jinim)|"
+    "(ove)|(ovo)|(ovskima)|(ev)|(evima)|(evskih)|(jem)|(jevih)|(jevskemu)|(jin)|"
+    "(jinima)|(ovega)|(ovska)|(ovskimi)|(eva)|(evimi)|(evskim)|(jema)|(jevim)|"
+    "(jevski)|(jina)|(jinimi)|(ovem)|(ovske)|(ovsko)|(eve)|(evo)|(evskima)|(jev)|"
+    "(jevima)|(jevskih)|(jine)|(jino)|(ovemu)|(ovskega)|(u)|(evega)|(evska)|"
+    "(evskimi)|(jeva)|(jevimi)|(jevskim)|(jinega)|(ju)|(ovi)|(ovskem)|(evem)|"
+    "(evske)|(evsko)|(jeve)|(jevo)|(jevskima)|(jinem)|(om)|(ovih)|(ovskemu)|"
+    "(ovec)|(ovca)|(ovcu)|(ovcem)|(ovcev)|(ovcema)|(ovcih)|(ovci)|(ovce)|(ovcimi)|"
+    "(evec)|(evca)|(evcu)|(evcem)|(evcev)|(evcema)|(evcih)|(evci)|(evce)|(evcimi)|"
+    "(jevec)|(jevca)|(jevcu)|(jevcem)|(jevcev)|(jevcema)|(jevcih)|(jevci)|(jevce)|"
+    "(jevcimi)|(ovka)|(ovke)|(ovki)|(ovko)|(ovk)|(ovkama)|(ovkah)|(ovkam)|(ovkami)|"
+    "(evka)|(evke)|(evki)|(evko)|(evk)|(evkama)|(evkah)|(evkam)|(evkami)|(jevka)|"
+    "(jevke)|(jevki)|(jevko)|(jevk)|(jevkama)|(jevkah)|(jevkam)|(jevkami)|(timi)|"
+    "(im)|(ima)|(a)|(imi)|(e)|(o)|(ega)|(ti)|(em)|(tih)|(emu)|(tim)|(i)|(tima)|"
+    "(ih)|(ta)|(te)|(to)|(tega)|(tem)|(temu))"
+)
+
+_infixes = (
+    LIST_ELLIPSES
+    + LIST_ICONS
+    + [
+        r"(?<=[0-9])[+\-\*^](?=[0-9-])",
+        r"(?<=[{al}{q}])\.(?=[{au}{q}])".format(
+            al=ALPHA_LOWER, au=ALPHA_UPPER, q=CONCAT_QUOTES
+        ),
+        r"(?<=[{a}]),(?=[{a}])".format(a=ALPHA),
+        r"(?<=[{a}0-9])(?:{h})(?!{hp}$)(?=[{a}])".format(
+            a=ALPHA, h=HYPHENS, hp=HYPHENS_PERMITTED
+        ),
+        r"(?<=[{a}0-9])[:<>=/](?=[{a}])".format(a=ALPHA),
+    ]
+)
+
+
+TOKENIZER_PREFIXES = _prefixes
+TOKENIZER_SUFFIXES = _suffixes
+TOKENIZER_INFIXES = _infixes
diff --git a/spacy/lang/sl/stop_words.py b/spacy/lang/sl/stop_words.py
index c9004ed5d..8491efcb5 100644
--- a/spacy/lang/sl/stop_words.py
+++ b/spacy/lang/sl/stop_words.py
@@ -1,326 +1,84 @@
 # Source: https://github.com/stopwords-iso/stopwords-sl
-# Removed various words that are not normally considered stop words, such as months.
 
 STOP_WORDS = set(
     """
-a
-ali
-b
-bi
-bil
-bila
-bile
-bili
-bilo
-biti
-blizu
-bo
-bodo
-bolj
-bom
-bomo
-boste
-bova
-boš
-brez
-c
-cel
-cela
-celi
-celo
-d
-da
-daleč
-dan
-danes
-do
-dober
-dobra
-dobri
-dobro
-dokler
-dol
-dovolj
-e
-eden
-en
-ena
-ene
-eni
-enkrat
-eno
-etc.
+a ali 
+
+b bi bil bila bile bili bilo biti blizu bo bodo bojo bolj bom bomo 
+boste bova boš brez
+
+c cel cela celi celo
+
+č če često četrta četrtek četrti četrto čez čigav
+
+d da daleč dan danes datum deset deseta deseti deseto devet
+deveta deveti deveto do dober dobra dobri dobro dokler dol dolg
+dolga dolgi dovolj drug druga drugi drugo dva dve
+
+e eden en ena ene eni enkrat eno etc.
+
 f
-g
-g.
-ga
-ga.
-gor
-gospa
-gospod
-h
-halo
-i
-idr.
-ii
-iii
-in
-iv
-ix
-iz
-j
-jaz
-je
-ji
-jih
-jim
-jo
-k
-kadarkoli
-kaj
-kajti
-kako
-kakor
-kamor
-kamorkoli
-kar
-karkoli
-katerikoli
-kdaj
-kdo
-kdorkoli
-ker
-ki
-kje
-kjer
-kjerkoli
-ko
-koderkoli
-koga
-komu
-kot
-l
-le
-lep
-lepa
-lepe
-lepi
-lepo
-m
-manj
-me
-med
-medtem
-mene
-mi
-midva
-midve
-mnogo
-moj
-moja
-moje
-mora
-morajo
-moram
-moramo
-morate
-moraš
-morem
-mu
-n
-na
-nad
-naj
-najina
-najino
-najmanj
-naju
-največ
-nam
-nas
-nato
-nazaj
-naš
-naša
-naše
-ne
-nedavno
-nek
-neka
-nekaj
-nekatere
-nekateri
-nekatero
-nekdo
-neke
-nekega
-neki
-nekje
-neko
-nekoga
-nekoč
-ni
-nikamor
-nikdar
-nikjer
-nikoli
-nič
-nje
-njega
-njegov
-njegova
-njegovo
-njej
-njemu
-njen
-njena
-njeno
-nji
-njih
-njihov
-njihova
-njihovo
-njiju
-njim
-njo
-njun
-njuna
-njuno
-no
-nocoj
-npr.
-o
-ob
-oba
-obe
-oboje
-od
-okoli
-on
-onadva
-one
-oni
-onidve
-oz.
-p
-pa
-po
-pod
-pogosto
-poleg
-ponavadi
-ponovno
-potem
-povsod
-prbl.
-precej
-pred
-prej
-preko
-pri
-pribl.
-približno
-proti
-r
-redko
-res
-s
-saj
-sam
-sama
-same
-sami
-samo
-se
-sebe
-sebi
-sedaj
-sem
-seveda
-si
-sicer
-skoraj
-skozi
-smo
-so
-spet
-sta
-ste
-sva
-t
-ta
-tak
-taka
-take
-taki
-tako
-takoj
-tam
-te
-tebe
-tebi
-tega
-ti
-tista
-tiste
-tisti
-tisto
-tj.
-tja
-to
-toda
-tu
-tudi
-tukaj
-tvoj
-tvoja
-tvoje
+
+g g. ga ga. gor gospa gospod 
+
+h halo 
+
+i idr. ii iii in iv ix iz
+
+j jaz je ji jih jim jo jutri
+
+k kadarkoli kaj kajti kako kakor kamor kamorkoli kar karkoli
+katerikoli kdaj kdo kdorkoli ker ki kje kjer kjerkoli
+ko koder koderkoli koga komu kot kratek kratka kratke kratki
+
+l lahka lahke lahki lahko le lep lepa lepe lepi lepo leto
+
+m majhen majhna majhni malce malo manj me med medtem mene
+mesec mi midva midve mnogo moj moja moje mora morajo moram
+moramo morate moraš morem mu
+
+n na nad naj najina najino najmanj naju največ nam narobe
+nas nato nazaj naš naša naše ne nedavno nedelja nek neka
+nekaj nekatere nekateri nekatero nekdo neke nekega neki
+nekje neko nekoga nekoč ni nikamor nikdar nikjer nikoli
+nič nje njega njegov njegova njegovo njej njemu njen
+njena njeno nji njih njihov njihova njihovo njiju njim
+njo njun njuna njuno no nocoj npr.
+
+o ob oba obe oboje od odprt odprta odprti okoli on
+onadva one oni onidve osem osma osmi osmo oz.
+
+p pa pet peta petek peti peto po pod pogosto poleg poln
+polna polni polno ponavadi ponedeljek ponovno potem
+povsod pozdravljen pozdravljeni prav prava prave pravi
+pravo prazen prazna prazno prbl. precej pred prej preko
+pri pribl. približno primer pripravljen pripravljena
+pripravljeni proti prva prvi prvo
+
+r ravno redko res reč
+
+s saj sam sama same sami samo se sebe sebi sedaj sedem
+sedma sedmi sedmo sem seveda si sicer skoraj skozi slab sm
+so sobota spet sreda srednja srednji sta ste stran stvar sva
+
+š šest šesta šesti šesto štiri 
+
+t ta tak taka take taki tako takoj tam te tebe tebi tega
+težak težka težki težko ti tista tiste tisti tisto tj.
+tja to toda torek tretja tretje tretji tri tu tudi tukaj
+tvoj tvoja tvoje
+
 u
-v
-vaju
-vam
-vas
-vaš
-vaša
-vaše
-ve
-vedno
-vendar
-ves
-več
-vi
-vidva
-vii
-viii
-vsa
-vsaj
-vsak
-vsaka
-vsakdo
-vsake
-vsaki
-vsakomur
-vse
-vsega
-vsi
-vso
-včasih
-x
-z
-za
-zadaj
-zadnji
-zakaj
-zdaj
-zelo
-zunaj
-č
-če
-često
-čez
-čigav
-š
-ž
-že
+
+v vaju vam vas vaš vaša vaše ve vedno velik velika veliki
+veliko vendar ves več vi vidva vii viii visok visoka visoke
+visoki vsa vsaj vsak vsaka vsakdo vsake vsaki vsakomur vse
+vsega vsi vso včasih včeraj 
+
+x 
+
+z za zadaj zadnji zakaj zaprta zaprti zaprto zdaj zelo zunaj
+
+ž že
 """.split()
 )
diff --git a/spacy/lang/sl/tokenizer_exceptions.py b/spacy/lang/sl/tokenizer_exceptions.py
new file mode 100644
index 000000000..3d4109228
--- /dev/null
+++ b/spacy/lang/sl/tokenizer_exceptions.py
@@ -0,0 +1,272 @@
+from typing import Dict, List
+from ..tokenizer_exceptions import BASE_EXCEPTIONS
+from ...symbols import ORTH, NORM
+from ...util import update_exc
+
+_exc: Dict[str, List[Dict]] = {}
+
+_other_exc = {
+    "t.i.": [{ORTH: "t.", NORM: "tako"}, {ORTH: "i.", NORM: "imenovano"}],
+    "t.j.": [{ORTH: "t.", NORM: "to"}, {ORTH: "j.", NORM: "je"}],
+    "T.j.": [{ORTH: "T.", NORM: "to"}, {ORTH: "j.", NORM: "je"}],
+    "d.o.o.": [
+        {ORTH: "d.", NORM: "družba"},
+        {ORTH: "o.", NORM: "omejeno"},
+        {ORTH: "o.", NORM: "odgovornostjo"},
+    ],
+    "D.O.O.": [
+        {ORTH: "D.", NORM: "družba"},
+        {ORTH: "O.", NORM: "omejeno"},
+        {ORTH: "O.", NORM: "odgovornostjo"},
+    ],
+    "d.n.o.": [
+        {ORTH: "d.", NORM: "družba"},
+        {ORTH: "n.", NORM: "neomejeno"},
+        {ORTH: "o.", NORM: "odgovornostjo"},
+    ],
+    "D.N.O.": [
+        {ORTH: "D.", NORM: "družba"},
+        {ORTH: "N.", NORM: "neomejeno"},
+        {ORTH: "O.", NORM: "odgovornostjo"},
+    ],
+    "d.d.": [{ORTH: "d.", NORM: "delniška"}, {ORTH: "d.", NORM: "družba"}],
+    "D.D.": [{ORTH: "D.", NORM: "delniška"}, {ORTH: "D.", NORM: "družba"}],
+    "s.p.": [{ORTH: "s.", NORM: "samostojni"}, {ORTH: "p.", NORM: "podjetnik"}],
+    "S.P.": [{ORTH: "S.", NORM: "samostojni"}, {ORTH: "P.", NORM: "podjetnik"}],
+    "l.r.": [{ORTH: "l.", NORM: "lastno"}, {ORTH: "r.", NORM: "ročno"}],
+    "le-te": [{ORTH: "le"}, {ORTH: "-"}, {ORTH: "te"}],
+    "Le-te": [{ORTH: "Le"}, {ORTH: "-"}, {ORTH: "te"}],
+    "le-ti": [{ORTH: "le"}, {ORTH: "-"}, {ORTH: "ti"}],
+    "Le-ti": [{ORTH: "Le"}, {ORTH: "-"}, {ORTH: "ti"}],
+    "le-to": [{ORTH: "le"}, {ORTH: "-"}, {ORTH: "to"}],
+    "Le-to": [{ORTH: "Le"}, {ORTH: "-"}, {ORTH: "to"}],
+    "le-ta": [{ORTH: "le"}, {ORTH: "-"}, {ORTH: "ta"}],
+    "Le-ta": [{ORTH: "Le"}, {ORTH: "-"}, {ORTH: "ta"}],
+    "le-tega": [{ORTH: "le"}, {ORTH: "-"}, {ORTH: "tega"}],
+    "Le-tega": [{ORTH: "Le"}, {ORTH: "-"}, {ORTH: "tega"}],
+}
+
+_exc.update(_other_exc)
+
+
+for exc_data in [
+    {ORTH: "adm.", NORM: "administracija"},
+    {ORTH: "aer.", NORM: "aeronavtika"},
+    {ORTH: "agr.", NORM: "agronomija"},
+    {ORTH: "amer.", NORM: "ameriško"},
+    {ORTH: "anat.", NORM: "anatomija"},
+    {ORTH: "angl.", NORM: "angleški"},
+    {ORTH: "ant.", NORM: "antonim"},
+    {ORTH: "antr.", NORM: "antropologija"},
+    {ORTH: "apr.", NORM: "april"},
+    {ORTH: "arab.", NORM: "arabsko"},
+    {ORTH: "arheol.", NORM: "arheologija"},
+    {ORTH: "arhit.", NORM: "arhitektura"},
+    {ORTH: "avg.", NORM: "avgust"},
+    {ORTH: "avstr.", NORM: "avstrijsko"},
+    {ORTH: "avt.", NORM: "avtomobilizem"},
+    {ORTH: "bibl.", NORM: "biblijsko"},
+    {ORTH: "biokem.", NORM: "biokemija"},
+    {ORTH: "biol.", NORM: "biologija"},
+    {ORTH: "bolg.", NORM: "bolgarski"},
+    {ORTH: "bot.", NORM: "botanika"},
+    {ORTH: "cit.", NORM: "citat"},
+    {ORTH: "daj.", NORM: "dajalnik"},
+    {ORTH: "del.", NORM: "deležnik"},
+    {ORTH: "ed.", NORM: "ednina"},
+    {ORTH: "etn.", NORM: "etnografija"},
+    {ORTH: "farm.", NORM: "farmacija"},
+    {ORTH: "filat.", NORM: "filatelija"},
+    {ORTH: "filoz.", NORM: "filozofija"},
+    {ORTH: "fin.", NORM: "finančništvo"},
+    {ORTH: "fiz.", NORM: "fizika"},
+    {ORTH: "fot.", NORM: "fotografija"},
+    {ORTH: "fr.", NORM: "francoski"},
+    {ORTH: "friz.", NORM: "frizerstvo"},
+    {ORTH: "gastr.", NORM: "gastronomija"},
+    {ORTH: "geogr.", NORM: "geografija"},
+    {ORTH: "geol.", NORM: "geologija"},
+    {ORTH: "geom.", NORM: "geometrija"},
+    {ORTH: "germ.", NORM: "germanski"},
+    {ORTH: "gl.", NORM: "glej"},
+    {ORTH: "glag.", NORM: "glagolski"},
+    {ORTH: "glasb.", NORM: "glasba"},
+    {ORTH: "gled.", NORM: "gledališče"},
+    {ORTH: "gost.", NORM: "gostinstvo"},
+    {ORTH: "gozd.", NORM: "gozdarstvo"},
+    {ORTH: "gr.", NORM: "grški"},
+    {ORTH: "grad.", NORM: "gradbeništvo"},
+    {ORTH: "hebr.", NORM: "hebrejsko"},
+    {ORTH: "hrv.", NORM: "hrvaško"},
+    {ORTH: "ide.", NORM: "indoevropsko"},
+    {ORTH: "igr.", NORM: "igre"},
+    {ORTH: "im.", NORM: "imenovalnik"},
+    {ORTH: "iron.", NORM: "ironično"},
+    {ORTH: "it.", NORM: "italijanski"},
+    {ORTH: "itd.", NORM: "in tako dalje"},
+    {ORTH: "itn.", NORM: "in tako naprej"},
+    {ORTH: "ipd.", NORM: "in podobno"},
+    {ORTH: "jap.", NORM: "japonsko"},
+    {ORTH: "jul.", NORM: "julij"},
+    {ORTH: "jun.", NORM: "junij"},
+    {ORTH: "kit.", NORM: "kitajsko"},
+    {ORTH: "knj.", NORM: "knjižno"},
+    {ORTH: "knjiž.", NORM: "knjižno"},
+    {ORTH: "kor.", NORM: "koreografija"},
+    {ORTH: "lat.", NORM: "latinski"},
+    {ORTH: "les.", NORM: "lesna stroka"},
+    {ORTH: "lingv.", NORM: "lingvistika"},
+    {ORTH: "lit.", NORM: "literarni"},
+    {ORTH: "ljubk.", NORM: "ljubkovalno"},
+    {ORTH: "lov.", NORM: "lovstvo"},
+    {ORTH: "m.", NORM: "moški"},
+    {ORTH: "mak.", NORM: "makedonski"},
+    {ORTH: "mar.", NORM: "marec"},
+    {ORTH: "mat.", NORM: "matematika"},
+    {ORTH: "med.", NORM: "medicina"},
+    {ORTH: "meh.", NORM: "mehiško"},
+    {ORTH: "mest.", NORM: "mestnik"},
+    {ORTH: "mdr.", NORM: "med drugim"},
+    {ORTH: "min.", NORM: "mineralogija"},
+    {ORTH: "mitol.", NORM: "mitologija"},
+    {ORTH: "mn.", NORM: "množina"},
+    {ORTH: "mont.", NORM: "montanistika"},
+    {ORTH: "muz.", NORM: "muzikologija"},
+    {ORTH: "nam.", NORM: "namenilnik"},
+    {ORTH: "nar.", NORM: "narečno"},
+    {ORTH: "nav.", NORM: "navadno"},
+    {ORTH: "nedol.", NORM: "nedoločnik"},
+    {ORTH: "nedov.", NORM: "nedovršni"},
+    {ORTH: "neprav.", NORM: "nepravilno"},
+    {ORTH: "nepreh.", NORM: "neprehodno"},
+    {ORTH: "neskl.", NORM: "nesklonljiv(o)"},
+    {ORTH: "nestrok.", NORM: "nestrokovno"},
+    {ORTH: "num.", NORM: "numizmatika"},
+    {ORTH: "npr.", NORM: "na primer"},
+    {ORTH: "obrt.", NORM: "obrtništvo"},
+    {ORTH: "okt.", NORM: "oktober"},
+    {ORTH: "or.", NORM: "orodnik"},
+    {ORTH: "os.", NORM: "oseba"},
+    {ORTH: "otr.", NORM: "otroško"},
+    {ORTH: "oz.", NORM: "oziroma"},
+    {ORTH: "pal.", NORM: "paleontologija"},
+    {ORTH: "papir.", NORM: "papirništvo"},
+    {ORTH: "ped.", NORM: "pedagogika"},
+    {ORTH: "pisar.", NORM: "pisarniško"},
+    {ORTH: "pog.", NORM: "pogovorno"},
+    {ORTH: "polit.", NORM: "politika"},
+    {ORTH: "polj.", NORM: "poljsko"},
+    {ORTH: "poljud.", NORM: "poljudno"},
+    {ORTH: "preg.", NORM: "pregovor"},
+    {ORTH: "preh.", NORM: "prehodno"},
+    {ORTH: "pren.", NORM: "preneseno"},
+    {ORTH: "prid.", NORM: "pridevnik"},
+    {ORTH: "prim.", NORM: "primerjaj"},
+    {ORTH: "prisl.", NORM: "prislov"},
+    {ORTH: "psih.", NORM: "psihologija"},
+    {ORTH: "psiht.", NORM: "psihiatrija"},
+    {ORTH: "rad.", NORM: "radiotehnika"},
+    {ORTH: "rač.", NORM: "računalništvo"},
+    {ORTH: "rib.", NORM: "ribištvo"},
+    {ORTH: "rod.", NORM: "rodilnik"},
+    {ORTH: "rus.", NORM: "rusko"},
+    {ORTH: "s.", NORM: "srednji"},
+    {ORTH: "sam.", NORM: "samostalniški"},
+    {ORTH: "sed.", NORM: "sedanjik"},
+    {ORTH: "sep.", NORM: "september"},
+    {ORTH: "slabš.", NORM: "slabšalno"},
+    {ORTH: "slovan.", NORM: "slovansko"},
+    {ORTH: "slovaš.", NORM: "slovaško"},
+    {ORTH: "srb.", NORM: "srbsko"},
+    {ORTH: "star.", NORM: "starinsko"},
+    {ORTH: "stil.", NORM: "stilno"},
+    {ORTH: "sv.", NORM: "svet(i)"},
+    {ORTH: "teh.", NORM: "tehnika"},
+    {ORTH: "tisk.", NORM: "tiskarstvo"},
+    {ORTH: "tj.", NORM: "to je"},
+    {ORTH: "tož.", NORM: "tožilnik"},
+    {ORTH: "trg.", NORM: "trgovina"},
+    {ORTH: "ukr.", NORM: "ukrajinski"},
+    {ORTH: "um.", NORM: "umetnost"},
+    {ORTH: "vel.", NORM: "velelnik"},
+    {ORTH: "vet.", NORM: "veterina"},
+    {ORTH: "vez.", NORM: "veznik"},
+    {ORTH: "vn.", NORM: "visokonemško"},
+    {ORTH: "voj.", NORM: "vojska"},
+    {ORTH: "vrtn.", NORM: "vrtnarstvo"},
+    {ORTH: "vulg.", NORM: "vulgarno"},
+    {ORTH: "vznes.", NORM: "vzneseno"},
+    {ORTH: "zal.", NORM: "založništvo"},
+    {ORTH: "zastar.", NORM: "zastarelo"},
+    {ORTH: "zgod.", NORM: "zgodovina"},
+    {ORTH: "zool.", NORM: "zoologija"},
+    {ORTH: "čeb.", NORM: "čebelarstvo"},
+    {ORTH: "češ.", NORM: "češki"},
+    {ORTH: "člov.", NORM: "človeškost"},
+    {ORTH: "šah.", NORM: "šahovski"},
+    {ORTH: "šalj.", NORM: "šaljivo"},
+    {ORTH: "šp.", NORM: "španski"},
+    {ORTH: "špan.", NORM: "špansko"},
+    {ORTH: "šport.", NORM: "športni"},
+    {ORTH: "štev.", NORM: "števnik"},
+    {ORTH: "šved.", NORM: "švedsko"},
+    {ORTH: "švic.", NORM: "švicarsko"},
+    {ORTH: "ž.", NORM: "ženski"},
+    {ORTH: "žarg.", NORM: "žargonsko"},
+    {ORTH: "žel.", NORM: "železnica"},
+    {ORTH: "živ.", NORM: "živost"},
+]:
+    _exc[exc_data[ORTH]] = [exc_data]
+
+
+abbrv = """
+Co. Ch. DIPL. DR. Dr. Ev. Inc. Jr. Kr. Mag. M. MR. Mr. Mt. Murr. Npr. OZ. 
+Opr. Osn. Prim. Roj. ST. Sim. Sp. Sred. St. Sv. Škofl. Tel. UR. Zb. 
+a. aa. ab. abc. abit. abl. abs. abt. acc. accel. add. adj. adv. aet. afr. akad. al. alban. all. alleg. 
+alp. alt. alter. alžir. am. an. andr. ang. anh. anon. ans. antrop. apoc. app. approx. apt. ar. arc. arch. 
+arh. arr. as. asist. assist. assoc. asst. astr. attn. aug. avstral. az. b. bab. bal. bbl. bd. belg. bioinf. 
+biomed. bk. bl. bn. borg. bp. br. braz. brit. bros. broš. bt. bu. c. ca. cal. can. cand. cantab. cap. capt.
+cat. cath. cc. cca. cd. cdr. cdre. cent. cerkv. cert. cf. cfr. ch. chap. chem. chr. chs. cic. circ. civ. cl.
+cm. cmd. cnr. co. cod. col. coll. colo. com. comp. con. conc. cond. conn. cons. cont. coop. corr. cost. cp.
+cpl. cr. crd. cres. cresc. ct. cu. d. dan. dat. davč. ddr. dec. ded. def. dem. dent. dept. dia. dip. dipl. 
+dir. disp. diss. div. do. doc. dok. dol. doo. dop. dott. dr. dram. druž. družb. drž. dt. duh. dur. dvr. dwt. e.
+ea. ecc. eccl. eccles. econ. edn. egipt. egr. ekon. eksp. el. em. enc. eng. eo. ep. err. esp. esq. est.
+et. etc. etnogr. etnol. ev. evfem. evr. ex. exc. excl. exp. expl. ext. exx. f. fa. facs. fak. faks. fas.
+fasc. fco. fcp. feb. febr. fec. fed. fem. ff. fff. fid. fig. fil. film. fiziol. fiziot. flam. fm. fo. fol. folk.
+frag. fran. franc. fsc. g. ga. gal. gdč. ge. gen. geod. geog. geotehnol. gg. gimn. glas. glav. gnr. go. gor.
+gosp. gp. graf. gram. gren. grš. gs. h. hab. hf. hist. ho. hort. i. ia. ib. ibid. id. idr. idridr. ill. imen.
+imp. impf. impr. in. inc. incl. ind. indus. inf. inform. ing. init. ins. int. inv. inšp. inštr. inž. is. islam.
+ist. ital. iur. iz. izbr. izd. izg. izgr. izr. izv. j. jak. jam. jan. jav. je. jez. jr. jsl. jud. jug.
+jugoslovan. jur. juž. jv. jz. k. kal. kan. kand. kat. kdo. kem. kip. kmet. kol. kom. komp. konf. kont. kost. kov. 
+kp. kpfw. kr. kraj. krat. kub. kult. kv. kval. l. la. lab. lb. ld. let. lib. lik. litt. lj. ljud. ll. loc. log. 
+loč. lt. ma. madž. mag. manag. manjš. masc. mass. mater. max. maxmax. mb. md. mech. medic. medij. medn. 
+mehč. mem. menedž. mes. mess. metal. meteor. meteorol. mex. mi. mikr. mil. minn. mio. misc. miss. mit. mk. 
+mkt. ml. mlad. mlle. mlr. mm. mme. množ. mo. moj. moš. možn. mr. mrd. mrs. ms. msc. msgr. mt. murr. mus. mut. 
+n. na. nad. nadalj. nadom. nagl. nakl. namer. nan. naniz. nasl. nat. navt. nač. ned. nem. nik. nizoz. nm. nn. 
+no. nom. norv. notr. nov. novogr. ns. o. ob. obd. obj. oblač. obl. oblik. obr. obraz. obs. obst. obt. obč. oc. 
+oct. od. odd. odg. odn. odst. odv. oec. off. ok. okla. okr. ont. oo. op. opis. opp. opr. orch. ord. ore. oreg. 
+org. orient. orig. ork. ort. oseb. osn. ot. ozir. ošk. p. pag. par. para. parc. parl. part. past. pat. pdk. 
+pen. perf. pert. perz. pesn. pet. pev. pf. pfc. ph. pharm. phil. pis. pl. po. pod. podr. podaljš. pogl. pogoj. pojm. 
+pok. pokr. pol. poljed. poljub. polu. pom. pomen. pon. ponov. pop. por. port. pos. posl. posn. pov. pp. ppl. pr. 
+praet. prav. pravopis. pravosl. preb. pred. predl. predm. predp. preds. pref. pregib. prel. prem. premen. prep. 
+pres. pret. prev. pribl. prih. pril. primerj. primor. prip. pripor. prir. prist. priv. proc. prof. prog. proiz. 
+prom. pron. prop. prot. protest. prov. ps. pss. pt. publ. pz. q. qld. qu. quad. que. r. racc. rastl. razgl. 
+razl. razv. rd. red. ref. reg. rel. relig. rep. repr. rer. resp. rest. ret. rev. revol. rež. rim. rist. rkp. rm. 
+roj. rom. romun. rp. rr. rt. rud. ruš. ry. sal. samogl. san. sc. scen. sci. scr. sdv. seg. sek. sen. sept. ser. 
+sev. sg. sgt. sh. sig. sigg. sign. sim. sin. sing. sinh. skand. skl. sklad. sklanj. sklep. skr. sl. slik. slov. 
+slovak. slovn. sn. so. sob. soc. sociol. sod. sopomen. sopr. sor. sov. sovj. sp. spec. spl. spr. spreg. sq. sr. 
+sre. sred. sredoz. srh. ss. ssp. st. sta. stan. stanstar. stcsl. ste. stim. stol. stom. str. stroj. strok. stsl. 
+stud. sup. supl. suppl. svet. sz. t. tab. tech. ted. tehn. tehnol. tek. teks. tekst. tel. temp. ten. teol. ter. 
+term. test. th. theol. tim. tip. tisočl. tit. tl. tol. tolmač. tom. tor. tov. tr. trad. traj. trans. tren. 
+trib. tril. trop. trp. trž. ts. tt. tu. tur. turiz. tvor. tvorb. tč. u. ul. umet. un. univ. up. upr. ur. urad. 
+us. ust. utr. v. va. val. var. varn. ven. ver. verb. vest. vezal. vic. vis. viv. viz. viš. vod. vok. vol. vpr. 
+vrst. vrstil. vs. vv. vzd. vzg. vzh. vzor. w. wed. wg. wk. x. y. z. zah. zaim. zak. zap. zasl. zavar. zač. zb. 
+združ. zg. zn. znan. znanstv. zoot. zun. zv. zvd. á. é. ć. č. čas. čet. čl. člen. čustv. đ. ľ. ł. ş. ŠT. š. šir. 
+škofl. škot. šol. št. števil. štud. ů. ű. žen. žival. 
+""".split()
+
+for orth in abbrv:
+    _exc[orth] = [{ORTH: orth}]
+
+
+TOKENIZER_EXCEPTIONS = update_exc(BASE_EXCEPTIONS, _exc)
diff --git a/spacy/tests/lang/sl/test_text.py b/spacy/tests/lang/sl/test_text.py
index ddc5b6b5d..a2a932077 100644
--- a/spacy/tests/lang/sl/test_text.py
+++ b/spacy/tests/lang/sl/test_text.py
@@ -20,7 +20,6 @@ od katerih so te svoboščine odvisne,
     assert len(tokens) == 116
 
 
-@pytest.mark.xfail
 def test_ordinal_number(sl_tokenizer):
     text = "10. decembra 1948"
     tokens = sl_tokenizer(text)

From 23749cfc91110a77e4c6bbaa71ad90d8c056ca0b Mon Sep 17 00:00:00 2001
From: stefawolf <wlf.ste@gmail.com>
Date: Fri, 5 Aug 2022 12:26:38 +0200
Subject: [PATCH 054/174] adding spans to doc_annotation in Example.to_dict
 (#11261)

* adding spans to doc_annotation in Example.to_dict

* to_dict compatible with from_dict: tuples instead of spans

* use strings for label and kb_id

* Simplify test

* Update data formats docs

Co-authored-by: Stefanie Wolf <stefanie.wolf@vitecsoftware.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
---
 spacy/tests/training/test_new_example.py | 38 ++++++++++++++++++++++++
 spacy/training/example.pyx               | 13 ++++++++
 website/docs/api/data-formats.md         |  6 ++--
 3 files changed, 55 insertions(+), 2 deletions(-)

diff --git a/spacy/tests/training/test_new_example.py b/spacy/tests/training/test_new_example.py
index a39d40ded..6b15603b3 100644
--- a/spacy/tests/training/test_new_example.py
+++ b/spacy/tests/training/test_new_example.py
@@ -431,3 +431,41 @@ def test_Example_aligned_whitespace(en_vocab):
 
     example = Example(predicted, reference)
     assert example.get_aligned("TAG", as_string=True) == tags
+
+
+@pytest.mark.issue("11260")
+def test_issue11260():
+    annots = {
+        "words": ["I", "like", "New", "York", "."],
+        "spans": {
+            "cities": [(7, 15, "LOC", "")],
+            "people": [(0, 1, "PERSON", "")],
+        },
+    }
+    vocab = Vocab()
+    predicted = Doc(vocab, words=annots["words"])
+    example = Example.from_dict(predicted, annots)
+    assert len(example.reference.spans["cities"]) == 1
+    assert len(example.reference.spans["people"]) == 1
+
+    output_dict = example.to_dict()
+    assert "spans" in output_dict["doc_annotation"]
+    assert output_dict["doc_annotation"]["spans"]["cities"] == annots["spans"]["cities"]
+    assert output_dict["doc_annotation"]["spans"]["people"] == annots["spans"]["people"]
+
+    output_example = Example.from_dict(predicted, output_dict)
+
+    assert len(output_example.reference.spans["cities"]) == len(
+        example.reference.spans["cities"]
+    )
+    assert len(output_example.reference.spans["people"]) == len(
+        example.reference.spans["people"]
+    )
+    for span in example.reference.spans["cities"]:
+        assert span.label_ == "LOC"
+        assert span.text == "New York"
+        assert span.start_char == 7
+    for span in example.reference.spans["people"]:
+        assert span.label_ == "PERSON"
+        assert span.text == "I"
+        assert span.start_char == 0
diff --git a/spacy/training/example.pyx b/spacy/training/example.pyx
index d592e5a52..dfd337b9e 100644
--- a/spacy/training/example.pyx
+++ b/spacy/training/example.pyx
@@ -361,6 +361,7 @@ cdef class Example:
             "doc_annotation": {
                 "cats": dict(self.reference.cats),
                 "entities": doc_to_biluo_tags(self.reference),
+                "spans": self._spans_to_dict(),
                 "links": self._links_to_dict()
             },
             "token_annotation": {
@@ -376,6 +377,18 @@ cdef class Example:
             }
         }
 
+    def _spans_to_dict(self):
+        span_dict = {}
+        for key in self.reference.spans:
+            span_tuples = []
+            for span in self.reference.spans[key]: 
+                span_tuple = (span.start_char, span.end_char, span.label_, span.kb_id_)
+                span_tuples.append(span_tuple)
+            span_dict[key] = span_tuples
+
+        return span_dict
+
+
     def _links_to_dict(self):
         links = {}
         for ent in self.reference.ents:
diff --git a/website/docs/api/data-formats.md b/website/docs/api/data-formats.md
index b7aedc511..ce06c4ea8 100644
--- a/website/docs/api/data-formats.md
+++ b/website/docs/api/data-formats.md
@@ -395,12 +395,13 @@ file to keep track of your settings and hyperparameters and your own
 >    "pos": List[str],
 >    "morphs": List[str],
 >    "sent_starts": List[Optional[bool]],
->    "deps": List[string],
+>    "deps": List[str],
 >    "heads": List[int],
 >    "entities": List[str],
 >    "entities": List[(int, int, str)],
 >    "cats": Dict[str, float],
 >    "links": Dict[(int, int), dict],
+>    "spans": Dict[str, List[Tuple]],
 > }
 > ```
 
@@ -417,9 +418,10 @@ file to keep track of your settings and hyperparameters and your own
 | `deps`        | List of string values indicating the [dependency relation](/usage/linguistic-features#dependency-parse) of a token to its head. ~~List[str]~~                                                                                  |
 | `heads`       | List of integer values indicating the dependency head of each token, referring to the absolute index of each token in the text. ~~List[int]~~                                                                                  |
 | `entities`    | **Option 1:** List of [BILUO tags](/usage/linguistic-features#accessing-ner) per token of the format `"{action}-{label}"`, or `None` for unannotated tokens. ~~List[str]~~                                                     |
-| `entities`    | **Option 2:** List of `"(start, end, label)"` tuples defining all entities in the text. ~~List[Tuple[int, int, str]]~~                                                                                                         |
+| `entities`    | **Option 2:** List of `(start_char, end_char, label)` tuples defining all entities in the text. ~~List[Tuple[int, int, str]]~~                                                                                                 |
 | `cats`        | Dictionary of `label`/`value` pairs indicating how relevant a certain [text category](/api/textcategorizer) is for the text. ~~Dict[str, float]~~                                                                              |
 | `links`       | Dictionary of `offset`/`dict` pairs defining [named entity links](/usage/linguistic-features#entity-linking). The character offsets are linked to a dictionary of relevant knowledge base IDs. ~~Dict[Tuple[int, int], Dict]~~ |
+| `spans`       | Dictionary of `spans_key`/`List[Tuple]` pairs defining the spans for each spans key as `(start_char, end_char, label, kb_id)` tuples. ~~Dict[str, List[Tuple[int, int, str, str]]~~                                            |
 
 <Infobox title="Notes and caveats">
 

From fc4246558be4f6e9b3e71afb814019552764cfb1 Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Tue, 9 Aug 2022 10:59:36 +0200
Subject: [PATCH 055/174] Fix regex invalid escape sequences (#11276)

---
 spacy/lang/ko/punctuation.py | 2 +-
 spacy/schemas.py             | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/spacy/lang/ko/punctuation.py b/spacy/lang/ko/punctuation.py
index 7f7b40c5b..f5f1c51da 100644
--- a/spacy/lang/ko/punctuation.py
+++ b/spacy/lang/ko/punctuation.py
@@ -3,7 +3,7 @@ from ..punctuation import TOKENIZER_INFIXES as BASE_TOKENIZER_INFIXES
 
 
 _infixes = (
-    ["·", "ㆍ", "\(", "\)"]
+    ["·", "ㆍ", r"\(", r"\)"]
     + [r"(?<=[0-9])~(?=[0-9-])"]
     + LIST_QUOTES
     + BASE_TOKENIZER_INFIXES
diff --git a/spacy/schemas.py b/spacy/schemas.py
index 658e45268..9f91451a9 100644
--- a/spacy/schemas.py
+++ b/spacy/schemas.py
@@ -207,7 +207,7 @@ class TokenPatternOperatorSimple(str, Enum):
 
 
 class TokenPatternOperatorMinMax(ConstrainedStr):
-    regex = re.compile("^({\d+}|{\d+,\d*}|{\d*,\d+})$")
+    regex = re.compile(r"^({\d+}|{\d+,\d*}|{\d*,\d+})$")
 
 
 TokenPatternOperator = Union[TokenPatternOperatorSimple, TokenPatternOperatorMinMax]

From e700358ba00cecb2185add0448cf0588b2fc351f Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Tue, 9 Aug 2022 12:15:13 +0200
Subject: [PATCH 056/174] Add W605 to the errors raised by flake8 in the CI
 (#11283)

---
 azure-pipelines.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/azure-pipelines.yml b/azure-pipelines.yml
index 4624b2eb2..f475b7fdd 100644
--- a/azure-pipelines.yml
+++ b/azure-pipelines.yml
@@ -32,7 +32,7 @@ jobs:
           versionSpec: "3.7"
       - script: |
           pip install flake8==3.9.2
-          python -m flake8 spacy --count --select=E901,E999,F821,F822,F823 --show-source --statistics
+          python -m flake8 spacy --count --select=E901,E999,F821,F822,F823,W605 --show-source --statistics
         displayName: "flake8"
 
   - job: "Test"

From 231a17817db0997caab1379e601dac1b9a90b46c Mon Sep 17 00:00:00 2001
From: Paul O'Leary McCann <polm@dampfkraft.com>
Date: Tue, 9 Aug 2022 21:50:50 +0900
Subject: [PATCH 057/174] Clean up automated label-based issue handling
 (#11284)

* Clean up automated label-based issue handline

1. upgrade tiangolo/issue-manager to latest
2. move needs-more-info to tiangolo
3. change needs-more-info close time to 7 days
4. delete old needs-more-info config

* Use old, longer message

* Fix label name
---
 .github/no-response.yml             | 13 -------------
 .github/workflows/issue-manager.yml |  8 +++++++-
 2 files changed, 7 insertions(+), 14 deletions(-)
 delete mode 100644 .github/no-response.yml

diff --git a/.github/no-response.yml b/.github/no-response.yml
deleted file mode 100644
index ea78104b9..000000000
--- a/.github/no-response.yml
+++ /dev/null
@@ -1,13 +0,0 @@
-# Configuration for probot-no-response - https://github.com/probot/no-response
-
-# Number of days of inactivity before an Issue is closed for lack of response
-daysUntilClose: 14
-# Label requiring a response
-responseRequiredLabel: more-info-needed
-# Comment to post when closing an Issue for lack of response. Set to `false` to disable
-closeComment: >
-  This issue has been automatically closed because there has been no response
-  to a request for more information from the original author. With only the
-  information that is currently in the issue, there's not enough information
-  to take action. If you're the original author, feel free to reopen the issue
-  if you have or find the answers needed to investigate further.
diff --git a/.github/workflows/issue-manager.yml b/.github/workflows/issue-manager.yml
index 3fb42ed01..8f3a151ea 100644
--- a/.github/workflows/issue-manager.yml
+++ b/.github/workflows/issue-manager.yml
@@ -15,7 +15,7 @@ jobs:
   issue-manager:
     runs-on: ubuntu-latest
     steps:
-      - uses: tiangolo/issue-manager@0.2.1
+      - uses: tiangolo/issue-manager@0.4.0
         with:
           token: ${{ secrets.GITHUB_TOKEN }}
           config: >
@@ -25,5 +25,11 @@ jobs:
                 "message": "This issue has been automatically closed because it was answered and there was no follow-up discussion.",
                 "remove_label_on_comment": true,
                 "remove_label_on_close": true
+              },
+              "more-info-needed": {
+                "delay": "P7D",
+                "message": "This issue has been automatically closed because there has been no response to a request for more information from the original author. With only the information that is currently in the issue, there's not enough information to take action. If you're the original author, feel free to reopen the issue if you have or find the answers needed to investigate further.",
+                "remove_label_on_comment": true,
+                "remove_label_on_close": true
               }
             }

From ed4ad309e6dd6fb420cbf18e4fd5e8de3291eeba Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Wed, 10 Aug 2022 09:49:08 +0200
Subject: [PATCH 058/174] Fix Dutch noun chunks to skip overlapping spans
 (#11275)

* Add test for overlapping noun chunks

* Skip overlapping noun chunks

* Update spacy/tests/lang/nl/test_noun_chunks.py

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
---
 spacy/lang/nl/syntax_iterators.py       | 11 +++++++----
 spacy/tests/lang/nl/test_noun_chunks.py | 18 +++++++++++++++++-
 2 files changed, 24 insertions(+), 5 deletions(-)

diff --git a/spacy/lang/nl/syntax_iterators.py b/spacy/lang/nl/syntax_iterators.py
index 1ab5e7cff..be9beabe6 100644
--- a/spacy/lang/nl/syntax_iterators.py
+++ b/spacy/lang/nl/syntax_iterators.py
@@ -40,6 +40,7 @@ def noun_chunks(doclike: Union[Doc, Span]) -> Iterator[Tuple[int, int, int]]:
     span_label = doc.vocab.strings.add("NP")
 
     # Only NOUNS and PRONOUNS matter
+    end_span = -1
     for i, word in enumerate(filter(lambda x: x.pos in [PRON, NOUN], doclike)):
         # For NOUNS
         # Pick children from syntactic parse (only those with certain dependencies)
@@ -58,15 +59,17 @@ def noun_chunks(doclike: Union[Doc, Span]) -> Iterator[Tuple[int, int, int]]:
             children_i = [c.i for c in children] + [word.i]
 
             start_span = min(children_i)
-            end_span = max(children_i) + 1
-            yield start_span, end_span, span_label
+            if start_span >= end_span:
+                end_span = max(children_i) + 1
+                yield start_span, end_span, span_label
 
         # PRONOUNS only if it is the subject of a verb
         elif word.pos == PRON:
             if word.dep in pronoun_deps:
                 start_span = word.i
-                end_span = word.i + 1
-                yield start_span, end_span, span_label
+                if start_span >= end_span:
+                    end_span = word.i + 1
+                    yield start_span, end_span, span_label
 
 
 SYNTAX_ITERATORS = {"noun_chunks": noun_chunks}
diff --git a/spacy/tests/lang/nl/test_noun_chunks.py b/spacy/tests/lang/nl/test_noun_chunks.py
index 73b501e4a..8962e3b75 100644
--- a/spacy/tests/lang/nl/test_noun_chunks.py
+++ b/spacy/tests/lang/nl/test_noun_chunks.py
@@ -1,5 +1,6 @@
-from spacy.tokens import Doc
 import pytest
+from spacy.tokens import Doc
+from spacy.util import filter_spans
 
 
 @pytest.fixture
@@ -207,3 +208,18 @@ def test_chunking(nl_sample, nl_reference_chunking):
     """
     chunks = [s.text.lower() for s in nl_sample.noun_chunks]
     assert chunks == nl_reference_chunking
+
+
+@pytest.mark.issue(10846)
+def test_no_overlapping_chunks(nl_vocab):
+    # fmt: off
+    doc = Doc(
+        nl_vocab,
+        words=["Dit", "programma", "wordt", "beschouwd", "als", "'s", "werelds", "eerste", "computerprogramma"],
+        deps=["det", "nsubj:pass", "aux:pass", "ROOT", "mark", "det", "fixed", "amod", "xcomp"],
+        heads=[1, 3, 3, 3, 8, 8, 5, 8, 3],
+        pos=["DET", "NOUN", "AUX", "VERB", "SCONJ", "DET", "NOUN", "ADJ", "NOUN"],
+    )
+    # fmt: on
+    chunks = list(doc.noun_chunks)
+    assert filter_spans(chunks) == chunks

From db7b9938a40830f95f3674c00f122f90805b4f5a Mon Sep 17 00:00:00 2001
From: Peter Baumgartner <5107405+pmbaumgartner@users.noreply.github.com>
Date: Tue, 16 Aug 2022 11:23:34 -0400
Subject: [PATCH 059/174] Docs: displaCy documentation - data types,
 `parse_{deps,ents,spans}`, spans example (#10950)

* add in spans example and parse references

* rm autoformatter

* rm extra ents copy

* TypedDict draft

* type fixes

* restore non-documentation files

* docs update

* fix spans example

* fix hyperlinks

* add parse example

* example fix + argument fix

* fix api arg in docs

* fix bad variable replacement

* fix spacing in style

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* fix spacing on table

* fix spacing on table

* rm temp files

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
---
 spacy/displacy/__init__.py        |  5 ++-
 website/docs/api/top-level.md     | 71 ++++++++++++++++++++++++++++++-
 website/docs/usage/visualizers.md | 39 ++++++++++++++---
 3 files changed, 104 insertions(+), 11 deletions(-)

diff --git a/spacy/displacy/__init__.py b/spacy/displacy/__init__.py
index 5d49b6eb7..7bb300afa 100644
--- a/spacy/displacy/__init__.py
+++ b/spacy/displacy/__init__.py
@@ -123,7 +123,8 @@ def app(environ, start_response):
 def parse_deps(orig_doc: Doc, options: Dict[str, Any] = {}) -> Dict[str, Any]:
     """Generate dependency parse in {'words': [], 'arcs': []} format.
 
-    doc (Doc): Document do parse.
+    orig_doc (Doc): Document to parse.
+    options (Dict[str, Any]): Dependency parse specific visualisation options.
     RETURNS (dict): Generated dependency parse keyed by words and arcs.
     """
     doc = Doc(orig_doc.vocab).from_bytes(
@@ -209,7 +210,7 @@ def parse_ents(doc: Doc, options: Dict[str, Any] = {}) -> Dict[str, Any]:
 
 
 def parse_spans(doc: Doc, options: Dict[str, Any] = {}) -> Dict[str, Any]:
-    """Generate spans in [{start: i, end: i, label: 'label'}] format.
+    """Generate spans in [{start_token: i, end_token: i, label: 'label'}] format.
 
     doc (Doc): Document to parse.
     options (Dict[str, any]): Span-specific visualisation options.
diff --git a/website/docs/api/top-level.md b/website/docs/api/top-level.md
index c96c571e9..1e1925442 100644
--- a/website/docs/api/top-level.md
+++ b/website/docs/api/top-level.md
@@ -240,7 +240,7 @@ browser. Will run a simple web server.
 | Name      | Description                                                                                                                                                       |
 | --------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------- |
 | `docs`    | Document(s) or span(s) to visualize. ~~Union[Iterable[Union[Doc, Span]], Doc, Span]~~                                                                             |
-| `style`   | Visualization style, `"dep"`, `"ent"` or `"span"` <Tag variant="new">3.3</Tag>. Defaults to `"dep"`. ~~str~~                                                                                             |
+| `style`   | Visualization style, `"dep"`, `"ent"` or `"span"` <Tag variant="new">3.3</Tag>. Defaults to `"dep"`. ~~str~~                                                      |
 | `page`    | Render markup as full HTML page. Defaults to `True`. ~~bool~~                                                                                                     |
 | `minify`  | Minify HTML markup. Defaults to `False`. ~~bool~~                                                                                                                 |
 | `options` | [Visualizer-specific options](#displacy_options), e.g. colors. ~~Dict[str, Any]~~                                                                                 |
@@ -265,7 +265,7 @@ Render a dependency parse tree or named entity visualization.
 | Name        | Description                                                                                                                                                                            |
 | ----------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
 | `docs`      | Document(s) or span(s) to visualize. ~~Union[Iterable[Union[Doc, Span, dict]], Doc, Span, dict]~~                                                                                      |
-| `style`     | Visualization style,`"dep"`, `"ent"` or `"span"` <Tag variant="new">3.3</Tag>. Defaults to `"dep"`. ~~str~~                                                                                                                  |
+| `style`     | Visualization style, `"dep"`, `"ent"` or `"span"` <Tag variant="new">3.3</Tag>. Defaults to `"dep"`. ~~str~~                                                                           |
 | `page`      | Render markup as full HTML page. Defaults to `True`. ~~bool~~                                                                                                                          |
 | `minify`    | Minify HTML markup. Defaults to `False`. ~~bool~~                                                                                                                                      |
 | `options`   | [Visualizer-specific options](#displacy_options), e.g. colors. ~~Dict[str, Any]~~                                                                                                      |
@@ -273,6 +273,73 @@ Render a dependency parse tree or named entity visualization.
 | `jupyter`   | Explicitly enable or disable "[Jupyter](http://jupyter.org/) mode" to return markup ready to be rendered in a notebook. Detected automatically if `None` (default). ~~Optional[bool]~~ |
 | **RETURNS** | The rendered HTML markup. ~~str~~                                                                                                                                                      |
 
+### displacy.parse_deps {#displacy.parse_deps tag="method" new="2"}
+
+Generate dependency parse in `{'words': [], 'arcs': []}` format.
+For use with the `manual=True` argument in `displacy.render`.
+
+> #### Example
+>
+> ```python
+> import spacy
+> from spacy import displacy
+> nlp = spacy.load("en_core_web_sm")
+> doc = nlp("This is a sentence.")
+> deps_parse = displacy.parse_deps(doc)
+> html = displacy.render(deps_parse, style="dep", manual=True)
+> ```
+
+| Name        | Description                                                         |
+| ----------- | ------------------------------------------------------------------- |
+| `orig_doc`  | Doc to parse dependencies. ~~Doc~~                                  |
+| `options`   | Dependency parse specific visualisation options. ~~Dict[str, Any]~~ |
+| **RETURNS** | Generated dependency parse keyed by words and arcs. ~~dict~~        |
+
+### displacy.parse_ents {#displacy.parse_ents tag="method" new="2"}
+
+Generate named entities in `[{start: i, end: i, label: 'label'}]` format.
+For use with the `manual=True` argument in `displacy.render`.
+
+> #### Example
+>
+> ```python
+> import spacy
+> from spacy import displacy
+> nlp = spacy.load("en_core_web_sm")
+> doc = nlp("But Google is starting from behind.")
+> ents_parse = displacy.parse_ents(doc)
+> html = displacy.render(ents_parse, style="ent", manual=True)
+> ```
+
+| Name        | Description                                                         |
+| ----------- | ------------------------------------------------------------------- |
+| `doc`       | Doc to parse entities. ~~Doc~~                                      |
+| `options`   | NER-specific visualisation options. ~~Dict[str, Any]~~              |
+| **RETURNS** | Generated entities keyed by text (original text) and ents. ~~dict~~ |
+
+### displacy.parse_spans {#displacy.parse_spans tag="method" new="2"}
+
+Generate spans in `[{start_token: i, end_token: i, label: 'label'}]` format.
+For use with the `manual=True` argument in `displacy.render`.
+
+> #### Example
+>
+> ```python
+> import spacy
+> from spacy import displacy
+> nlp = spacy.load("en_core_web_sm")
+> doc = nlp("But Google is starting from behind.")
+> doc.spans['orgs'] = [doc[1:2]]
+> ents_parse = displacy.parse_spans(doc, options={"spans_key" : "orgs"})
+> html = displacy.render(ents_parse, style="span", manual=True)
+> ```
+
+| Name        | Description                                                         |
+| ----------- | ------------------------------------------------------------------- |
+| `doc`       | Doc to parse entities. ~~Doc~~                                      |
+| `options`   | Span-specific visualisation options. ~~Dict[str, Any]~~             |
+| **RETURNS** | Generated entities keyed by text (original text) and ents. ~~dict~~ |
+
 ### Visualizer options {#displacy_options}
 
 The `options` argument lets you specify additional settings for each visualizer.
diff --git a/website/docs/usage/visualizers.md b/website/docs/usage/visualizers.md
index d2892b863..da847d939 100644
--- a/website/docs/usage/visualizers.md
+++ b/website/docs/usage/visualizers.md
@@ -198,12 +198,12 @@ import DisplacySpanHtml from 'images/displacy-span.html'
 
 The span visualizer lets you customize the following `options`:
 
-| Argument | Description                                                                                                                                             |
-|-----------------|---------------------------------------------------------------------------------------------------------------------------------------------------------|
-| `spans_key`       | Which spans key to render spans from. Default is `"sc"`. ~~str~~                                                                                                   |
+| Argument          | Description                                                                                                                                                                               |
+| ----------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `spans_key`       | Which spans key to render spans from. Default is `"sc"`. ~~str~~                                                                                                                          |
 | `templates`       | Dictionary containing the keys `"span"`, `"slice"`, and `"start"`. These dictate how the overall span, a span slice, and the starting token will be rendered. ~~Optional[Dict[str, str]~~ |
-| `kb_url_template` | Optional template to construct the KB url for the entity to link to. Expects a python f-string format with single field to fill in ~~Optional[str]~~                    |
-| `colors`          | Color overrides. Entity types should be mapped to color names or values. ~~Dict[str, str]~~ |
+| `kb_url_template` | Optional template to construct the KB url for the entity to link to. Expects a python f-string format with single field to fill in ~~Optional[str]~~                                      |
+| `colors`          | Color overrides. Entity types should be mapped to color names or values. ~~Dict[str, str]~~                                                                                               |
 
 Because spans can be stored across different keys in `doc.spans`, you need to specify
 which one displaCy should use with `spans_key` (`sc` is the default). 
@@ -343,9 +343,21 @@ want to visualize output from other libraries, like [NLTK](http://www.nltk.org)
 or
 [SyntaxNet](https://github.com/tensorflow/models/tree/master/research/syntaxnet).
 If you set `manual=True` on either `render()` or `serve()`, you can pass in data
-in displaCy's format as a dictionary (instead of `Doc` objects).
+in displaCy's format as a dictionary (instead of `Doc` objects). There are helper 
+functions for converting `Doc` objects to displaCy's format for use with `manual=True`: 
+[`displacy.parse_deps`](/api/top-level#displacy.parse_deps), 
+[`displacy.parse_ents`](/api/top-level#displacy.parse_ents), 
+and [`displacy.parse_spans`](/api/top-level#displacy.parse_spans).
 
-> #### Example
+> #### Example with parse function
+>
+> ```python
+> doc = nlp("But Google is starting from behind.")
+> ex = displacy.parse_ents(doc)
+> html = displacy.render(ex, style="ent", manual=True)
+> ```
+
+> #### Example with raw data
 >
 > ```python
 > ex = [{"text": "But Google is starting from behind.",
@@ -354,6 +366,7 @@ in displaCy's format as a dictionary (instead of `Doc` objects).
 > html = displacy.render(ex, style="ent", manual=True)
 > ```
 
+
 ```python
 ### DEP input
 {
@@ -389,6 +402,18 @@ in displaCy's format as a dictionary (instead of `Doc` objects).
 }
 ```
 
+```python
+### SPANS input
+{
+    "text": "Welcome to the Bank of China.",
+    "spans": [
+        {"start_token": 3, "end_token": 6, "label": "ORG"},
+        {"start_token": 5, "end_token": 6, "label": "GPE"},
+    ],
+    "tokens": ["Welcome", "to", "the", "Bank", "of", "China", "."],
+}
+```
+
 ## Using displaCy in a web application {#webapp}
 
 If you want to use the visualizers as part of a web application, for example to

From cab263791ff25a713bd2a0e72759fa48aff36b9f Mon Sep 17 00:00:00 2001
From: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Date: Wed, 17 Aug 2022 19:55:54 +0200
Subject: [PATCH 060/174] include span_ruler for default warning filter
 (#11333)

---
 spacy/errors.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/spacy/errors.py b/spacy/errors.py
index fd412a4da..9a679ae2c 100644
--- a/spacy/errors.py
+++ b/spacy/errors.py
@@ -16,8 +16,8 @@ def setup_default_warnings():
     filter_warning("ignore", error_msg="numpy.dtype size changed")  # noqa
     filter_warning("ignore", error_msg="numpy.ufunc size changed")  # noqa
 
-    # warn about entity_ruler & matcher having no patterns only once
-    for pipe in ["matcher", "entity_ruler"]:
+    # warn about entity_ruler, span_ruler & matcher having no patterns only once
+    for pipe in ["matcher", "entity_ruler", "span_ruler"]:
         filter_warning("once", error_msg=Warnings.W036.format(name=pipe))
 
     # warn once about lemmatizer without required POS

From 09b3118b26520786db5fee468008be4f0653614d Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Thu, 18 Aug 2022 14:04:57 +0200
Subject: [PATCH 061/174] Add uk pipelines to website (#11332)

---
 website/meta/languages.json | 10 ++++++++++
 1 file changed, 10 insertions(+)

diff --git a/website/meta/languages.json b/website/meta/languages.json
index 6bc2309ed..87c91f791 100644
--- a/website/meta/languages.json
+++ b/website/meta/languages.json
@@ -467,10 +467,20 @@
             "code": "uk",
             "name": "Ukrainian",
             "has_examples": true,
+            "models": [
+                "uk_core_news_sm",
+                "uk_core_news_md",
+                "uk_core_news_lg",
+                "uk_core_news_trf"
+            ],
             "dependencies": [
                 {
                     "name": "pymorphy2",
                     "url": "https://github.com/kmike/pymorphy2"
+                },
+                {
+                    "name": "pymorphy2-dicts-uk",
+                    "url": "https://github.com/kmike/pymorphy2-dicts/"
                 }
             ]
         },

From 3e4cf1bbe1745a55ede0dece31353aebc3f82729 Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Fri, 19 Aug 2022 09:52:12 +0200
Subject: [PATCH 062/174] Check for . in factory names (#11336)

---
 spacy/errors.py              |  2 ++
 spacy/language.py            |  9 +++++++--
 spacy/tests/test_language.py | 11 +++++++++++
 3 files changed, 20 insertions(+), 2 deletions(-)

diff --git a/spacy/errors.py b/spacy/errors.py
index 9a679ae2c..40e50aaa9 100644
--- a/spacy/errors.py
+++ b/spacy/errors.py
@@ -540,6 +540,8 @@ class Errors(metaclass=ErrorsWithCodes):
     E202 = ("Unsupported {name} mode '{mode}'. Supported modes: {modes}.")
 
     # New errors added in v3.x
+    E853 = ("Unsupported component factory name '{name}'. The character '.' is "
+            "not permitted in factory names.")
     E854 = ("Unable to set doc.ents. Check that the 'ents_filter' does not "
             "permit overlapping spans.")
     E855 = ("Invalid {obj}: {obj} is not from the same doc.")
diff --git a/spacy/language.py b/spacy/language.py
index 816bd6531..e89ae142b 100644
--- a/spacy/language.py
+++ b/spacy/language.py
@@ -465,6 +465,8 @@ class Language:
         """
         if not isinstance(name, str):
             raise ValueError(Errors.E963.format(decorator="factory"))
+        if "." in name:
+            raise ValueError(Errors.E853.format(name=name))
         if not isinstance(default_config, dict):
             err = Errors.E962.format(
                 style="default config", name=name, cfg_type=type(default_config)
@@ -543,8 +545,11 @@ class Language:
 
         DOCS: https://spacy.io/api/language#component
         """
-        if name is not None and not isinstance(name, str):
-            raise ValueError(Errors.E963.format(decorator="component"))
+        if name is not None:
+            if not isinstance(name, str):
+                raise ValueError(Errors.E963.format(decorator="component"))
+            if "." in name:
+                raise ValueError(Errors.E853.format(name=name))
         component_name = name if name is not None else util.get_object_name(func)
 
         def add_component(component_func: "Pipe") -> Callable:
diff --git a/spacy/tests/test_language.py b/spacy/tests/test_language.py
index c5fdc8eb0..6f3ba8acc 100644
--- a/spacy/tests/test_language.py
+++ b/spacy/tests/test_language.py
@@ -659,3 +659,14 @@ def test_multiprocessing_gpu_warning(nlp2, texts):
             # Trigger multi-processing.
             for _ in docs:
                 pass
+
+
+def test_dot_in_factory_names(nlp):
+    Language.component("my_evil_component", func=evil_component)
+    nlp.add_pipe("my_evil_component")
+
+    with pytest.raises(ValueError, match="not permitted"):
+        Language.component("my.evil.component.v1", func=evil_component)
+
+    with pytest.raises(ValueError, match="not permitted"):
+        Language.factory("my.evil.component.v1", func=evil_component)

From 5fa8f4faca966fe58c5c8de861900724c7659f25 Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Mon, 22 Aug 2022 11:27:14 +0200
Subject: [PATCH 063/174] Switch ru and uk lemmatizers to pymorphy3 (#11345)

* Switch ru and uk lemmatizers to pymorphy3

* Switch to pymorphy3 in tests
---
 spacy/lang/ru/__init__.py      |  2 +-
 spacy/lang/ru/lemmatizer.py    | 15 ++++++++++++++-
 spacy/lang/uk/__init__.py      |  2 +-
 spacy/lang/uk/lemmatizer.py    | 13 ++++++++++++-
 spacy/tests/conftest.py        | 10 +++++-----
 website/docs/api/lemmatizer.md |  6 +++---
 website/meta/languages.json    |  8 ++++----
 7 files changed, 40 insertions(+), 16 deletions(-)

diff --git a/spacy/lang/ru/__init__.py b/spacy/lang/ru/__init__.py
index c118c26ff..7d17628c4 100644
--- a/spacy/lang/ru/__init__.py
+++ b/spacy/lang/ru/__init__.py
@@ -28,7 +28,7 @@ class Russian(Language):
     assigns=["token.lemma"],
     default_config={
         "model": None,
-        "mode": "pymorphy2",
+        "mode": "pymorphy3",
         "overwrite": False,
         "scorer": {"@scorers": "spacy.lemmatizer_scorer.v1"},
     },
diff --git a/spacy/lang/ru/lemmatizer.py b/spacy/lang/ru/lemmatizer.py
index 85180b1e4..720d3a8cb 100644
--- a/spacy/lang/ru/lemmatizer.py
+++ b/spacy/lang/ru/lemmatizer.py
@@ -19,7 +19,7 @@ class RussianLemmatizer(Lemmatizer):
         model: Optional[Model],
         name: str = "lemmatizer",
         *,
-        mode: str = "pymorphy2",
+        mode: str = "pymorphy3",
         overwrite: bool = False,
         scorer: Optional[Callable] = lemmatizer_score,
     ) -> None:
@@ -33,6 +33,16 @@ class RussianLemmatizer(Lemmatizer):
                 ) from None
             if getattr(self, "_morph", None) is None:
                 self._morph = MorphAnalyzer()
+        elif mode == "pymorphy3":
+            try:
+                from pymorphy3 import MorphAnalyzer
+            except ImportError:
+                raise ImportError(
+                    "The Russian lemmatizer mode 'pymorphy3' requires the "
+                    "pymorphy3 library. Install it with: pip install pymorphy3"
+                ) from None
+            if getattr(self, "_morph", None) is None:
+                self._morph = MorphAnalyzer()
         super().__init__(
             vocab, model, name, mode=mode, overwrite=overwrite, scorer=scorer
         )
@@ -104,6 +114,9 @@ class RussianLemmatizer(Lemmatizer):
             return [analyses[0].normal_form]
         return [string]
 
+    def pymorphy3_lemmatize(self, token: Token) -> List[str]:
+        return self.pymorphy2_lemmatize(token)
+
 
 def oc2ud(oc_tag: str) -> Tuple[str, Dict[str, str]]:
     gram_map = {
diff --git a/spacy/lang/uk/__init__.py b/spacy/lang/uk/__init__.py
index 737243b66..bfea9ff69 100644
--- a/spacy/lang/uk/__init__.py
+++ b/spacy/lang/uk/__init__.py
@@ -29,7 +29,7 @@ class Ukrainian(Language):
     assigns=["token.lemma"],
     default_config={
         "model": None,
-        "mode": "pymorphy2",
+        "mode": "pymorphy3",
         "overwrite": False,
         "scorer": {"@scorers": "spacy.lemmatizer_scorer.v1"},
     },
diff --git a/spacy/lang/uk/lemmatizer.py b/spacy/lang/uk/lemmatizer.py
index a8bc56057..97ee80479 100644
--- a/spacy/lang/uk/lemmatizer.py
+++ b/spacy/lang/uk/lemmatizer.py
@@ -14,7 +14,7 @@ class UkrainianLemmatizer(RussianLemmatizer):
         model: Optional[Model],
         name: str = "lemmatizer",
         *,
-        mode: str = "pymorphy2",
+        mode: str = "pymorphy3",
         overwrite: bool = False,
         scorer: Optional[Callable] = lemmatizer_score,
     ) -> None:
@@ -29,6 +29,17 @@ class UkrainianLemmatizer(RussianLemmatizer):
                 ) from None
             if getattr(self, "_morph", None) is None:
                 self._morph = MorphAnalyzer(lang="uk")
+        elif mode == "pymorphy3":
+            try:
+                from pymorphy3 import MorphAnalyzer
+            except ImportError:
+                raise ImportError(
+                    "The Ukrainian lemmatizer mode 'pymorphy3' requires the "
+                    "pymorphy3 library and dictionaries. Install them with: "
+                    "pip install pymorphy3 pymorphy3-dicts-uk"
+                ) from None
+            if getattr(self, "_morph", None) is None:
+                self._morph = MorphAnalyzer(lang="uk")
         super().__init__(
             vocab, model, name, mode=mode, overwrite=overwrite, scorer=scorer
         )
diff --git a/spacy/tests/conftest.py b/spacy/tests/conftest.py
index eb643ec2f..76de8f373 100644
--- a/spacy/tests/conftest.py
+++ b/spacy/tests/conftest.py
@@ -323,13 +323,13 @@ def ro_tokenizer():
 
 @pytest.fixture(scope="session")
 def ru_tokenizer():
-    pytest.importorskip("pymorphy2")
+    pytest.importorskip("pymorphy3")
     return get_lang_class("ru")().tokenizer
 
 
 @pytest.fixture
 def ru_lemmatizer():
-    pytest.importorskip("pymorphy2")
+    pytest.importorskip("pymorphy3")
     return get_lang_class("ru")().add_pipe("lemmatizer")
 
 
@@ -401,14 +401,14 @@ def ky_tokenizer():
 
 @pytest.fixture(scope="session")
 def uk_tokenizer():
-    pytest.importorskip("pymorphy2")
+    pytest.importorskip("pymorphy3")
     return get_lang_class("uk")().tokenizer
 
 
 @pytest.fixture
 def uk_lemmatizer():
-    pytest.importorskip("pymorphy2")
-    pytest.importorskip("pymorphy2_dicts_uk")
+    pytest.importorskip("pymorphy3")
+    pytest.importorskip("pymorphy3_dicts_uk")
     return get_lang_class("uk")().add_pipe("lemmatizer")
 
 
diff --git a/website/docs/api/lemmatizer.md b/website/docs/api/lemmatizer.md
index 422f34040..905096338 100644
--- a/website/docs/api/lemmatizer.md
+++ b/website/docs/api/lemmatizer.md
@@ -70,7 +70,7 @@ lemmatizer is available. The lemmatizer modes `rule` and `pos_lookup` require
 [`token.pos`](/api/token) from a previous pipeline component (see example
 pipeline configurations in the
 [pretrained pipeline design details](/models#design-cnn)) or rely on third-party
-libraries (`pymorphy2`).
+libraries (`pymorphy3`).
 
 | Language | Default Mode |
 | -------- | ------------ |
@@ -86,9 +86,9 @@ libraries (`pymorphy2`).
 | `nb`     | `rule`       |
 | `nl`     | `rule`       |
 | `pl`     | `pos_lookup` |
-| `ru`     | `pymorphy2`  |
+| `ru`     | `pymorphy3`  |
 | `sv`     | `rule`       |
-| `uk`     | `pymorphy2`  |
+| `uk`     | `pymorphy3`  |
 
 ```python
 %%GITHUB_SPACY/spacy/pipeline/lemmatizer.py
diff --git a/website/meta/languages.json b/website/meta/languages.json
index 6bc2309ed..5305ceffc 100644
--- a/website/meta/languages.json
+++ b/website/meta/languages.json
@@ -369,8 +369,8 @@
             "has_examples": true,
             "dependencies": [
                 {
-                    "name": "pymorphy2",
-                    "url": "https://github.com/kmike/pymorphy2"
+                    "name": "pymorphy3",
+                    "url": "https://github.com/no-plagiarism/pymorphy3"
                 }
             ],
             "models": [
@@ -469,8 +469,8 @@
             "has_examples": true,
             "dependencies": [
                 {
-                    "name": "pymorphy2",
-                    "url": "https://github.com/kmike/pymorphy2"
+                    "name": "pymorphy3",
+                    "url": "https://github.com/no-plagiarism/pymorphy3"
                 }
             ]
         },

From 04c6e5cb9526c3ac3ce395be7de5fa607ddefe4b Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Mon, 22 Aug 2022 11:28:13 +0200
Subject: [PATCH 064/174] Improve floret vectors display in pipeline docs
 (#11343)

---
 website/src/templates/models.js | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/website/src/templates/models.js b/website/src/templates/models.js
index 69cec3376..df53f8c3c 100644
--- a/website/src/templates/models.js
+++ b/website/src/templates/models.js
@@ -114,7 +114,11 @@ function formatVectors(data) {
     if (!data) return 'n/a'
     if (Object.values(data).every(n => n === 0)) return 'context vectors only'
     const { keys, vectors, width } = data
-    return `${abbrNum(keys)} keys, ${abbrNum(vectors)} unique vectors (${width} dimensions)`
+    if (keys >= 0) {
+        return `${abbrNum(keys)} keys, ${abbrNum(vectors)} unique vectors (${width} dimensions)`
+    } else {
+        return `${abbrNum(vectors)} floret vectors (${width} dimensions)`
+    }
 }
 
 function formatAccuracy(data, lang) {

From 0f07defe2ca0ba7a726aafb4a30c89627510bae1 Mon Sep 17 00:00:00 2001
From: Paul O'Leary McCann <polm@dampfkraft.com>
Date: Mon, 22 Aug 2022 18:29:05 +0900
Subject: [PATCH 065/174] Remove reference to voting on issue (#11335)

Not clear which issue this refers to, we don't suggest this for any
other issues, and we don't use votes in general.
---
 spacy/errors.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/spacy/errors.py b/spacy/errors.py
index 40e50aaa9..a1420c8fc 100644
--- a/spacy/errors.py
+++ b/spacy/errors.py
@@ -535,8 +535,7 @@ class Errors(metaclass=ErrorsWithCodes):
     E198 = ("Unable to return {n} most similar vectors for the current vectors "
             "table, which contains {n_rows} vectors.")
     E199 = ("Unable to merge 0-length span at `doc[{start}:{end}]`.")
-    E200 = ("Can't yet set {attr} from Span. Vote for this feature on the "
-            "issue tracker: http://github.com/explosion/spaCy/issues")
+    E200 = ("Can't set {attr} from Span.")
     E202 = ("Unsupported {name} mode '{mode}'. Supported modes: {modes}.")
 
     # New errors added in v3.x

From f55bb7470d2f7267937d8491ae6651fbcf505094 Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Mon, 22 Aug 2022 12:04:30 +0200
Subject: [PATCH 066/174] Clean up warnings in the test suite (#11331)

---
 .github/azure-steps.yml                    | 4 ++--
 spacy/tests/doc/test_doc_api.py            | 5 +++--
 spacy/tests/lang/ru/test_lemmatizer.py     | 3 +++
 spacy/tests/lang/uk/test_lemmatizer.py     | 4 ++++
 spacy/tests/matcher/test_phrase_matcher.py | 9 +++++----
 spacy/tests/pipeline/test_entity_linker.py | 4 ++++
 spacy/training/initialize.py               | 2 ++
 7 files changed, 23 insertions(+), 8 deletions(-)

diff --git a/.github/azure-steps.yml b/.github/azure-steps.yml
index aae08c7f3..18224ba8c 100644
--- a/.github/azure-steps.yml
+++ b/.github/azure-steps.yml
@@ -54,12 +54,12 @@ steps:
     condition: eq(${{ parameters.gpu }}, true)
 
   - script: |
-      ${{ parameters.prefix }} python -m pytest --pyargs spacy
+      ${{ parameters.prefix }} python -m pytest --pyargs spacy -W error
     displayName: "Run CPU tests"
     condition: eq(${{ parameters.gpu }}, false)
 
   - script: |
-      ${{ parameters.prefix }} python -m pytest --pyargs spacy -p spacy.tests.enable_gpu
+      ${{ parameters.prefix }} python -m pytest --pyargs spacy -W error -p spacy.tests.enable_gpu
     displayName: "Run GPU tests"
     condition: eq(${{ parameters.gpu }}, true)
 
diff --git a/spacy/tests/doc/test_doc_api.py b/spacy/tests/doc/test_doc_api.py
index dd4942989..a64ab2ba8 100644
--- a/spacy/tests/doc/test_doc_api.py
+++ b/spacy/tests/doc/test_doc_api.py
@@ -3,6 +3,7 @@ import weakref
 import numpy
 from numpy.testing import assert_array_equal
 import pytest
+import warnings
 from thinc.api import NumpyOps, get_current_ops
 
 from spacy.attrs import DEP, ENT_IOB, ENT_TYPE, HEAD, IS_ALPHA, MORPH, POS
@@ -529,9 +530,9 @@ def test_doc_from_array_sent_starts(en_vocab):
     # no warning using default attrs
     attrs = doc._get_array_attrs()
     arr = doc.to_array(attrs)
-    with pytest.warns(None) as record:
+    with warnings.catch_warnings():
+        warnings.simplefilter("error")
         new_doc.from_array(attrs, arr)
-        assert len(record) == 0
     # only SENT_START uses SENT_START
     attrs = [SENT_START]
     arr = doc.to_array(attrs)
diff --git a/spacy/tests/lang/ru/test_lemmatizer.py b/spacy/tests/lang/ru/test_lemmatizer.py
index 3810323bf..9ca7f441b 100644
--- a/spacy/tests/lang/ru/test_lemmatizer.py
+++ b/spacy/tests/lang/ru/test_lemmatizer.py
@@ -2,6 +2,9 @@ import pytest
 from spacy.tokens import Doc
 
 
+pytestmark = pytest.mark.filterwarnings("ignore::DeprecationWarning")
+
+
 def test_ru_doc_lemmatization(ru_lemmatizer):
     words = ["мама", "мыла", "раму"]
     pos = ["NOUN", "VERB", "NOUN"]
diff --git a/spacy/tests/lang/uk/test_lemmatizer.py b/spacy/tests/lang/uk/test_lemmatizer.py
index 4a787b2a6..57dd4198a 100644
--- a/spacy/tests/lang/uk/test_lemmatizer.py
+++ b/spacy/tests/lang/uk/test_lemmatizer.py
@@ -1,6 +1,10 @@
+import pytest
 from spacy.tokens import Doc
 
 
+pytestmark = pytest.mark.filterwarnings("ignore::DeprecationWarning")
+
+
 def test_uk_lemmatizer(uk_lemmatizer):
     """Check that the default uk lemmatizer runs."""
     doc = Doc(uk_lemmatizer.vocab, words=["a", "b", "c"])
diff --git a/spacy/tests/matcher/test_phrase_matcher.py b/spacy/tests/matcher/test_phrase_matcher.py
index 3b24f3ba8..8a8d9eb84 100644
--- a/spacy/tests/matcher/test_phrase_matcher.py
+++ b/spacy/tests/matcher/test_phrase_matcher.py
@@ -1,4 +1,5 @@
 import pytest
+import warnings
 import srsly
 from mock import Mock
 
@@ -344,13 +345,13 @@ def test_phrase_matcher_validation(en_vocab):
         matcher.add("TEST1", [doc1])
     with pytest.warns(UserWarning):
         matcher.add("TEST2", [doc2])
-    with pytest.warns(None) as record:
+    with warnings.catch_warnings():
+        warnings.simplefilter("error")
         matcher.add("TEST3", [doc3])
-        assert not record.list
     matcher = PhraseMatcher(en_vocab, attr="POS", validate=True)
-    with pytest.warns(None) as record:
+    with warnings.catch_warnings():
+        warnings.simplefilter("error")
         matcher.add("TEST4", [doc2])
-        assert not record.list
 
 
 def test_attr_validation(en_vocab):
diff --git a/spacy/tests/pipeline/test_entity_linker.py b/spacy/tests/pipeline/test_entity_linker.py
index 14995d7b8..82bc976bb 100644
--- a/spacy/tests/pipeline/test_entity_linker.py
+++ b/spacy/tests/pipeline/test_entity_linker.py
@@ -1048,6 +1048,10 @@ def test_no_gold_ents(patterns):
     for eg in train_examples:
         eg.predicted = ruler(eg.predicted)
 
+    # Entity ruler is no longer needed (initialization below wipes out the
+    # patterns and causes warnings)
+    nlp.remove_pipe("entity_ruler")
+
     def create_kb(vocab):
         # create artificial KB
         mykb = KnowledgeBase(vocab, entity_vector_length=vector_length)
diff --git a/spacy/training/initialize.py b/spacy/training/initialize.py
index 48ff7b589..6304e4a84 100644
--- a/spacy/training/initialize.py
+++ b/spacy/training/initialize.py
@@ -337,3 +337,5 @@ def ensure_shape(vectors_loc):
         # store all the results in a list in memory
         lines2 = open_file(vectors_loc)
         yield from lines2
+        lines2.close()
+    lines.close()

From 6e20842370bf9ed33b184013241c42f3d2f2a321 Mon Sep 17 00:00:00 2001
From: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Date: Mon, 22 Aug 2022 15:52:53 +0200
Subject: [PATCH 067/174] dev docs: numeric comparators (#11334)

* add section on numeric comparators

* edit

* prettier

* Update extra/DEVELOPER_DOCS/Code Conventions.md

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

* note on typing imports

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
---
 extra/DEVELOPER_DOCS/Code Conventions.md | 25 +++++++++++++++++++++++-
 1 file changed, 24 insertions(+), 1 deletion(-)

diff --git a/extra/DEVELOPER_DOCS/Code Conventions.md b/extra/DEVELOPER_DOCS/Code Conventions.md
index 31a87d362..7294ac38b 100644
--- a/extra/DEVELOPER_DOCS/Code Conventions.md	
+++ b/extra/DEVELOPER_DOCS/Code Conventions.md	
@@ -191,6 +191,8 @@ def load_model(name: str) -> "Language":
     ...
 ```
 
+Note that we typically put the `from typing` import statements on the first line(s) of the Python module.
+
 ## Structuring logic
 
 ### Positional and keyword arguments
@@ -275,6 +277,27 @@ If you have to use `try`/`except`, make sure to only include what's **absolutely
 +     return [v.strip() for v in value.split(",")]
 ```
 
+### Numeric comparisons
+
+For numeric comparisons, as a general rule we always use `<` and `>=` and avoid the usage of `<=` and `>`. This is to ensure we consistently
+apply inclusive lower bounds and exclusive upper bounds, helping to prevent off-by-one errors.
+
+One exception to this rule is the ternary case. With a chain like
+
+```python
+if value >= 0 and value < max:
+    ...
+```
+
+it's fine to rewrite this to the shorter form
+
+```python
+if 0 <= value < max:
+    ...
+```
+
+even though this requires the usage of the `<=` operator.
+
 ### Iteration and comprehensions
 
 We generally avoid using built-in functions like `filter` or `map` in favor of list or generator comprehensions.
@@ -451,7 +474,7 @@ spaCy uses the [`pytest`](http://doc.pytest.org/) framework for testing. Tests f
 
 When adding tests, make sure to use descriptive names and only test for one behavior at a time. Tests should be grouped into modules dedicated to the same type of functionality and some test modules are organized as directories of test files related to the same larger area of the library, e.g. `matcher` or `tokenizer`.
 
-Regression tests are tests that refer to bugs reported in specific issues. They should live in the relevant module of the test suite, named according to the issue number (e.g., `test_issue1234.py`), and [marked](https://docs.pytest.org/en/6.2.x/example/markers.html#working-with-custom-markers) appropriately (e.g. `@pytest.mark.issue(1234)`). This system allows us to relate tests for specific bugs back to the original reported issue, which is especially useful if we introduce a regression and a previously passing regression tests suddenly fails again. When fixing a bug, it's often useful to create a regression test for it first. 
+Regression tests are tests that refer to bugs reported in specific issues. They should live in the relevant module of the test suite, named according to the issue number (e.g., `test_issue1234.py`), and [marked](https://docs.pytest.org/en/6.2.x/example/markers.html#working-with-custom-markers) appropriately (e.g. `@pytest.mark.issue(1234)`). This system allows us to relate tests for specific bugs back to the original reported issue, which is especially useful if we introduce a regression and a previously passing regression tests suddenly fails again. When fixing a bug, it's often useful to create a regression test for it first.
 
 The test suite also provides [fixtures](https://github.com/explosion/spaCy/blob/master/spacy/tests/conftest.py) for different language tokenizers that can be used as function arguments of the same name and will be passed in automatically. Those should only be used for tests related to those specific languages. We also have [test utility functions](https://github.com/explosion/spaCy/blob/master/spacy/tests/util.py) for common operations, like creating a temporary file.
 

From 7e75327893a60a2985de66bde73f3e1664cdf123 Mon Sep 17 00:00:00 2001
From: Tal Zussman <32444106+tzussman@users.noreply.github.com>
Date: Tue, 23 Aug 2022 01:40:38 -0400
Subject: [PATCH 068/174] Fix menu order in linguistic-features.md (#11364)

Swap 'Vectors & Similarity' and 'Mappings & Exceptions' in menu to match order in body
---
 website/docs/usage/linguistic-features.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/website/docs/usage/linguistic-features.md b/website/docs/usage/linguistic-features.md
index 9dae6f2ee..82472c67e 100644
--- a/website/docs/usage/linguistic-features.md
+++ b/website/docs/usage/linguistic-features.md
@@ -11,8 +11,8 @@ menu:
   - ['Tokenization', 'tokenization']
   - ['Merging & Splitting', 'retokenization']
   - ['Sentence Segmentation', 'sbd']
-  - ['Vectors & Similarity', 'vectors-similarity']
   - ['Mappings & Exceptions', 'mappings-exceptions']
+  - ['Vectors & Similarity', 'vectors-similarity']
   - ['Language Data', 'language-data']
 ---
 

From 5afa98aabfc18a23f19b07b13e2cd12ddb6ee009 Mon Sep 17 00:00:00 2001
From: Edward <43848523+thomashacker@users.noreply.github.com>
Date: Tue, 23 Aug 2022 10:05:02 +0200
Subject: [PATCH 069/174] Support custom attributes for tokens and spans in
 json conversion (#11125)

* Add token and span custom attributes to to_json()

* Change logic for to_json

* Add functionality to from_json

* Small adjustments

* Move token/span attributes to new dict key

* Fix test

* Fix the same test but much better

* Add backwards compatibility tests and adjust logic

* Add test to check if attributes not set in underscore are not saved in the json

* Add tests for json compatibility

* Adjust test names

* Fix tests and clean up code

* Fix assert json tests

* small adjustment

* adjust naming and code readability

* Adjust naming, added more tests and changed logic

* Fix typo

* Adjust errors, naming, and small test optimization

* Fix byte tests

* Fix bytes tests

* Change naming and json structure

* update schema

* Update spacy/schemas.py

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

* Update spacy/tokens/doc.pyx

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

* Update spacy/tokens/doc.pyx

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

* Update spacy/schemas.py

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

* Update schema for underscore attributes

* Adjust underscore schema

* adjust schema tests

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
---
 spacy/errors.py                             |   2 +-
 spacy/schemas.py                            |  12 +-
 spacy/tests/doc/test_json_doc_conversion.py | 194 +++++++++++++++++++-
 spacy/tokens/doc.pyx                        |  59 ++++--
 4 files changed, 243 insertions(+), 24 deletions(-)

diff --git a/spacy/errors.py b/spacy/errors.py
index a1420c8fc..608305a06 100644
--- a/spacy/errors.py
+++ b/spacy/errors.py
@@ -389,7 +389,7 @@ class Errors(metaclass=ErrorsWithCodes):
             "consider using doc.spans instead.")
     E106 = ("Can't find `doc._.{attr}` attribute specified in the underscore "
             "settings: {opts}")
-    E107 = ("Value of `doc._.{attr}` is not JSON-serializable: {value}")
+    E107 = ("Value of custom attribute `{attr}` is not JSON-serializable: {value}")
     E109 = ("Component '{name}' could not be run. Did you forget to "
             "call `initialize()`?")
     E110 = ("Invalid displaCy render wrapper. Expected callable, got: {obj}")
diff --git a/spacy/schemas.py b/spacy/schemas.py
index 9f91451a9..048082134 100644
--- a/spacy/schemas.py
+++ b/spacy/schemas.py
@@ -514,6 +514,14 @@ class DocJSONSchema(BaseModel):
     tokens: List[Dict[StrictStr, Union[StrictStr, StrictInt]]] = Field(
         ..., title="Token information - ID, start, annotations"
     )
-    _: Optional[Dict[StrictStr, Any]] = Field(
-        None, title="Any custom data stored in the document's _ attribute"
+    underscore_doc: Optional[Dict[StrictStr, Any]] = Field(
+        None,
+        title="Any custom data stored in the document's _ attribute",
+        alias="_",
+    )
+    underscore_token: Optional[Dict[StrictStr, Dict[StrictStr, Any]]] = Field(
+        None, title="Any custom data stored in the token's _ attribute"
+    )
+    underscore_span: Optional[Dict[StrictStr, Dict[StrictStr, Any]]] = Field(
+        None, title="Any custom data stored in the span's _ attribute"
     )
diff --git a/spacy/tests/doc/test_json_doc_conversion.py b/spacy/tests/doc/test_json_doc_conversion.py
index 85e4def29..0d7c061c9 100644
--- a/spacy/tests/doc/test_json_doc_conversion.py
+++ b/spacy/tests/doc/test_json_doc_conversion.py
@@ -1,12 +1,15 @@
 import pytest
 import spacy
 from spacy import schemas
-from spacy.tokens import Doc, Span
+from spacy.tokens import Doc, Span, Token
+import srsly
+from .test_underscore import clean_underscore  # noqa: F401
 
 
 @pytest.fixture()
 def doc(en_vocab):
     words = ["c", "d", "e"]
+    spaces = [True, True, True]
     pos = ["VERB", "NOUN", "NOUN"]
     tags = ["VBP", "NN", "NN"]
     heads = [0, 0, 1]
@@ -17,6 +20,7 @@ def doc(en_vocab):
     return Doc(
         en_vocab,
         words=words,
+        spaces=spaces,
         pos=pos,
         tags=tags,
         heads=heads,
@@ -45,6 +49,47 @@ def doc_without_deps(en_vocab):
     )
 
 
+@pytest.fixture()
+def doc_json():
+    return {
+        "text": "c d e ",
+        "ents": [{"start": 2, "end": 3, "label": "ORG"}],
+        "sents": [{"start": 0, "end": 5}],
+        "tokens": [
+            {
+                "id": 0,
+                "start": 0,
+                "end": 1,
+                "tag": "VBP",
+                "pos": "VERB",
+                "morph": "Feat1=A",
+                "dep": "ROOT",
+                "head": 0,
+            },
+            {
+                "id": 1,
+                "start": 2,
+                "end": 3,
+                "tag": "NN",
+                "pos": "NOUN",
+                "morph": "Feat1=B",
+                "dep": "dobj",
+                "head": 0,
+            },
+            {
+                "id": 2,
+                "start": 4,
+                "end": 5,
+                "tag": "NN",
+                "pos": "NOUN",
+                "morph": "Feat1=A|Feat2=D",
+                "dep": "dobj",
+                "head": 1,
+            },
+        ],
+    }
+
+
 def test_doc_to_json(doc):
     json_doc = doc.to_json()
     assert json_doc["text"] == "c d e "
@@ -56,7 +101,8 @@ def test_doc_to_json(doc):
     assert json_doc["ents"][0]["start"] == 2  # character offset!
     assert json_doc["ents"][0]["end"] == 3  # character offset!
     assert json_doc["ents"][0]["label"] == "ORG"
-    assert not schemas.validate(schemas.DocJSONSchema, json_doc)
+    assert len(schemas.validate(schemas.DocJSONSchema, json_doc)) == 0
+    assert srsly.json_loads(srsly.json_dumps(json_doc)) == json_doc
 
 
 def test_doc_to_json_underscore(doc):
@@ -64,11 +110,96 @@ def test_doc_to_json_underscore(doc):
     Doc.set_extension("json_test2", default=False)
     doc._.json_test1 = "hello world"
     doc._.json_test2 = [1, 2, 3]
+
     json_doc = doc.to_json(underscore=["json_test1", "json_test2"])
     assert "_" in json_doc
     assert json_doc["_"]["json_test1"] == "hello world"
     assert json_doc["_"]["json_test2"] == [1, 2, 3]
-    assert not schemas.validate(schemas.DocJSONSchema, json_doc)
+    assert len(schemas.validate(schemas.DocJSONSchema, json_doc)) == 0
+    assert srsly.json_loads(srsly.json_dumps(json_doc)) == json_doc
+
+
+def test_doc_to_json_with_token_span_attributes(doc):
+    Doc.set_extension("json_test1", default=False)
+    Doc.set_extension("json_test2", default=False)
+    Token.set_extension("token_test", default=False)
+    Span.set_extension("span_test", default=False)
+
+    doc._.json_test1 = "hello world"
+    doc._.json_test2 = [1, 2, 3]
+    doc[0:1]._.span_test = "span_attribute"
+    doc[0]._.token_test = 117
+    doc.spans["span_group"] = [doc[0:1]]
+    json_doc = doc.to_json(
+        underscore=["json_test1", "json_test2", "token_test", "span_test"]
+    )
+
+    assert "_" in json_doc
+    assert json_doc["_"]["json_test1"] == "hello world"
+    assert json_doc["_"]["json_test2"] == [1, 2, 3]
+    assert "underscore_token" in json_doc
+    assert "underscore_span" in json_doc
+    assert json_doc["underscore_token"]["token_test"]["value"] == 117
+    assert json_doc["underscore_span"]["span_test"]["value"] == "span_attribute"
+    assert len(schemas.validate(schemas.DocJSONSchema, json_doc)) == 0
+    assert srsly.json_loads(srsly.json_dumps(json_doc)) == json_doc
+
+
+def test_doc_to_json_with_custom_user_data(doc):
+    Doc.set_extension("json_test", default=False)
+    Token.set_extension("token_test", default=False)
+    Span.set_extension("span_test", default=False)
+
+    doc._.json_test = "hello world"
+    doc[0:1]._.span_test = "span_attribute"
+    doc[0]._.token_test = 117
+    json_doc = doc.to_json(underscore=["json_test", "token_test", "span_test"])
+    doc.user_data["user_data_test"] = 10
+    doc.user_data[("user_data_test2", True)] = 10
+
+    assert "_" in json_doc
+    assert json_doc["_"]["json_test"] == "hello world"
+    assert "underscore_token" in json_doc
+    assert "underscore_span" in json_doc
+    assert json_doc["underscore_token"]["token_test"]["value"] == 117
+    assert json_doc["underscore_span"]["span_test"]["value"] == "span_attribute"
+    assert len(schemas.validate(schemas.DocJSONSchema, json_doc)) == 0
+    assert srsly.json_loads(srsly.json_dumps(json_doc)) == json_doc
+
+
+def test_doc_to_json_with_token_span_same_identifier(doc):
+    Doc.set_extension("my_ext", default=False)
+    Token.set_extension("my_ext", default=False)
+    Span.set_extension("my_ext", default=False)
+
+    doc._.my_ext = "hello world"
+    doc[0:1]._.my_ext = "span_attribute"
+    doc[0]._.my_ext = 117
+    json_doc = doc.to_json(underscore=["my_ext"])
+
+    assert "_" in json_doc
+    assert json_doc["_"]["my_ext"] == "hello world"
+    assert "underscore_token" in json_doc
+    assert "underscore_span" in json_doc
+    assert json_doc["underscore_token"]["my_ext"]["value"] == 117
+    assert json_doc["underscore_span"]["my_ext"]["value"] == "span_attribute"
+    assert len(schemas.validate(schemas.DocJSONSchema, json_doc)) == 0
+    assert srsly.json_loads(srsly.json_dumps(json_doc)) == json_doc
+
+
+def test_doc_to_json_with_token_attributes_missing(doc):
+    Token.set_extension("token_test", default=False)
+    Span.set_extension("span_test", default=False)
+
+    doc[0:1]._.span_test = "span_attribute"
+    doc[0]._.token_test = 117
+    json_doc = doc.to_json(underscore=["span_test"])
+
+    assert "underscore_token" in json_doc
+    assert "underscore_span" in json_doc
+    assert json_doc["underscore_span"]["span_test"]["value"] == "span_attribute"
+    assert "token_test" not in json_doc["underscore_token"]
+    assert len(schemas.validate(schemas.DocJSONSchema, json_doc)) == 0
 
 
 def test_doc_to_json_underscore_error_attr(doc):
@@ -94,11 +225,29 @@ def test_doc_to_json_span(doc):
     assert len(json_doc["spans"]) == 1
     assert len(json_doc["spans"]["test"]) == 2
     assert json_doc["spans"]["test"][0]["start"] == 0
-    assert not schemas.validate(schemas.DocJSONSchema, json_doc)
+    assert len(schemas.validate(schemas.DocJSONSchema, json_doc)) == 0
 
 
 def test_json_to_doc(doc):
-    new_doc = Doc(doc.vocab).from_json(doc.to_json(), validate=True)
+    json_doc = doc.to_json()
+    json_doc = srsly.json_loads(srsly.json_dumps(json_doc))
+    new_doc = Doc(doc.vocab).from_json(json_doc, validate=True)
+    assert new_doc.text == doc.text == "c d e "
+    assert len(new_doc) == len(doc) == 3
+    assert new_doc[0].pos == doc[0].pos
+    assert new_doc[0].tag == doc[0].tag
+    assert new_doc[0].dep == doc[0].dep
+    assert new_doc[0].head.idx == doc[0].head.idx
+    assert new_doc[0].lemma == doc[0].lemma
+    assert len(new_doc.ents) == 1
+    assert new_doc.ents[0].start == 1
+    assert new_doc.ents[0].end == 2
+    assert new_doc.ents[0].label_ == "ORG"
+    assert doc.to_bytes() == new_doc.to_bytes()
+
+
+def test_json_to_doc_compat(doc, doc_json):
+    new_doc = Doc(doc.vocab).from_json(doc_json, validate=True)
     new_tokens = [token for token in new_doc]
     assert new_doc.text == doc.text == "c d e "
     assert len(new_tokens) == len([token for token in doc]) == 3
@@ -114,11 +263,8 @@ def test_json_to_doc(doc):
 
 
 def test_json_to_doc_underscore(doc):
-    if not Doc.has_extension("json_test1"):
-        Doc.set_extension("json_test1", default=False)
-    if not Doc.has_extension("json_test2"):
-        Doc.set_extension("json_test2", default=False)
-
+    Doc.set_extension("json_test1", default=False)
+    Doc.set_extension("json_test2", default=False)
     doc._.json_test1 = "hello world"
     doc._.json_test2 = [1, 2, 3]
     json_doc = doc.to_json(underscore=["json_test1", "json_test2"])
@@ -126,6 +272,34 @@ def test_json_to_doc_underscore(doc):
     assert all([new_doc.has_extension(f"json_test{i}") for i in range(1, 3)])
     assert new_doc._.json_test1 == "hello world"
     assert new_doc._.json_test2 == [1, 2, 3]
+    assert doc.to_bytes() == new_doc.to_bytes()
+
+
+def test_json_to_doc_with_token_span_attributes(doc):
+    Doc.set_extension("json_test1", default=False)
+    Doc.set_extension("json_test2", default=False)
+    Token.set_extension("token_test", default=False)
+    Span.set_extension("span_test", default=False)
+    doc._.json_test1 = "hello world"
+    doc._.json_test2 = [1, 2, 3]
+    doc[0:1]._.span_test = "span_attribute"
+    doc[0]._.token_test = 117
+
+    json_doc = doc.to_json(
+        underscore=["json_test1", "json_test2", "token_test", "span_test"]
+    )
+    json_doc = srsly.json_loads(srsly.json_dumps(json_doc))
+    new_doc = Doc(doc.vocab).from_json(json_doc, validate=True)
+
+    assert all([new_doc.has_extension(f"json_test{i}") for i in range(1, 3)])
+    assert new_doc._.json_test1 == "hello world"
+    assert new_doc._.json_test2 == [1, 2, 3]
+    assert new_doc[0]._.token_test == 117
+    assert new_doc[0:1]._.span_test == "span_attribute"
+    assert new_doc.user_data == doc.user_data
+    assert new_doc.to_bytes(exclude=["user_data"]) == doc.to_bytes(
+        exclude=["user_data"]
+    )
 
 
 def test_json_to_doc_spans(doc):
diff --git a/spacy/tokens/doc.pyx b/spacy/tokens/doc.pyx
index d9a104ac8..7ba9a3341 100644
--- a/spacy/tokens/doc.pyx
+++ b/spacy/tokens/doc.pyx
@@ -1602,13 +1602,30 @@ cdef class Doc:
                 ents.append(char_span)
             self.ents = ents
 
-        # Add custom attributes. Note that only Doc extensions are currently considered, Token and Span extensions are
-        # not yet supported.
+        # Add custom attributes for the whole Doc object.
         for attr in doc_json.get("_", {}):
             if not Doc.has_extension(attr):
                 Doc.set_extension(attr)
             self._.set(attr, doc_json["_"][attr])
 
+        if doc_json.get("underscore_token", {}):
+            for token_attr in doc_json["underscore_token"]:
+                token_start = doc_json["underscore_token"][token_attr]["token_start"]
+                value = doc_json["underscore_token"][token_attr]["value"]
+
+                if not Token.has_extension(token_attr):
+                    Token.set_extension(token_attr)
+                self[token_start]._.set(token_attr, value)
+                
+        if doc_json.get("underscore_span", {}):
+            for span_attr in doc_json["underscore_span"]:
+                token_start = doc_json["underscore_span"][span_attr]["token_start"]
+                token_end = doc_json["underscore_span"][span_attr]["token_end"]
+                value = doc_json["underscore_span"][span_attr]["value"]
+
+                if not Span.has_extension(span_attr):
+                    Span.set_extension(span_attr)
+                self[token_start:token_end]._.set(span_attr, value)
         return self
 
     def to_json(self, underscore=None):
@@ -1650,20 +1667,40 @@ cdef class Doc:
             for span_group in self.spans:
                 data["spans"][span_group] = []
                 for span in self.spans[span_group]:
-                    span_data = {
-                        "start": span.start_char, "end": span.end_char, "label": span.label_, "kb_id": span.kb_id_
-                    }
+                    span_data = {"start": span.start_char, "end": span.end_char, "label": span.label_, "kb_id": span.kb_id_}
                     data["spans"][span_group].append(span_data)
 
         if underscore:
-            data["_"] = {}
+            user_keys = set()
+            if self.user_data:
+                data["_"] = {}
+                data["underscore_token"] = {}
+                data["underscore_span"] = {}
+                for data_key in self.user_data:
+                    if type(data_key) == tuple and len(data_key) >= 4 and data_key[0] == "._.":
+                        attr = data_key[1]
+                        start = data_key[2]
+                        end = data_key[3]
+                        if attr in underscore:
+                            user_keys.add(attr)
+                            value = self.user_data[data_key]
+                            if not srsly.is_json_serializable(value):
+                                raise ValueError(Errors.E107.format(attr=attr, value=repr(value)))
+                            # Check if doc attribute
+                            if start is None:
+                                data["_"][attr] = value
+                            # Check if token attribute
+                            elif end is None:
+                                if attr not in data["underscore_token"]:
+                                    data["underscore_token"][attr] = {"token_start": start, "value": value}
+                            # Else span attribute
+                            else:
+                                if attr not in data["underscore_span"]:
+                                    data["underscore_span"][attr] = {"token_start": start, "token_end": end, "value": value}
+
             for attr in underscore:
-                if not self.has_extension(attr):
+                if attr not in user_keys:
                     raise ValueError(Errors.E106.format(attr=attr, opts=underscore))
-                value = self._.get(attr)
-                if not srsly.is_json_serializable(value):
-                    raise ValueError(Errors.E107.format(attr=attr, value=repr(value)))
-                data["_"][attr] = value
         return data
 
     def to_utf8_array(self, int nr_char=-1):

From c09d2fa25bae47f0c70a3dde6bc2bc43c044b231 Mon Sep 17 00:00:00 2001
From: Tobius Saul <30893923+tobiusaolo@users.noreply.github.com>
Date: Tue, 23 Aug 2022 14:09:36 +0300
Subject: [PATCH 070/174] luganda language extension (#10847)

* luganda language extension

* __init__.py changes

* New enhancements

* Lexical attribute changed

* punctuaction and sentence additions

* Remove comment header

* Fix typos, reformat

* reformated version

* Add tokenizer test

* Remove contractions from stop words

* Format

* Add Luganda to website

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
---
 spacy/lang/lg/__init__.py             | 18 +++++
 spacy/lang/lg/examples.py             | 17 +++++
 spacy/lang/lg/lex_attrs.py            | 95 +++++++++++++++++++++++++++
 spacy/lang/lg/punctuation.py          | 19 ++++++
 spacy/lang/lg/stop_words.py           | 19 ++++++
 spacy/tests/conftest.py               |  5 ++
 spacy/tests/lang/lg/__init__.py       |  0
 spacy/tests/lang/lg/test_tokenizer.py | 15 +++++
 website/meta/languages.json           |  5 ++
 9 files changed, 193 insertions(+)
 create mode 100644 spacy/lang/lg/__init__.py
 create mode 100644 spacy/lang/lg/examples.py
 create mode 100644 spacy/lang/lg/lex_attrs.py
 create mode 100644 spacy/lang/lg/punctuation.py
 create mode 100644 spacy/lang/lg/stop_words.py
 create mode 100644 spacy/tests/lang/lg/__init__.py
 create mode 100644 spacy/tests/lang/lg/test_tokenizer.py

diff --git a/spacy/lang/lg/__init__.py b/spacy/lang/lg/__init__.py
new file mode 100644
index 000000000..6f7153fce
--- /dev/null
+++ b/spacy/lang/lg/__init__.py
@@ -0,0 +1,18 @@
+from .stop_words import STOP_WORDS
+from .lex_attrs import LEX_ATTRS
+from .punctuation import TOKENIZER_INFIXES
+from ...language import Language, BaseDefaults
+
+
+class LugandaDefaults(BaseDefaults):
+    lex_attr_getters = LEX_ATTRS
+    infixes = TOKENIZER_INFIXES
+    stop_words = STOP_WORDS
+
+
+class Luganda(Language):
+    lang = "lg"
+    Defaults = LugandaDefaults
+
+
+__all__ = ["Luganda"]
diff --git a/spacy/lang/lg/examples.py b/spacy/lang/lg/examples.py
new file mode 100644
index 000000000..5450c5520
--- /dev/null
+++ b/spacy/lang/lg/examples.py
@@ -0,0 +1,17 @@
+"""
+Example sentences to test spaCy and its language models.
+
+>>> from spacy.lang.lg.examples import sentences
+>>> docs = nlp.pipe(sentences)
+"""
+
+sentences = [
+    "Mpa ebyafaayo ku byalo Nakatu ne Nkajja",
+    "Okuyita Ttembo kitegeeza kugwa ddalu",
+    "Ekifumu kino kyali kya mulimu ki?",
+    "Ekkovu we liyise wayitibwa mukululo",
+    "Akola mulimu ki oguvaamu ssente?",
+    "Emisumaali egikomerera embaawo giyitibwa nninga",
+    "Abooluganda ab’emmamba ababiri",
+    "Ekisaawe ky'ebyenjigiriza kya mugaso nnyo",
+]
diff --git a/spacy/lang/lg/lex_attrs.py b/spacy/lang/lg/lex_attrs.py
new file mode 100644
index 000000000..3c60e3d0e
--- /dev/null
+++ b/spacy/lang/lg/lex_attrs.py
@@ -0,0 +1,95 @@
+from ...attrs import LIKE_NUM
+
+_num_words = [
+    "nnooti",  # Zero
+    "zeero",  # zero
+    "emu",  # one
+    "bbiri",  # two
+    "ssatu",  # three
+    "nnya",  # four
+    "ttaano",  # five
+    "mukaaga",  # six
+    "musanvu",  # seven
+    "munaana",  # eight
+    "mwenda",  # nine
+    "kkumi",  # ten
+    "kkumi n'emu",  # eleven
+    "kkumi na bbiri",  # twelve
+    "kkumi na ssatu",  # thirteen
+    "kkumi na nnya",  # forteen
+    "kkumi na ttaano",  # fifteen
+    "kkumi na mukaaga",  # sixteen
+    "kkumi na musanvu",  # seventeen
+    "kkumi na munaana",  # eighteen
+    "kkumi na mwenda",  # nineteen
+    "amakumi abiri",  # twenty
+    "amakumi asatu",  # thirty
+    "amakumi ana",  # forty
+    "amakumi ataano",  # fifty
+    "nkaaga",  # sixty
+    "nsanvu",  # seventy
+    "kinaana",  # eighty
+    "kyenda",  # ninety
+    "kikumi",  # hundred
+    "lukumi",  # thousand
+    "kakadde",  # million
+    "kawumbi",  # billion
+    "kase",  # trillion
+    "katabalika",  # quadrillion
+    "keesedde",  # gajillion
+    "kafukunya",  # bazillion
+    "ekisooka",  # first
+    "ekyokubiri",  # second
+    "ekyokusatu",  # third
+    "ekyokuna",  # fourth
+    "ekyokutaano",  # fifith
+    "ekyomukaaga",  # sixth
+    "ekyomusanvu",  # seventh
+    "eky'omunaana",  # eighth
+    "ekyomwenda",  # nineth
+    "ekyekkumi",  # tenth
+    "ekyekkumi n'ekimu",  # eleventh
+    "ekyekkumi n'ebibiri",  # twelveth
+    "ekyekkumi n'ebisatu",  # thirteenth
+    "ekyekkumi n'ebina",  # fourteenth
+    "ekyekkumi n'ebitaano",  # fifteenth
+    "ekyekkumi n'omukaaga",  # sixteenth
+    "ekyekkumi n'omusanvu",  # seventeenth
+    "ekyekkumi n'omunaana",  # eigteenth
+    "ekyekkumi n'omwenda",  # nineteenth
+    "ekyamakumi abiri",  # twentieth
+    "ekyamakumi asatu",  # thirtieth
+    "ekyamakumi ana",  # fortieth
+    "ekyamakumi ataano",  # fiftieth
+    "ekyenkaaga",  # sixtieth
+    "ekyensanvu",  # seventieth
+    "ekyekinaana",  # eightieth
+    "ekyekyenda",  # ninetieth
+    "ekyekikumi",  # hundredth
+    "ekyolukumi",  # thousandth
+    "ekyakakadde",  # millionth
+    "ekyakawumbi",  # billionth
+    "ekyakase",  # trillionth
+    "ekyakatabalika",  # quadrillionth
+    "ekyakeesedde",  # gajillionth
+    "ekyakafukunya",  # bazillionth
+]
+
+
+def like_num(text):
+    if text.startswith(("+", "-", "±", "~")):
+        text = text[1:]
+    text = text.replace(",", "").replace(".", "")
+    if text.isdigit():
+        return True
+    if text.count("/") == 1:
+        num, denom = text.split("/")
+        if num.isdigit() and denom.isdigit():
+            return True
+    text_lower = text.lower()
+    if text_lower in _num_words:
+        return True
+    return False
+
+
+LEX_ATTRS = {LIKE_NUM: like_num}
diff --git a/spacy/lang/lg/punctuation.py b/spacy/lang/lg/punctuation.py
new file mode 100644
index 000000000..5d3eb792e
--- /dev/null
+++ b/spacy/lang/lg/punctuation.py
@@ -0,0 +1,19 @@
+from ..char_classes import LIST_ELLIPSES, LIST_ICONS, HYPHENS
+from ..char_classes import CONCAT_QUOTES, ALPHA_LOWER, ALPHA_UPPER, ALPHA
+
+_infixes = (
+    LIST_ELLIPSES
+    + LIST_ICONS
+    + [
+        r"(?<=[0-9])[+\-\*^](?=[0-9-])",
+        r"(?<=[{al}{q}])\.(?=[{au}{q}])".format(
+            al=ALPHA_LOWER, au=ALPHA_UPPER, q=CONCAT_QUOTES
+        ),
+        r"(?<=[{a}]),(?=[{a}])".format(a=ALPHA),
+        r"(?<=[{a}0-9])(?:{h})(?=[{a}])".format(a=ALPHA, h=HYPHENS),
+        r"(?<=[{a}0-9])[:<>=/](?=[{a}])".format(a=ALPHA),
+    ]
+)
+
+
+TOKENIZER_INFIXES = _infixes
diff --git a/spacy/lang/lg/stop_words.py b/spacy/lang/lg/stop_words.py
new file mode 100644
index 000000000..7bad59344
--- /dev/null
+++ b/spacy/lang/lg/stop_words.py
@@ -0,0 +1,19 @@
+STOP_WORDS = set(
+    """
+abadde abalala abamu abangi abava ajja ali alina ani anti ateekeddwa atewamu
+atya awamu aweebwa ayinza ba baali babadde babalina bajja
+bajjanewankubade bali balina bandi bangi bano bateekeddwa baweebwa bayina bebombi beera bibye
+bimu bingi bino bo bokka bonna buli bulijjo bulungi bwabwe bwaffe bwayo bwe bwonna bya byabwe
+byaffe byebimu byonna ddaa ddala ddi e ebimu ebiri ebweruobulungi ebyo edda ejja ekirala ekyo
+endala engeri ennyo era erimu erina ffe ffenna ga gujja gumu gunno guno gwa gwe kaseera kati
+kennyini ki kiki kikino kikye kikyo kino kirungi kki ku kubangabyombi kubangaolwokuba kudda
+kuva kuwa kwegamba kyaffe kye kyekimuoyo kyekyo kyonna leero liryo lwa lwaki lyabwezaabwe
+lyaffe lyange mbadde mingi mpozzi mu mulinaoyina munda mwegyabwe nolwekyo nabadde nabo nandiyagadde
+nandiye nanti naye ne nedda neera nga nnyingi nnyini nnyinza nnyo nti nyinza nze oba ojja okudda
+okugenda okuggyako okutuusa okuva okuwa oli olina oluvannyuma olwekyobuva omuli ono osobola otya
+oyina oyo seetaaga si sinakindi singa talina tayina tebaali tebaalina tebayina terina tetulina
+tetuteekeddwa tewali teyalina teyayina tolina tu tuyina tulina tuyina twafuna twetaaga wa wabula
+wabweru wadde waggulunnina wakati waliwobangi waliyo wandi wange wano wansi weebwa yabadde yaffe
+ye yenna yennyini yina yonna ziba zijja zonna
+""".split()
+)
diff --git a/spacy/tests/conftest.py b/spacy/tests/conftest.py
index eb643ec2f..5193bd301 100644
--- a/spacy/tests/conftest.py
+++ b/spacy/tests/conftest.py
@@ -261,6 +261,11 @@ def lb_tokenizer():
     return get_lang_class("lb")().tokenizer
 
 
+@pytest.fixture(scope="session")
+def lg_tokenizer():
+    return get_lang_class("lg")().tokenizer
+
+
 @pytest.fixture(scope="session")
 def lt_tokenizer():
     return get_lang_class("lt")().tokenizer
diff --git a/spacy/tests/lang/lg/__init__.py b/spacy/tests/lang/lg/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/spacy/tests/lang/lg/test_tokenizer.py b/spacy/tests/lang/lg/test_tokenizer.py
new file mode 100644
index 000000000..958385a77
--- /dev/null
+++ b/spacy/tests/lang/lg/test_tokenizer.py
@@ -0,0 +1,15 @@
+import pytest
+
+LG_BASIC_TOKENIZATION_TESTS = [
+    (
+        "Abooluganda ab’emmamba ababiri",
+        ["Abooluganda", "ab’emmamba", "ababiri"],
+    ),
+]
+
+
+@pytest.mark.parametrize("text,expected_tokens", LG_BASIC_TOKENIZATION_TESTS)
+def test_lg_tokenizer_basic(lg_tokenizer, text, expected_tokens):
+    tokens = lg_tokenizer(text)
+    token_list = [token.text for token in tokens if not token.is_space]
+    assert expected_tokens == token_list
diff --git a/website/meta/languages.json b/website/meta/languages.json
index 87c91f791..79e1fc5d5 100644
--- a/website/meta/languages.json
+++ b/website/meta/languages.json
@@ -265,6 +265,11 @@
             "name": "Luxembourgish",
             "has_examples": true
         },
+        {
+            "code": "lg",
+            "name": "Luganda",
+            "has_examples": true
+        },
         {
             "code": "lij",
             "name": "Ligurian",

From 7a2c58864cfb24b78c28643e22ce8c9686e1f1bf Mon Sep 17 00:00:00 2001
From: Paul O'Leary McCann <polm@dampfkraft.com>
Date: Fri, 26 Aug 2022 17:23:10 +0900
Subject: [PATCH 071/174] Move deps outside explosion to "third-party" (#11381)

---
 setup.cfg | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/setup.cfg b/setup.cfg
index 708300b04..bf4890a68 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -50,9 +50,9 @@ install_requires =
     wasabi>=0.9.1,<1.1.0
     srsly>=2.4.3,<3.0.0
     catalogue>=2.0.6,<2.1.0
+    # Third-party dependencies
     typer>=0.3.0,<0.5.0
     pathy>=0.3.5
-    # Third-party dependencies
     tqdm>=4.38.0,<5.0.0
     numpy>=1.15.0
     requests>=2.13.0,<3.0.0

From ba3320097948cd5056fc068cfc1a9cc1b2d89cf2 Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Fri, 26 Aug 2022 16:07:16 +0200
Subject: [PATCH 072/174] Remove pathy from pyproject.toml (#11383)

---
 pyproject.toml | 1 -
 1 file changed, 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index 317c5fdbe..7abd7a96f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -6,7 +6,6 @@ requires = [
     "preshed>=3.0.2,<3.1.0",
     "murmurhash>=0.28.0,<1.1.0",
     "thinc>=8.1.0,<8.2.0",
-    "pathy",
     "numpy>=1.15.0",
 ]
 build-backend = "setuptools.build_meta"

From 6723d76f24a55f24ef1632ac8be46567a984d0ef Mon Sep 17 00:00:00 2001
From: Edward <43848523+thomashacker@users.noreply.github.com>
Date: Mon, 29 Aug 2022 10:23:05 +0200
Subject: [PATCH 073/174] Add ConsoleLogger.v2 (#11214)

* Init

* Change logger to ConsoleLogger.v2

* adjust naming

* More naming adjustments

* Fix output_file reference error

* ignore type

* Add basic test for logger

* Hopefully fix mypy issue

* mypy ignore line

* Update mypy line

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

* Update test method name

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

* Change file saving logic

* Fix finalize method

* increase spacy-legacy version in requirements

* Update docs

* small adjustments

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
---
 requirements.txt                    |   2 +-
 setup.cfg                           |   2 +-
 spacy/tests/training/test_logger.py |  30 ++++++++
 spacy/training/loggers.py           | 102 +++++++++++++++++++++-------
 website/docs/api/legacy.md          |  53 +++++++++++++++
 website/docs/api/top-level.md       |  57 +++++++++-------
 6 files changed, 198 insertions(+), 48 deletions(-)
 create mode 100644 spacy/tests/training/test_logger.py

diff --git a/requirements.txt b/requirements.txt
index 437dd415a..3b8d66e0e 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,5 +1,5 @@
 # Our libraries
-spacy-legacy>=3.0.9,<3.1.0
+spacy-legacy>=3.0.10,<3.1.0
 spacy-loggers>=1.0.0,<2.0.0
 cymem>=2.0.2,<2.1.0
 preshed>=3.0.2,<3.1.0
diff --git a/setup.cfg b/setup.cfg
index bf4890a68..5fd820a96 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -41,7 +41,7 @@ setup_requires =
     thinc>=8.1.0,<8.2.0
 install_requires =
     # Our libraries
-    spacy-legacy>=3.0.9,<3.1.0
+    spacy-legacy>=3.0.10,<3.1.0
     spacy-loggers>=1.0.0,<2.0.0
     murmurhash>=0.28.0,<1.1.0
     cymem>=2.0.2,<2.1.0
diff --git a/spacy/tests/training/test_logger.py b/spacy/tests/training/test_logger.py
new file mode 100644
index 000000000..0dfd0cbf4
--- /dev/null
+++ b/spacy/tests/training/test_logger.py
@@ -0,0 +1,30 @@
+import pytest
+import spacy
+
+from spacy.training import loggers
+
+
+@pytest.fixture()
+def nlp():
+    nlp = spacy.blank("en")
+    nlp.add_pipe("ner")
+    return nlp
+
+
+@pytest.fixture()
+def info():
+    return {
+        "losses": {"ner": 100},
+        "other_scores": {"ENTS_F": 0.85, "ENTS_P": 0.90, "ENTS_R": 0.80},
+        "epoch": 100,
+        "step": 125,
+        "score": 85,
+    }
+
+
+def test_console_logger(nlp, info):
+    console_logger = loggers.console_logger(
+        progress_bar=True, console_output=True, output_file=None
+    )
+    log_step, finalize = console_logger(nlp)
+    log_step(info)
diff --git a/spacy/training/loggers.py b/spacy/training/loggers.py
index edd0f1959..408ea7140 100644
--- a/spacy/training/loggers.py
+++ b/spacy/training/loggers.py
@@ -1,10 +1,13 @@
-from typing import TYPE_CHECKING, Dict, Any, Tuple, Callable, List, Optional, IO
+from typing import TYPE_CHECKING, Dict, Any, Tuple, Callable, List, Optional, IO, Union
 from wasabi import Printer
+from pathlib import Path
 import tqdm
 import sys
+import srsly
 
 from ..util import registry
 from ..errors import Errors
+from .. import util
 
 if TYPE_CHECKING:
     from ..language import Language  # noqa: F401
@@ -23,13 +26,44 @@ def setup_table(
     return final_cols, final_widths, ["r" for _ in final_widths]
 
 
-@registry.loggers("spacy.ConsoleLogger.v1")
-def console_logger(progress_bar: bool = False):
+@registry.loggers("spacy.ConsoleLogger.v2")
+def console_logger(
+    progress_bar: bool = False,
+    console_output: bool = True,
+    output_file: Optional[Union[str, Path]] = None,
+):
+    """The ConsoleLogger.v2 prints out training logs in the console and/or saves them to a jsonl file.
+    progress_bar (bool): Whether the logger should print the progress bar.
+    console_output (bool): Whether the logger should print the logs on the console.
+    output_file (Optional[Union[str, Path]]): The file to save the training logs to.
+    """
+    _log_exist = False
+    if output_file:
+        output_file = util.ensure_path(output_file)  # type: ignore
+        if output_file.exists():  # type: ignore
+            _log_exist = True
+        if not output_file.parents[0].exists():  # type: ignore
+            output_file.parents[0].mkdir(parents=True)  # type: ignore
+
     def setup_printer(
         nlp: "Language", stdout: IO = sys.stdout, stderr: IO = sys.stderr
     ) -> Tuple[Callable[[Optional[Dict[str, Any]]], None], Callable[[], None]]:
         write = lambda text: print(text, file=stdout, flush=True)
         msg = Printer(no_print=True)
+
+        nonlocal output_file
+        output_stream = None
+        if _log_exist:
+            write(
+                msg.warn(
+                    f"Saving logs is disabled because {output_file} already exists."
+                )
+            )
+            output_file = None
+        elif output_file:
+            write(msg.info(f"Saving results to {output_file}"))
+            output_stream = open(output_file, "w", encoding="utf-8")
+
         # ensure that only trainable components are logged
         logged_pipes = [
             name
@@ -40,13 +74,15 @@ def console_logger(progress_bar: bool = False):
         score_weights = nlp.config["training"]["score_weights"]
         score_cols = [col for col, value in score_weights.items() if value is not None]
         loss_cols = [f"Loss {pipe}" for pipe in logged_pipes]
-        spacing = 2
-        table_header, table_widths, table_aligns = setup_table(
-            cols=["E", "#"] + loss_cols + score_cols + ["Score"],
-            widths=[3, 6] + [8 for _ in loss_cols] + [6 for _ in score_cols] + [6],
-        )
-        write(msg.row(table_header, widths=table_widths, spacing=spacing))
-        write(msg.row(["-" * width for width in table_widths], spacing=spacing))
+
+        if console_output:
+            spacing = 2
+            table_header, table_widths, table_aligns = setup_table(
+                cols=["E", "#"] + loss_cols + score_cols + ["Score"],
+                widths=[3, 6] + [8 for _ in loss_cols] + [6 for _ in score_cols] + [6],
+            )
+            write(msg.row(table_header, widths=table_widths, spacing=spacing))
+            write(msg.row(["-" * width for width in table_widths], spacing=spacing))
         progress = None
 
         def log_step(info: Optional[Dict[str, Any]]) -> None:
@@ -57,12 +93,15 @@ def console_logger(progress_bar: bool = False):
                 if progress is not None:
                     progress.update(1)
                 return
-            losses = [
-                "{0:.2f}".format(float(info["losses"][pipe_name]))
-                for pipe_name in logged_pipes
-            ]
+
+            losses = []
+            log_losses = {}
+            for pipe_name in logged_pipes:
+                losses.append("{0:.2f}".format(float(info["losses"][pipe_name])))
+                log_losses[pipe_name] = float(info["losses"][pipe_name])
 
             scores = []
+            log_scores = {}
             for col in score_cols:
                 score = info["other_scores"].get(col, 0.0)
                 try:
@@ -73,6 +112,7 @@ def console_logger(progress_bar: bool = False):
                 if col != "speed":
                     score *= 100
                 scores.append("{0:.2f}".format(score))
+                log_scores[str(col)] = score
 
             data = (
                 [info["epoch"], info["step"]]
@@ -80,20 +120,36 @@ def console_logger(progress_bar: bool = False):
                 + scores
                 + ["{0:.2f}".format(float(info["score"]))]
             )
+
+            if output_stream:
+                # Write to log file per log_step
+                log_data = {
+                    "epoch": info["epoch"],
+                    "step": info["step"],
+                    "losses": log_losses,
+                    "scores": log_scores,
+                    "score": float(info["score"]),
+                }
+                output_stream.write(srsly.json_dumps(log_data) + "\n")
+
             if progress is not None:
                 progress.close()
-            write(
-                msg.row(data, widths=table_widths, aligns=table_aligns, spacing=spacing)
-            )
-            if progress_bar:
-                # Set disable=None, so that it disables on non-TTY
-                progress = tqdm.tqdm(
-                    total=eval_frequency, disable=None, leave=False, file=stderr
+            if console_output:
+                write(
+                    msg.row(
+                        data, widths=table_widths, aligns=table_aligns, spacing=spacing
+                    )
                 )
-                progress.set_description(f"Epoch {info['epoch']+1}")
+                if progress_bar:
+                    # Set disable=None, so that it disables on non-TTY
+                    progress = tqdm.tqdm(
+                        total=eval_frequency, disable=None, leave=False, file=stderr
+                    )
+                    progress.set_description(f"Epoch {info['epoch']+1}")
 
         def finalize() -> None:
-            pass
+            if output_stream:
+                output_stream.close()
 
         return log_step, finalize
 
diff --git a/website/docs/api/legacy.md b/website/docs/api/legacy.md
index 31d178b67..d9167c76f 100644
--- a/website/docs/api/legacy.md
+++ b/website/docs/api/legacy.md
@@ -248,6 +248,59 @@ added to an existing vectors table. See more details in
 
 ## Loggers {#loggers}
 
+These functions are available from `@spacy.registry.loggers`.
+
+### spacy.ConsoleLogger.v1 {#ConsoleLogger_v1}
+
+> #### Example config
+>
+> ```ini
+> [training.logger]
+> @loggers = "spacy.ConsoleLogger.v1"
+> progress_bar = true
+> ```
+
+Writes the results of a training step to the console in a tabular format.
+
+<Accordion title="Example console output" spaced>
+
+```cli
+$ python -m spacy train config.cfg
+```
+
+```
+ℹ Using CPU
+ℹ Loading config and nlp from: config.cfg
+ℹ Pipeline: ['tok2vec', 'tagger']
+ℹ Start training
+ℹ Training. Initial learn rate: 0.0
+
+E     #        LOSS TOK2VEC   LOSS TAGGER   TAG_ACC   SCORE
+---   ------   ------------   -----------   -------   ------
+  0        0           0.00         86.20      0.22     0.00
+  0      200           3.08      18968.78     34.00     0.34
+  0      400          31.81      22539.06     33.64     0.34
+  0      600          92.13      22794.91     43.80     0.44
+  0      800         183.62      21541.39     56.05     0.56
+  0     1000         352.49      25461.82     65.15     0.65
+  0     1200         422.87      23708.82     71.84     0.72
+  0     1400         601.92      24994.79     76.57     0.77
+  0     1600         662.57      22268.02     80.20     0.80
+  0     1800        1101.50      28413.77     82.56     0.83
+  0     2000        1253.43      28736.36     85.00     0.85
+  0     2200        1411.02      28237.53     87.42     0.87
+  0     2400        1605.35      28439.95     88.70     0.89
+```
+
+Note that the cumulative loss keeps increasing within one epoch, but should
+start decreasing across epochs.
+
+ </Accordion>
+
+| Name           | Description                                               |
+| -------------- | --------------------------------------------------------- |
+| `progress_bar` | Whether the logger should print the progress bar ~~bool~~ |
+
 Logging utilities for spaCy are implemented in the
 [`spacy-loggers`](https://github.com/explosion/spacy-loggers) repo, and the
 functions are typically available from `@spacy.registry.loggers`.
diff --git a/website/docs/api/top-level.md b/website/docs/api/top-level.md
index 1e1925442..c3dc42f1a 100644
--- a/website/docs/api/top-level.md
+++ b/website/docs/api/top-level.md
@@ -275,8 +275,8 @@ Render a dependency parse tree or named entity visualization.
 
 ### displacy.parse_deps {#displacy.parse_deps tag="method" new="2"}
 
-Generate dependency parse in `{'words': [], 'arcs': []}` format.
-For use with the `manual=True` argument in `displacy.render`.
+Generate dependency parse in `{'words': [], 'arcs': []}` format. For use with
+the `manual=True` argument in `displacy.render`.
 
 > #### Example
 >
@@ -297,8 +297,8 @@ For use with the `manual=True` argument in `displacy.render`.
 
 ### displacy.parse_ents {#displacy.parse_ents tag="method" new="2"}
 
-Generate named entities in `[{start: i, end: i, label: 'label'}]` format.
-For use with the `manual=True` argument in `displacy.render`.
+Generate named entities in `[{start: i, end: i, label: 'label'}]` format. For
+use with the `manual=True` argument in `displacy.render`.
 
 > #### Example
 >
@@ -319,8 +319,8 @@ For use with the `manual=True` argument in `displacy.render`.
 
 ### displacy.parse_spans {#displacy.parse_spans tag="method" new="2"}
 
-Generate spans in `[{start_token: i, end_token: i, label: 'label'}]` format.
-For use with the `manual=True` argument in `displacy.render`.
+Generate spans in `[{start_token: i, end_token: i, label: 'label'}]` format. For
+use with the `manual=True` argument in `displacy.render`.
 
 > #### Example
 >
@@ -505,7 +505,7 @@ finished. To log each training step, a
 and the accuracy scores on the development set.
 
 The built-in, default logger is the ConsoleLogger, which prints results to the
-console in tabular format. The
+console in tabular format and saves them to a `jsonl` file. The
 [spacy-loggers](https://github.com/explosion/spacy-loggers) package, included as
 a dependency of spaCy, enables other loggers, such as one that sends results to
 a [Weights & Biases](https://www.wandb.com/) dashboard.
@@ -513,16 +513,20 @@ a [Weights & Biases](https://www.wandb.com/) dashboard.
 Instead of using one of the built-in loggers, you can
 [implement your own](/usage/training#custom-logging).
 
-#### spacy.ConsoleLogger.v1 {#ConsoleLogger tag="registered function"}
+#### spacy.ConsoleLogger.v2 {#ConsoleLogger tag="registered function"}
 
 > #### Example config
 >
 > ```ini
 > [training.logger]
-> @loggers = "spacy.ConsoleLogger.v1"
+> @loggers = "spacy.ConsoleLogger.v2"
+> progress_bar = true
+> console_output = true
+> output_file = "training_log.jsonl"
 > ```
 
-Writes the results of a training step to the console in a tabular format.
+Writes the results of a training step to the console in a tabular format and
+saves them to a `jsonl` file.
 
 <Accordion title="Example console output" spaced>
 
@@ -536,22 +540,23 @@ $ python -m spacy train config.cfg
 ℹ Pipeline: ['tok2vec', 'tagger']
 ℹ Start training
 ℹ Training. Initial learn rate: 0.0
+ℹ Saving results to training_log.jsonl
 
 E     #        LOSS TOK2VEC   LOSS TAGGER   TAG_ACC   SCORE
 ---   ------   ------------   -----------   -------   ------
-  1        0           0.00         86.20      0.22     0.00
-  1      200           3.08      18968.78     34.00     0.34
-  1      400          31.81      22539.06     33.64     0.34
-  1      600          92.13      22794.91     43.80     0.44
-  1      800         183.62      21541.39     56.05     0.56
-  1     1000         352.49      25461.82     65.15     0.65
-  1     1200         422.87      23708.82     71.84     0.72
-  1     1400         601.92      24994.79     76.57     0.77
-  1     1600         662.57      22268.02     80.20     0.80
-  1     1800        1101.50      28413.77     82.56     0.83
-  1     2000        1253.43      28736.36     85.00     0.85
-  1     2200        1411.02      28237.53     87.42     0.87
-  1     2400        1605.35      28439.95     88.70     0.89
+  0        0           0.00         86.20      0.22     0.00
+  0      200           3.08      18968.78     34.00     0.34
+  0      400          31.81      22539.06     33.64     0.34
+  0      600          92.13      22794.91     43.80     0.44
+  0      800         183.62      21541.39     56.05     0.56
+  0     1000         352.49      25461.82     65.15     0.65
+  0     1200         422.87      23708.82     71.84     0.72
+  0     1400         601.92      24994.79     76.57     0.77
+  0     1600         662.57      22268.02     80.20     0.80
+  0     1800        1101.50      28413.77     82.56     0.83
+  0     2000        1253.43      28736.36     85.00     0.85
+  0     2200        1411.02      28237.53     87.42     0.87
+  0     2400        1605.35      28439.95     88.70     0.89
 ```
 
 Note that the cumulative loss keeps increasing within one epoch, but should
@@ -559,6 +564,12 @@ start decreasing across epochs.
 
  </Accordion>
 
+| Name             | Description                                                           |
+| ---------------- | --------------------------------------------------------------------- |
+| `progress_bar`   | Whether the logger should print the progress bar ~~bool~~             |
+| `console_output` | Whether the logger should print the logs on the console. ~~bool~~     |
+| `output_file`    | The file to save the training logs to. ~~Optional[Union[str, Path]]~~ |
+
 ## Readers {#readers}
 
 ### File readers {#file-readers source="github.com/explosion/srsly" new="3"}

From aafee5e1b7c8d13d9ac14c438063621a18bec743 Mon Sep 17 00:00:00 2001
From: Paul O'Leary McCann <polm@dampfkraft.com>
Date: Mon, 29 Aug 2022 17:32:38 +0900
Subject: [PATCH 074/174] Fix lookup usage in French/Catalan (fix #11347)
 (#11382)

* Fix lookup usage (fix #11347)

Before using the lookups table in the French (and Catalan) lemmatizers,
there's a check to see if the current term is in the table. But it's
checking a string against hashes, so it's always false. Also the table
lookup function is designed so you don't have to do that anyway.

* Use the lookup table directly

* Use string, not token
---
 spacy/lang/ca/lemmatizer.py |  6 +++---
 spacy/lang/fr/lemmatizer.py | 13 ++++++++++---
 2 files changed, 13 insertions(+), 6 deletions(-)

diff --git a/spacy/lang/ca/lemmatizer.py b/spacy/lang/ca/lemmatizer.py
index 2fd012912..0f15e6e65 100644
--- a/spacy/lang/ca/lemmatizer.py
+++ b/spacy/lang/ca/lemmatizer.py
@@ -72,10 +72,10 @@ class CatalanLemmatizer(Lemmatizer):
                         oov_forms.append(form)
         if not forms:
             forms.extend(oov_forms)
-        if not forms and string in lookup_table.keys():
-            forms.append(self.lookup_lemmatize(token)[0])
+
+        # use lookups, and fall back to the token itself
         if not forms:
-            forms.append(string)
+            forms.append(lookup_table.get(string, [string])[0])
         forms = list(dict.fromkeys(forms))
         self.cache[cache_key] = forms
         return forms
diff --git a/spacy/lang/fr/lemmatizer.py b/spacy/lang/fr/lemmatizer.py
index c6422cf96..a7cbe0bcf 100644
--- a/spacy/lang/fr/lemmatizer.py
+++ b/spacy/lang/fr/lemmatizer.py
@@ -53,11 +53,16 @@ class FrenchLemmatizer(Lemmatizer):
         rules = rules_table.get(univ_pos, [])
         string = string.lower()
         forms = []
+        # first try lookup in table based on upos
         if string in index:
             forms.append(string)
             self.cache[cache_key] = forms
             return forms
+
+        # then add anything in the exceptions table
         forms.extend(exceptions.get(string, []))
+
+        # if nothing found yet, use the rules
         oov_forms = []
         if not forms:
             for old, new in rules:
@@ -69,12 +74,14 @@ class FrenchLemmatizer(Lemmatizer):
                         forms.append(form)
                     else:
                         oov_forms.append(form)
+
+        # if still nothing, add the oov forms from rules
         if not forms:
             forms.extend(oov_forms)
-        if not forms and string in lookup_table.keys():
-            forms.append(self.lookup_lemmatize(token)[0])
+
+        # use lookups, which fall back to the token itself
         if not forms:
-            forms.append(string)
+            forms.append(lookup_table.get(string, [string])[0])
         forms = list(dict.fromkeys(forms))
         self.cache[cache_key] = forms
         return forms

From 5ae63b1fbd549fdfc0f7399c0b9656d4a6681544 Mon Sep 17 00:00:00 2001
From: "Patrick J. Burns" <diyclassics@users.noreply.github.com>
Date: Tue, 30 Aug 2022 08:04:54 -0400
Subject: [PATCH 075/174] Add Latin language support (#11349)

* Add lang folder for la (Latin)

* Add Latin lang classes

* Add minimal tokenizer exceptions

* Add minimal stopwords

* Add minimal lex_attrs

* Update stopwords, tokenizer exceptions

* Add la tests; register la_tokenizer in conftest.py

* Update spacy/lang/la/lex_attrs.py

Remove duplicate form in Latin lex_attrs

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Update natto-py version spec (#11222)

* Update natto-py version spec

* Update setup.cfg

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

* Add scorer to textcat API docs config settings (#11263)

* Update docs for pipeline initialize() methods (#11221)

* Update documentation for dependency parser

* Update documentation for trainable_lemmatizer

* Update documentation for entity_linker

* Update documentation for ner

* Update documentation for morphologizer

* Update documentation for senter

* Update documentation for spancat

* Update documentation for tagger

* Update documentation for textcat

* Update documentation for tok2vec

* Run prettier on edited files

* Apply similar changes in transformer docs

* Remove need to say annotated example explicitly

I removed the need to say "Must contain at least one annotated Example"
because it's often a given that Examples will contain some gold-standard
annotation.

* Run prettier on transformer docs

* chore: add 'concepCy' to spacy universe (#11255)

* chore: add 'concepCy' to spacy universe

* docs: add 'slogan' to concepCy

* Support full prerelease versions in the compat table (#11228)

* Support full prerelease versions in the compat table

* Fix types

* adding spans to doc_annotation in Example.to_dict (#11261)

* adding spans to doc_annotation in Example.to_dict

* to_dict compatible with from_dict: tuples instead of spans

* use strings for label and kb_id

* Simplify test

* Update data formats docs

Co-authored-by: Stefanie Wolf <stefanie.wolf@vitecsoftware.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

* Fix regex invalid escape sequences (#11276)

* Add W605 to the errors raised by flake8 in the CI (#11283)

* Clean up automated label-based issue handling (#11284)

* Clean up automated label-based issue handline

1. upgrade tiangolo/issue-manager to latest
2. move needs-more-info to tiangolo
3. change needs-more-info close time to 7 days
4. delete old needs-more-info config

* Use old, longer message

* Fix label name

* Fix Dutch noun chunks to skip overlapping spans (#11275)

* Add test for overlapping noun chunks

* Skip overlapping noun chunks

* Update spacy/tests/lang/nl/test_noun_chunks.py

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Docs: displaCy documentation - data types, `parse_{deps,ents,spans}`, spans example (#10950)

* add in spans example and parse references

* rm autoformatter

* rm extra ents copy

* TypedDict draft

* type fixes

* restore non-documentation files

* docs update

* fix spans example

* fix hyperlinks

* add parse example

* example fix + argument fix

* fix api arg in docs

* fix bad variable replacement

* fix spacing in style

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* fix spacing on table

* fix spacing on table

* rm temp files

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* include span_ruler for default warning filter (#11333)

* Add uk pipelines to website (#11332)

* Check for . in factory names (#11336)

* Make fixes for PR #11349

* Fix roman numeral coverage in #11349

Co-authored-by: Patrick J. Burns <patricks@diyclassics.org>
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
Co-authored-by: Lj Miranda <12949683+ljvmiranda921@users.noreply.github.com>
Co-authored-by: Jules Belveze <32683010+JulesBelveze@users.noreply.github.com>
Co-authored-by: stefawolf <wlf.ste@gmail.com>
Co-authored-by: Stefanie Wolf <stefanie.wolf@vitecsoftware.com>
Co-authored-by: Peter Baumgartner <5107405+pmbaumgartner@users.noreply.github.com>
---
 spacy/lang/la/__init__.py             | 18 +++++++++++++
 spacy/lang/la/lex_attrs.py            | 32 +++++++++++++++++++++++
 spacy/lang/la/stop_words.py           | 37 +++++++++++++++++++++++++++
 spacy/lang/la/tokenizer_exceptions.py | 30 ++++++++++++++++++++++
 spacy/tests/conftest.py               |  5 ++++
 spacy/tests/lang/la/__init__.py       |  0
 spacy/tests/lang/la/test_exception.py |  7 +++++
 spacy/tests/lang/la/test_text.py      | 33 ++++++++++++++++++++++++
 website/docs/api/top-level.md         |  2 +-
 9 files changed, 163 insertions(+), 1 deletion(-)
 create mode 100644 spacy/lang/la/__init__.py
 create mode 100644 spacy/lang/la/lex_attrs.py
 create mode 100644 spacy/lang/la/stop_words.py
 create mode 100644 spacy/lang/la/tokenizer_exceptions.py
 create mode 100644 spacy/tests/lang/la/__init__.py
 create mode 100644 spacy/tests/lang/la/test_exception.py
 create mode 100644 spacy/tests/lang/la/test_text.py

diff --git a/spacy/lang/la/__init__.py b/spacy/lang/la/__init__.py
new file mode 100644
index 000000000..5f2cccee3
--- /dev/null
+++ b/spacy/lang/la/__init__.py
@@ -0,0 +1,18 @@
+from ...language import Language, BaseDefaults
+from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
+from .stop_words import STOP_WORDS
+from .lex_attrs import LEX_ATTRS
+
+
+class LatinDefaults(BaseDefaults):
+    tokenizer_exceptions = TOKENIZER_EXCEPTIONS
+    stop_words = STOP_WORDS    
+    lex_attr_getters = LEX_ATTRS
+
+
+class Latin(Language):
+    lang = "la"
+    Defaults = LatinDefaults
+
+
+__all__ = ["Latin"]
diff --git a/spacy/lang/la/lex_attrs.py b/spacy/lang/la/lex_attrs.py
new file mode 100644
index 000000000..9348a811a
--- /dev/null
+++ b/spacy/lang/la/lex_attrs.py
@@ -0,0 +1,32 @@
+from ...attrs import LIKE_NUM
+import re
+
+# cf. Goyvaerts/Levithan 2009; case-insensitive, allow 4
+roman_numerals_compile = re.compile(r'(?i)^(?=[MDCLXVI])M*(C[MD]|D?C{0,4})(X[CL]|L?X{0,4})(I[XV]|V?I{0,4})$')
+
+_num_words = set(
+    """
+unus una unum duo duae tres tria quattuor quinque sex septem octo novem decem
+""".split()
+)
+
+_ordinal_words = set(
+    """
+primus prima primum secundus secunda secundum tertius tertia tertium
+""".split()
+)
+
+
+def like_num(text):
+    if text.isdigit():
+        return True
+    if roman_numerals_compile.match(text):
+        return True
+    if text.lower() in _num_words:
+        return True
+    if text.lower() in _ordinal_words:
+        return True
+    return False
+
+
+LEX_ATTRS = {LIKE_NUM: like_num}
diff --git a/spacy/lang/la/stop_words.py b/spacy/lang/la/stop_words.py
new file mode 100644
index 000000000..8b590bb67
--- /dev/null
+++ b/spacy/lang/la/stop_words.py
@@ -0,0 +1,37 @@
+# Corrected Perseus list, cf. https://wiki.digitalclassicist.org/Stopwords_for_Greek_and_Latin
+
+STOP_WORDS = set(
+    """
+ab ac ad adhuc aliqui aliquis an ante apud at atque aut autem 
+
+cum cur 
+
+de deinde dum 
+
+ego enim ergo es est et etiam etsi ex 
+
+fio 
+
+haud hic 
+
+iam idem igitur ille in infra inter interim ipse is ita 
+
+magis modo mox 
+
+nam ne nec necque neque nisi non nos 
+
+o ob 
+
+per possum post pro 
+
+quae quam quare qui quia quicumque quidem quilibet quis quisnam quisquam quisque quisquis quo quoniam 
+
+sed si sic sive sub sui sum super suus 
+
+tam tamen trans tu tum 
+
+ubi uel uero
+
+vel vero
+""".split()
+)
diff --git a/spacy/lang/la/tokenizer_exceptions.py b/spacy/lang/la/tokenizer_exceptions.py
new file mode 100644
index 000000000..905304188
--- /dev/null
+++ b/spacy/lang/la/tokenizer_exceptions.py
@@ -0,0 +1,30 @@
+from ..tokenizer_exceptions import BASE_EXCEPTIONS
+from ...symbols import ORTH
+from ...util import update_exc
+
+
+## TODO: Look into systematically handling u/v
+_exc = {
+    "mecum": [{ORTH: "me"}, {ORTH: "cum"}],
+    "tecum": [{ORTH: "te"}, {ORTH: "cum"}],
+    "nobiscum": [{ORTH: "nobis"}, {ORTH: "cum"}],
+    "vobiscum": [{ORTH: "vobis"}, {ORTH: "cum"}],
+    "uobiscum": [{ORTH: "uobis"}, {ORTH: "cum"}],    
+}
+
+for orth in [
+
+    'A.', 'Agr.', 'Ap.', 'C.', 'Cn.', 'D.', 'F.', 'K.', 'L.', "M'.", 'M.', 'Mam.', 'N.', 'Oct.', 
+    'Opet.', 'P.', 'Paul.', 'Post.', 'Pro.', 'Q.', 'S.', 'Ser.', 'Sert.', 'Sex.', 'St.', 'Sta.', 
+    'T.', 'Ti.', 'V.', 'Vol.', 'Vop.', 'U.', 'Uol.', 'Uop.',
+
+    'Ian.', 'Febr.', 'Mart.', 'Apr.', 'Mai.', 'Iun.', 'Iul.', 'Aug.', 'Sept.', 'Oct.', 'Nov.', 'Nou.', 
+    'Dec.',
+    
+    'Non.', 'Id.', 'A.D.', 
+
+    'Coll.', 'Cos.', 'Ord.', 'Pl.', 'S.C.', 'Suff.', 'Trib.',
+]:
+    _exc[orth] = [{ORTH: orth}]
+
+TOKENIZER_EXCEPTIONS = update_exc(BASE_EXCEPTIONS, _exc)
diff --git a/spacy/tests/conftest.py b/spacy/tests/conftest.py
index 5193bd301..0395ba7ca 100644
--- a/spacy/tests/conftest.py
+++ b/spacy/tests/conftest.py
@@ -256,6 +256,11 @@ def ko_tokenizer_tokenizer():
     return nlp.tokenizer
 
 
+@pytest.fixture(scope="module")
+def la_tokenizer():
+    return get_lang_class("la")().tokenizer    
+
+
 @pytest.fixture(scope="session")
 def lb_tokenizer():
     return get_lang_class("lb")().tokenizer
diff --git a/spacy/tests/lang/la/__init__.py b/spacy/tests/lang/la/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/spacy/tests/lang/la/test_exception.py b/spacy/tests/lang/la/test_exception.py
new file mode 100644
index 000000000..04bc1d489
--- /dev/null
+++ b/spacy/tests/lang/la/test_exception.py
@@ -0,0 +1,7 @@
+import pytest
+
+def test_la_tokenizer_handles_exc_in_text(la_tokenizer):
+    text = "scio te omnia facturum, ut nobiscum quam primum sis"
+    tokens = la_tokenizer(text)
+    assert len(tokens) == 11
+    assert tokens[6].text == "nobis"
diff --git a/spacy/tests/lang/la/test_text.py b/spacy/tests/lang/la/test_text.py
new file mode 100644
index 000000000..11676b92b
--- /dev/null
+++ b/spacy/tests/lang/la/test_text.py
@@ -0,0 +1,33 @@
+import pytest
+from spacy.lang.la.lex_attrs import like_num
+
+@pytest.mark.parametrize(
+    "text,match",
+    [
+        ("IIII", True),
+        ("VI", True),
+        ("vi", True),
+        ("IV", True),
+        ("iv", True),
+        ("IX", True),
+        ("ix", True),
+        ("MMXXII", True),
+        ("0", True),
+        ("1", True),        
+        ("quattuor", True),
+        ("decem", True),
+        ("tertius", True),
+        ("canis", False),
+        ("MMXX11", False),
+        (",", False),
+    ],
+)
+def test_lex_attrs_like_number(la_tokenizer, text, match):
+    tokens = la_tokenizer(text)
+    assert len(tokens) == 1
+    assert tokens[0].like_num == match
+
+@pytest.mark.parametrize("word", ["quinque"])
+def test_la_lex_attrs_capitals(word):
+    assert like_num(word)
+    assert like_num(word.upper())
diff --git a/website/docs/api/top-level.md b/website/docs/api/top-level.md
index c3dc42f1a..724f2775e 100644
--- a/website/docs/api/top-level.md
+++ b/website/docs/api/top-level.md
@@ -451,7 +451,7 @@ factories.
 | Registry name     | Description                                                                                                                                                                                                                                        |
 | ----------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
 | `architectures`   | Registry for functions that create [model architectures](/api/architectures). Can be used to register custom model architectures and reference them in the `config.cfg`.                                                                           |
-| `augmenters`      | Registry for functions that create [data augmentation](#augmenters) callbacks for corpora and other training data iterators.                                                                                                                       |
+| `augmenters`      | Registry for functions that create [data augmentation](#augmenters) callbacks for corpora and other training data iterators.                                                                                                                       |
 | `batchers`        | Registry for training and evaluation [data batchers](#batchers).                                                                                                                                                                                   |
 | `callbacks`       | Registry for custom callbacks to [modify the `nlp` object](/usage/training#custom-code-nlp-callbacks) before training.                                                                                                                             |
 | `displacy_colors` | Registry for custom color scheme for the [`displacy` NER visualizer](/usage/visualizers). Automatically reads from [entry points](/usage/saving-loading#entry-points).                                                                             |

From 3f4b4b7b4fa2df6c5d888cdc97efb71093d3fb6b Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Dani=C3=ABl=20de=20Kok?= <me@danieldk.eu>
Date: Tue, 30 Aug 2022 14:21:02 +0200
Subject: [PATCH 076/174] Fix `test_{prefer,require}_gpu` (#11390)

* Fix `test_{prefer,require}_gpu`

These tests assumed that GPUs are only supported with CuPy, but since Thinc 8.1
we also support Metal Performance Shaders.

* test_misc: arrange thinc imports to be together
---
 spacy/tests/test_misc.py | 25 ++++++++++++-------------
 1 file changed, 12 insertions(+), 13 deletions(-)

diff --git a/spacy/tests/test_misc.py b/spacy/tests/test_misc.py
index d8743d322..1c9b045ac 100644
--- a/spacy/tests/test_misc.py
+++ b/spacy/tests/test_misc.py
@@ -10,7 +10,8 @@ from spacy.ml._precomputable_affine import _backprop_precomputable_affine_paddin
 from spacy.util import dot_to_object, SimpleFrozenList, import_file
 from spacy.util import to_ternary_int
 from thinc.api import Config, Optimizer, ConfigValidationError
-from thinc.api import set_current_ops
+from thinc.api import get_current_ops, set_current_ops, NumpyOps, CupyOps, MPSOps
+from thinc.compat import has_cupy_gpu, has_torch_mps_gpu
 from spacy.training.batchers import minibatch_by_words
 from spacy.lang.en import English
 from spacy.lang.nl import Dutch
@@ -18,7 +19,6 @@ from spacy.language import DEFAULT_CONFIG_PATH
 from spacy.schemas import ConfigSchemaTraining, TokenPattern, TokenPatternSchema
 from pydantic import ValidationError
 
-from thinc.api import get_current_ops, NumpyOps, CupyOps
 
 from .util import get_random_doc, make_tempdir
 
@@ -111,26 +111,25 @@ def test_PrecomputableAffine(nO=4, nI=5, nF=3, nP=2):
 
 def test_prefer_gpu():
     current_ops = get_current_ops()
-    try:
-        import cupy  # noqa: F401
-
-        prefer_gpu()
+    if has_cupy_gpu:
+        assert prefer_gpu()
         assert isinstance(get_current_ops(), CupyOps)
-    except ImportError:
+    elif has_torch_mps_gpu:
+        assert prefer_gpu()
+        assert isinstance(get_current_ops(), MPSOps)
+    else:
         assert not prefer_gpu()
     set_current_ops(current_ops)
 
 
 def test_require_gpu():
     current_ops = get_current_ops()
-    try:
-        import cupy  # noqa: F401
-
+    if has_cupy_gpu:
         require_gpu()
         assert isinstance(get_current_ops(), CupyOps)
-    except ImportError:
-        with pytest.raises(ValueError):
-            require_gpu()
+    elif has_torch_mps_gpu:
+        require_gpu()
+        assert isinstance(get_current_ops(), MPSOps)
     set_current_ops(current_ops)
 
 

From 8fc0efc502da2f02076575e0887cb585d0e0f391 Mon Sep 17 00:00:00 2001
From: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Date: Wed, 31 Aug 2022 09:02:34 +0200
Subject: [PATCH 077/174] Allow string argument for disable/enable/exclude
 (#11406)

* adding unit test for spacy.load with disable/exclude string arg

* allow pure strings in from_config

* update docs

* upstream type adjustements

* docs update

* make docstring more consistent

* Update spacy/language.py

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

* two more cleanups

* fix type in internal method

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
---
 spacy/__init__.py                         | 12 ++---
 spacy/language.py                         | 32 +++++++-----
 spacy/tests/pipeline/test_pipe_methods.py | 11 +++++
 spacy/util.py                             | 60 +++++++++++------------
 website/docs/api/language.md              | 27 +++++-----
 website/docs/api/top-level.md             | 58 +++++++++++-----------
 6 files changed, 112 insertions(+), 88 deletions(-)

diff --git a/spacy/__init__.py b/spacy/__init__.py
index 069215fda..d60f46b96 100644
--- a/spacy/__init__.py
+++ b/spacy/__init__.py
@@ -31,21 +31,21 @@ def load(
     name: Union[str, Path],
     *,
     vocab: Union[Vocab, bool] = True,
-    disable: Iterable[str] = util.SimpleFrozenList(),
-    enable: Iterable[str] = util.SimpleFrozenList(),
-    exclude: Iterable[str] = util.SimpleFrozenList(),
+    disable: Union[str, Iterable[str]] = util.SimpleFrozenList(),
+    enable: Union[str, Iterable[str]] = util.SimpleFrozenList(),
+    exclude: Union[str, Iterable[str]] = util.SimpleFrozenList(),
     config: Union[Dict[str, Any], Config] = util.SimpleFrozenDict(),
 ) -> Language:
     """Load a spaCy model from an installed package or a local path.
 
     name (str): Package name or model path.
     vocab (Vocab): A Vocab object. If True, a vocab is created.
-    disable (Iterable[str]): Names of pipeline components to disable. Disabled
+    disable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to disable. Disabled
         pipes will be loaded but they won't be run unless you explicitly
         enable them by calling nlp.enable_pipe.
-    enable (Iterable[str]): Names of pipeline components to enable. All other
+    enable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to enable. All other
         pipes will be disabled (but can be enabled later using nlp.enable_pipe).
-    exclude (Iterable[str]): Names of pipeline components to exclude. Excluded
+    exclude (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to exclude. Excluded
         components won't be loaded.
     config (Dict[str, Any] / Config): Config overrides as nested dict or dict
         keyed by section values in dot notation.
diff --git a/spacy/language.py b/spacy/language.py
index e89ae142b..ec330753c 100644
--- a/spacy/language.py
+++ b/spacy/language.py
@@ -1063,7 +1063,7 @@ class Language:
         """
         if enable is None and disable is None:
             raise ValueError(Errors.E991)
-        if disable is not None and isinstance(disable, str):
+        if isinstance(disable, str):
             disable = [disable]
         if enable is not None:
             if isinstance(enable, str):
@@ -1698,9 +1698,9 @@ class Language:
         config: Union[Dict[str, Any], Config] = {},
         *,
         vocab: Union[Vocab, bool] = True,
-        disable: Iterable[str] = SimpleFrozenList(),
-        enable: Iterable[str] = SimpleFrozenList(),
-        exclude: Iterable[str] = SimpleFrozenList(),
+        disable: Union[str, Iterable[str]] = SimpleFrozenList(),
+        enable: Union[str, Iterable[str]] = SimpleFrozenList(),
+        exclude: Union[str, Iterable[str]] = SimpleFrozenList(),
         meta: Dict[str, Any] = SimpleFrozenDict(),
         auto_fill: bool = True,
         validate: bool = True,
@@ -1711,12 +1711,12 @@ class Language:
 
         config (Dict[str, Any] / Config): The loaded config.
         vocab (Vocab): A Vocab object. If True, a vocab is created.
-        disable (Iterable[str]): Names of pipeline components to disable.
+        disable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to disable.
             Disabled pipes will be loaded but they won't be run unless you
             explicitly enable them by calling nlp.enable_pipe.
-        enable (Iterable[str]): Names of pipeline components to enable. All other
+        enable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to enable. All other
             pipes will be disabled (and can be enabled using `nlp.enable_pipe`).
-        exclude (Iterable[str]): Names of pipeline components to exclude.
+        exclude (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to exclude.
             Excluded components won't be loaded.
         meta (Dict[str, Any]): Meta overrides for nlp.meta.
         auto_fill (bool): Automatically fill in missing values in config based
@@ -1727,6 +1727,12 @@ class Language:
 
         DOCS: https://spacy.io/api/language#from_config
         """
+        if isinstance(disable, str):
+            disable = [disable]
+        if isinstance(enable, str):
+            enable = [enable]
+        if isinstance(exclude, str):
+            exclude = [exclude]
         if auto_fill:
             config = Config(
                 cls.default_config, section_order=CONFIG_SECTION_ORDER
@@ -2031,25 +2037,29 @@ class Language:
 
     @staticmethod
     def _resolve_component_status(
-        disable: Iterable[str], enable: Iterable[str], pipe_names: Collection[str]
+        disable: Union[str, Iterable[str]],
+        enable: Union[str, Iterable[str]],
+        pipe_names: Iterable[str],
     ) -> Tuple[str, ...]:
         """Derives whether (1) `disable` and `enable` values are consistent and (2)
         resolves those to a single set of disabled components. Raises an error in
         case of inconsistency.
 
-        disable (Iterable[str]): Names of components or serialization fields to disable.
-        enable (Iterable[str]): Names of pipeline components to enable.
+        disable (Union[str, Iterable[str]]): Name(s) of component(s) or serialization fields to disable.
+        enable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to enable.
         pipe_names (Iterable[str]): Names of all pipeline components.
 
         RETURNS (Tuple[str, ...]): Names of components to exclude from pipeline w.r.t.
                                    specified includes and excludes.
         """
 
-        if disable is not None and isinstance(disable, str):
+        if isinstance(disable, str):
             disable = [disable]
         to_disable = disable
 
         if enable:
+            if isinstance(enable, str):
+                enable = [enable]
             to_disable = [
                 pipe_name for pipe_name in pipe_names if pipe_name not in enable
             ]
diff --git a/spacy/tests/pipeline/test_pipe_methods.py b/spacy/tests/pipeline/test_pipe_methods.py
index 6f00a1cd9..b946061f6 100644
--- a/spacy/tests/pipeline/test_pipe_methods.py
+++ b/spacy/tests/pipeline/test_pipe_methods.py
@@ -618,6 +618,7 @@ def test_load_disable_enable() -> None:
         base_nlp.to_disk(tmp_dir)
         to_disable = ["parser", "tagger"]
         to_enable = ["tagger", "parser"]
+        single_str = "tagger"
 
         # Setting only `disable`.
         nlp = spacy.load(tmp_dir, disable=to_disable)
@@ -632,6 +633,16 @@ def test_load_disable_enable() -> None:
             ]
         )
 
+        # Loading with a string representing one component
+        nlp = spacy.load(tmp_dir, exclude=single_str)
+        assert single_str not in nlp.component_names
+
+        nlp = spacy.load(tmp_dir, disable=single_str)
+        assert single_str in nlp.component_names
+        assert single_str not in nlp.pipe_names
+        assert nlp._disabled == {single_str}
+        assert nlp.disabled == [single_str]
+
         # Testing consistent enable/disable combination.
         nlp = spacy.load(
             tmp_dir,
diff --git a/spacy/util.py b/spacy/util.py
index d170fc15b..4e1a62d05 100644
--- a/spacy/util.py
+++ b/spacy/util.py
@@ -398,9 +398,9 @@ def load_model(
     name: Union[str, Path],
     *,
     vocab: Union["Vocab", bool] = True,
-    disable: Iterable[str] = SimpleFrozenList(),
-    enable: Iterable[str] = SimpleFrozenList(),
-    exclude: Iterable[str] = SimpleFrozenList(),
+    disable: Union[str, Iterable[str]] = SimpleFrozenList(),
+    enable: Union[str, Iterable[str]] = SimpleFrozenList(),
+    exclude: Union[str, Iterable[str]] = SimpleFrozenList(),
     config: Union[Dict[str, Any], Config] = SimpleFrozenDict(),
 ) -> "Language":
     """Load a model from a package or data path.
@@ -408,9 +408,9 @@ def load_model(
     name (str): Package name or model path.
     vocab (Vocab / True): Optional vocab to pass in on initialization. If True,
         a new Vocab object will be created.
-    disable (Iterable[str]): Names of pipeline components to disable.
-    enable (Iterable[str]): Names of pipeline components to enable. All others will be disabled.
-    exclude (Iterable[str]):  Names of pipeline components to exclude.
+    disable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to disable.
+    enable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to enable. All others will be disabled.
+    exclude (Union[str, Iterable[str]]):  Name(s) of pipeline component(s) to exclude.
     config (Dict[str, Any] / Config): Config overrides as nested dict or dict
         keyed by section values in dot notation.
     RETURNS (Language): The loaded nlp object.
@@ -440,9 +440,9 @@ def load_model_from_package(
     name: str,
     *,
     vocab: Union["Vocab", bool] = True,
-    disable: Iterable[str] = SimpleFrozenList(),
-    enable: Iterable[str] = SimpleFrozenList(),
-    exclude: Iterable[str] = SimpleFrozenList(),
+    disable: Union[str, Iterable[str]] = SimpleFrozenList(),
+    enable: Union[str, Iterable[str]] = SimpleFrozenList(),
+    exclude: Union[str, Iterable[str]] = SimpleFrozenList(),
     config: Union[Dict[str, Any], Config] = SimpleFrozenDict(),
 ) -> "Language":
     """Load a model from an installed package.
@@ -450,12 +450,12 @@ def load_model_from_package(
     name (str): The package name.
     vocab (Vocab / True): Optional vocab to pass in on initialization. If True,
         a new Vocab object will be created.
-    disable (Iterable[str]): Names of pipeline components to disable. Disabled
+    disable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to disable. Disabled
         pipes will be loaded but they won't be run unless you explicitly
         enable them by calling nlp.enable_pipe.
-    enable (Iterable[str]): Names of pipeline components to enable. All other
+    enable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to enable. All other
         pipes will be disabled (and can be enabled using `nlp.enable_pipe`).
-    exclude (Iterable[str]): Names of pipeline components to exclude. Excluded
+    exclude (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to exclude. Excluded
         components won't be loaded.
     config (Dict[str, Any] / Config): Config overrides as nested dict or dict
         keyed by section values in dot notation.
@@ -470,9 +470,9 @@ def load_model_from_path(
     *,
     meta: Optional[Dict[str, Any]] = None,
     vocab: Union["Vocab", bool] = True,
-    disable: Iterable[str] = SimpleFrozenList(),
-    enable: Iterable[str] = SimpleFrozenList(),
-    exclude: Iterable[str] = SimpleFrozenList(),
+    disable: Union[str, Iterable[str]] = SimpleFrozenList(),
+    enable: Union[str, Iterable[str]] = SimpleFrozenList(),
+    exclude: Union[str, Iterable[str]] = SimpleFrozenList(),
     config: Union[Dict[str, Any], Config] = SimpleFrozenDict(),
 ) -> "Language":
     """Load a model from a data directory path. Creates Language class with
@@ -482,12 +482,12 @@ def load_model_from_path(
     meta (Dict[str, Any]): Optional model meta.
     vocab (Vocab / True): Optional vocab to pass in on initialization. If True,
         a new Vocab object will be created.
-    disable (Iterable[str]): Names of pipeline components to disable. Disabled
+    disable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to disable. Disabled
         pipes will be loaded but they won't be run unless you explicitly
         enable them by calling nlp.enable_pipe.
-    enable (Iterable[str]): Names of pipeline components to enable. All other
+    enable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to enable. All other
         pipes will be disabled (and can be enabled using `nlp.enable_pipe`).
-    exclude (Iterable[str]): Names of pipeline components to exclude. Excluded
+    exclude (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to exclude. Excluded
         components won't be loaded.
     config (Dict[str, Any] / Config): Config overrides as nested dict or dict
         keyed by section values in dot notation.
@@ -516,9 +516,9 @@ def load_model_from_config(
     *,
     meta: Dict[str, Any] = SimpleFrozenDict(),
     vocab: Union["Vocab", bool] = True,
-    disable: Iterable[str] = SimpleFrozenList(),
-    enable: Iterable[str] = SimpleFrozenList(),
-    exclude: Iterable[str] = SimpleFrozenList(),
+    disable: Union[str, Iterable[str]] = SimpleFrozenList(),
+    enable: Union[str, Iterable[str]] = SimpleFrozenList(),
+    exclude: Union[str, Iterable[str]] = SimpleFrozenList(),
     auto_fill: bool = False,
     validate: bool = True,
 ) -> "Language":
@@ -529,12 +529,12 @@ def load_model_from_config(
     meta (Dict[str, Any]): Optional model meta.
     vocab (Vocab / True): Optional vocab to pass in on initialization. If True,
         a new Vocab object will be created.
-    disable (Iterable[str]): Names of pipeline components to disable. Disabled
+    disable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to disable. Disabled
         pipes will be loaded but they won't be run unless you explicitly
         enable them by calling nlp.enable_pipe.
-    enable (Iterable[str]): Names of pipeline components to enable. All other
+    enable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to enable. All other
         pipes will be disabled (and can be enabled using `nlp.enable_pipe`).
-    exclude (Iterable[str]): Names of pipeline components to exclude. Excluded
+    exclude (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to exclude. Excluded
         components won't be loaded.
     auto_fill (bool): Whether to auto-fill config with missing defaults.
     validate (bool): Whether to show config validation errors.
@@ -616,9 +616,9 @@ def load_model_from_init_py(
     init_file: Union[Path, str],
     *,
     vocab: Union["Vocab", bool] = True,
-    disable: Iterable[str] = SimpleFrozenList(),
-    enable: Iterable[str] = SimpleFrozenList(),
-    exclude: Iterable[str] = SimpleFrozenList(),
+    disable: Union[str, Iterable[str]] = SimpleFrozenList(),
+    enable: Union[str, Iterable[str]] = SimpleFrozenList(),
+    exclude: Union[str, Iterable[str]] = SimpleFrozenList(),
     config: Union[Dict[str, Any], Config] = SimpleFrozenDict(),
 ) -> "Language":
     """Helper function to use in the `load()` method of a model package's
@@ -626,12 +626,12 @@ def load_model_from_init_py(
 
     vocab (Vocab / True): Optional vocab to pass in on initialization. If True,
         a new Vocab object will be created.
-    disable (Iterable[str]): Names of pipeline components to disable. Disabled
+    disable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to disable. Disabled
         pipes will be loaded but they won't be run unless you explicitly
         enable them by calling nlp.enable_pipe.
-    enable (Iterable[str]): Names of pipeline components to enable. All other
+    enable (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to enable. All other
         pipes will be disabled (and can be enabled using `nlp.enable_pipe`).
-    exclude (Iterable[str]): Names of pipeline components to exclude. Excluded
+    exclude (Union[str, Iterable[str]]): Name(s) of pipeline component(s) to exclude. Excluded
         components won't be loaded.
     config (Dict[str, Any] / Config): Config overrides as nested dict or dict
         keyed by section values in dot notation.
diff --git a/website/docs/api/language.md b/website/docs/api/language.md
index 9a413efaf..ed763e36a 100644
--- a/website/docs/api/language.md
+++ b/website/docs/api/language.md
@@ -63,17 +63,18 @@ spaCy loads a model under the hood based on its
 > nlp = Language.from_config(config)
 > ```
 
-| Name           | Description                                                                                                                                                                                                                                      |
-| -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
-| `config`       | The loaded config. ~~Union[Dict[str, Any], Config]~~                                                                                                                                                                                             |
-| _keyword-only_ |                                                                                                                                                                                                                                                  |
-| `vocab`        | A `Vocab` object. If `True`, a vocab is created using the default language data settings. ~~Vocab~~                                                                                                                                              |
-| `disable`      | Names of pipeline components to [disable](/usage/processing-pipelines#disabling). Disabled pipes will be loaded but they won't be run unless you explicitly enable them by calling [`nlp.enable_pipe`](/api/language#enable_pipe). ~~List[str]~~ |
-| `exclude`      | Names of pipeline components to [exclude](/usage/processing-pipelines#disabling). Excluded components won't be loaded. ~~List[str]~~                                                                                                             |
-| `meta`         | [Meta data](/api/data-formats#meta) overrides. ~~Dict[str, Any]~~                                                                                                                                                                                |
-| `auto_fill`    | Whether to automatically fill in missing values in the config, based on defaults and function argument annotations. Defaults to `True`. ~~bool~~                                                                                                 |
-| `validate`     | Whether to validate the component config and arguments against the types expected by the factory. Defaults to `True`. ~~bool~~                                                                                                                   |
-| **RETURNS**    | The initialized object. ~~Language~~                                                                                                                                                                                                             |
+| Name                                  | Description                                                                                                                                                                                                                                                          |
+| ------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `config`                              | The loaded config. ~~Union[Dict[str, Any], Config]~~                                                                                                                                                                                                                 |
+| _keyword-only_                        |                                                                                                                                                                                                                                                                      |
+| `vocab`                               | A `Vocab` object. If `True`, a vocab is created using the default language data settings. ~~Vocab~~                                                                                                                                                                  |
+| `disable`                             | Name(s) of pipeline component(s) to [disable](/usage/processing-pipelines#disabling). Disabled pipes will be loaded but they won't be run unless you explicitly enable them by calling [`nlp.enable_pipe`](/api/language#enable_pipe). ~~Union[str, Iterable[str]]~~ |
+| `enable` <Tag variant="new">3.4</Tag> | Name(s) of pipeline component(s) to [enable](/usage/processing-pipelines#disabling). All other pipes will be disabled, but can be enabled again using [`nlp.enable_pipe`](/api/language#enable_pipe). ~~Union[str, Iterable[str]]~~                                  |
+| `exclude`                             | Name(s) of pipeline component(s) to [exclude](/usage/processing-pipelines#disabling). Excluded components won't be loaded. ~~Union[str, Iterable[str]]~~                                                                                                             |
+| `meta`                                | [Meta data](/api/data-formats#meta) overrides. ~~Dict[str, Any]~~                                                                                                                                                                                                    |
+| `auto_fill`                           | Whether to automatically fill in missing values in the config, based on defaults and function argument annotations. Defaults to `True`. ~~bool~~                                                                                                                     |
+| `validate`                            | Whether to validate the component config and arguments against the types expected by the factory. Defaults to `True`. ~~bool~~                                                                                                                                       |
+| **RETURNS**                           | The initialized object. ~~Language~~                                                                                                                                                                                                                                 |
 
 ## Language.component {#component tag="classmethod" new="3"}
 
@@ -695,8 +696,8 @@ As of spaCy v3.0, the `disable_pipes` method has been renamed to `select_pipes`:
 | Name           | Description                                                                                            |
 | -------------- | ------------------------------------------------------------------------------------------------------ |
 | _keyword-only_ |                                                                                                        |
-| `disable`      | Name(s) of pipeline components to disable. ~~Optional[Union[str, Iterable[str]]]~~                     |
-| `enable`       | Name(s) of pipeline components that will not be disabled. ~~Optional[Union[str, Iterable[str]]]~~      |
+| `disable`      | Name(s) of pipeline component(s) to disable. ~~Optional[Union[str, Iterable[str]]]~~                   |
+| `enable`       | Name(s) of pipeline component(s) that will not be disabled. ~~Optional[Union[str, Iterable[str]]]~~    |
 | **RETURNS**    | The disabled pipes that can be restored by calling the object's `.restore()` method. ~~DisabledPipes~~ |
 
 ## Language.get_factory_meta {#get_factory_meta tag="classmethod" new="3"}
diff --git a/website/docs/api/top-level.md b/website/docs/api/top-level.md
index 724f2775e..220b2d6e9 100644
--- a/website/docs/api/top-level.md
+++ b/website/docs/api/top-level.md
@@ -45,16 +45,16 @@ specified separately using the new `exclude` keyword argument.
 > nlp = spacy.load("en_core_web_sm", exclude=["parser", "tagger"])
 > ```
 
-| Name                                 | Description                                                                                                                                                                                                                                    |
-| ------------------------------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `name`                               | Pipeline to load, i.e. package name or path. ~~Union[str, Path]~~                                                                                                                                                                              |
-| _keyword-only_                       |                                                                                                                                                                                                                                                |
-| `vocab`                              | Optional shared vocab to pass in on initialization. If `True` (default), a new `Vocab` object will be created. ~~Union[Vocab, bool]~~                                                                                                          |
-| `disable`                            | Names of pipeline components to [disable](/usage/processing-pipelines#disabling). Disabled pipes will be loaded but they won't be run unless you explicitly enable them by calling [nlp.enable_pipe](/api/language#enable_pipe). ~~List[str]~~ |
-| `enable`                             | Names of pipeline components to [enable](/usage/processing-pipelines#disabling). All other pipes will be disabled. ~~List[str]~~                                                                                                               |
-| `exclude` <Tag variant="new">3</Tag> | Names of pipeline components to [exclude](/usage/processing-pipelines#disabling). Excluded components won't be loaded. ~~List[str]~~                                                                                                           |
-| `config` <Tag variant="new">3</Tag>  | Optional config overrides, either as nested dict or dict keyed by section value in dot notation, e.g. `"components.name.value"`. ~~Union[Dict[str, Any], Config]~~                                                                             |
-| **RETURNS**                          | A `Language` object with the loaded pipeline. ~~Language~~                                                                                                                                                                                     |
+| Name                                  | Description                                                                                                                                                                                                                                                        |
+| ------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
+| `name`                                | Pipeline to load, i.e. package name or path. ~~Union[str, Path]~~                                                                                                                                                                                                  |
+| _keyword-only_                        |                                                                                                                                                                                                                                                                    |
+| `vocab`                               | Optional shared vocab to pass in on initialization. If `True` (default), a new `Vocab` object will be created. ~~Union[Vocab, bool]~~                                                                                                                              |
+| `disable`                             | Name(s) of pipeline component(s) to [disable](/usage/processing-pipelines#disabling). Disabled pipes will be loaded but they won't be run unless you explicitly enable them by calling [nlp.enable_pipe](/api/language#enable_pipe). ~~Union[str, Iterable[str]]~~ |
+| `enable` <Tag variant="new">3.4</Tag> | Name(s) of pipeline component(s) to [enable](/usage/processing-pipelines#disabling). All other pipes will be disabled. ~~Union[str, Iterable[str]]~~                                                                                                               |
+| `exclude` <Tag variant="new">3</Tag>  | Name(s) of pipeline component(s) to [exclude](/usage/processing-pipelines#disabling). Excluded components won't be loaded. ~~Union[str, Iterable[str]]~~                                                                                                           |
+| `config` <Tag variant="new">3</Tag>   | Optional config overrides, either as nested dict or dict keyed by section value in dot notation, e.g. `"components.name.value"`. ~~Union[Dict[str, Any], Config]~~                                                                                                 |
+| **RETURNS**                           | A `Language` object with the loaded pipeline. ~~Language~~                                                                                                                                                                                                         |
 
 Essentially, `spacy.load()` is a convenience wrapper that reads the pipeline's
 [`config.cfg`](/api/data-formats#config), uses the language and pipeline
@@ -1049,15 +1049,16 @@ and create a `Language` object. The model data will then be loaded in via
 > nlp = util.load_model("/path/to/data")
 > ```
 
-| Name                                 | Description                                                                                                                                                                                                                                      |
-| ------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
-| `name`                               | Package name or path. ~~str~~                                                                                                                                                                                                                    |
-| _keyword-only_                       |                                                                                                                                                                                                                                                  |
-| `vocab`                              | Optional shared vocab to pass in on initialization. If `True` (default), a new `Vocab` object will be created. ~~Union[Vocab, bool]~~                                                                                                            |
-| `disable`                            | Names of pipeline components to [disable](/usage/processing-pipelines#disabling). Disabled pipes will be loaded but they won't be run unless you explicitly enable them by calling [`nlp.enable_pipe`](/api/language#enable_pipe). ~~List[str]~~ |
-| `exclude` <Tag variant="new">3</Tag> | Names of pipeline components to [exclude](/usage/processing-pipelines#disabling). Excluded components won't be loaded. ~~List[str]~~                                                                                                             |
-| `config` <Tag variant="new">3</Tag>  | Config overrides as nested dict or flat dict keyed by section values in dot notation, e.g. `"nlp.pipeline"`. ~~Union[Dict[str, Any], Config]~~                                                                                                   |
-| **RETURNS**                          | `Language` class with the loaded pipeline. ~~Language~~                                                                                                                                                                                          |
+| Name                                  | Description                                                                                                                                                                                                                                                          |
+| ------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `name`                                | Package name or path. ~~str~~                                                                                                                                                                                                                                        |
+| _keyword-only_                        |                                                                                                                                                                                                                                                                      |
+| `vocab`                               | Optional shared vocab to pass in on initialization. If `True` (default), a new `Vocab` object will be created. ~~Union[Vocab, bool]~~                                                                                                                                |
+| `disable`                             | Name(s) of pipeline component(s) to [disable](/usage/processing-pipelines#disabling). Disabled pipes will be loaded but they won't be run unless you explicitly enable them by calling [`nlp.enable_pipe`](/api/language#enable_pipe). ~~Union[str, Iterable[str]]~~ |
+| `enable` <Tag variant="new">3.4</Tag> | Name(s) of pipeline component(s) to [enable](/usage/processing-pipelines#disabling). All other pipes will be disabled, but can be enabled again using [`nlp.enable_pipe`](/api/language#enable_pipe). ~~Union[str, Iterable[str]]~~                                  |
+| `exclude`                             | Name(s) of pipeline component(s) to [exclude](/usage/processing-pipelines#disabling). Excluded components won't be loaded. ~~Union[str, Iterable[str]]~~                                                                                                             |
+| `config` <Tag variant="new">3</Tag>   | Config overrides as nested dict or flat dict keyed by section values in dot notation, e.g. `"nlp.pipeline"`. ~~Union[Dict[str, Any], Config]~~                                                                                                                       |
+| **RETURNS**                           | `Language` class with the loaded pipeline. ~~Language~~                                                                                                                                                                                                              |
 
 ### util.load_model_from_init_py {#util.load_model_from_init_py tag="function" new="2"}
 
@@ -1073,15 +1074,16 @@ A helper function to use in the `load()` method of a pipeline package's
 >     return load_model_from_init_py(__file__, **overrides)
 > ```
 
-| Name                                 | Description                                                                                                                                                                                                                                    |
-| ------------------------------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `init_file`                          | Path to package's `__init__.py`, i.e. `__file__`. ~~Union[str, Path]~~                                                                                                                                                                         |
-| _keyword-only_                       |                                                                                                                                                                                                                                                |
-| `vocab` <Tag variant="new">3</Tag>   | Optional shared vocab to pass in on initialization. If `True` (default), a new `Vocab` object will be created. ~~Union[Vocab, bool]~~                                                                                                          |
-| `disable`                            | Names of pipeline components to [disable](/usage/processing-pipelines#disabling). Disabled pipes will be loaded but they won't be run unless you explicitly enable them by calling [nlp.enable_pipe](/api/language#enable_pipe). ~~List[str]~~ |
-| `exclude` <Tag variant="new">3</Tag> | Names of pipeline components to [exclude](/usage/processing-pipelines#disabling). Excluded components won't be loaded. ~~List[str]~~                                                                                                           |
-| `config` <Tag variant="new">3</Tag>  | Config overrides as nested dict or flat dict keyed by section values in dot notation, e.g. `"nlp.pipeline"`. ~~Union[Dict[str, Any], Config]~~                                                                                                 |
-| **RETURNS**                          | `Language` class with the loaded pipeline. ~~Language~~                                                                                                                                                                                        |
+| Name                                  | Description                                                                                                                                                                                                                                                          |
+| ------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `init_file`                           | Path to package's `__init__.py`, i.e. `__file__`. ~~Union[str, Path]~~                                                                                                                                                                                               |
+| _keyword-only_                        |                                                                                                                                                                                                                                                                      |
+| `vocab` <Tag variant="new">3</Tag>    | Optional shared vocab to pass in on initialization. If `True` (default), a new `Vocab` object will be created. ~~Union[Vocab, bool]~~                                                                                                                                |
+| `disable`                             | Name(s) of pipeline component(s) to [disable](/usage/processing-pipelines#disabling). Disabled pipes will be loaded but they won't be run unless you explicitly enable them by calling [`nlp.enable_pipe`](/api/language#enable_pipe). ~~Union[str, Iterable[str]]~~ |
+| `enable` <Tag variant="new">3.4</Tag> | Name(s) of pipeline component(s) to [enable](/usage/processing-pipelines#disabling). All other pipes will be disabled, but can be enabled again using [`nlp.enable_pipe`](/api/language#enable_pipe). ~~Union[str, Iterable[str]]~~                                  |
+| `exclude` <Tag variant="new">3</Tag>  | Name(s) of pipeline component(s) to [exclude](/usage/processing-pipelines#disabling). Excluded components won't be loaded. ~~Union[str, Iterable[str]]~~                                                                                                             |
+| `config` <Tag variant="new">3</Tag>   | Config overrides as nested dict or flat dict keyed by section values in dot notation, e.g. `"nlp.pipeline"`. ~~Union[Dict[str, Any], Config]~~                                                                                                                       |
+| **RETURNS**                           | `Language` class with the loaded pipeline. ~~Language~~                                                                                                                                                                                                              |
 
 ### util.load_config {#util.load_config tag="function" new="3"}
 

From 604a7c3c26bcc6737a9676c3ba1b16c9ac705be3 Mon Sep 17 00:00:00 2001
From: Madeesh Kannan <shadeMe@users.noreply.github.com>
Date: Wed, 31 Aug 2022 09:03:20 +0200
Subject: [PATCH 078/174] `SpanGroup(s)`-related optimizations (#11380)

* `SpanGroup`: Add support for binding copies to a new reference document

* `SpanGroups`: Replace superfluous serialize-deserialize roundtrip in `copy`

Instead, directly copy the in-memory representations of the constituent `SpanGroup`s.

* Update `SpanGroup.copy()` signature

* Rename `new_doc` param to `doc`

* Fix kwdarg

* Update `.pyi` file and docstrings

* `mypy` fix

* Update spacy/tokens/span_group.pyx

* Update docs

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
---
 spacy/tokens/_dict_proxies.py | 3 ++-
 spacy/tokens/span_group.pyi   | 4 ++--
 spacy/tokens/span_group.pyx   | 7 +++++--
 website/docs/api/spangroup.md | 7 ++++---
 4 files changed, 13 insertions(+), 8 deletions(-)

diff --git a/spacy/tokens/_dict_proxies.py b/spacy/tokens/_dict_proxies.py
index 9630da261..6edcce13d 100644
--- a/spacy/tokens/_dict_proxies.py
+++ b/spacy/tokens/_dict_proxies.py
@@ -42,7 +42,8 @@ class SpanGroups(UserDict):
     def copy(self, doc: Optional["Doc"] = None) -> "SpanGroups":
         if doc is None:
             doc = self._ensure_doc()
-        return SpanGroups(doc).from_bytes(self.to_bytes())
+        data_copy = ((k, v.copy(doc=doc)) for k, v in self.items())
+        return SpanGroups(doc, items=data_copy)
 
     def setdefault(self, key, default=None):
         if not isinstance(default, SpanGroup):
diff --git a/spacy/tokens/span_group.pyi b/spacy/tokens/span_group.pyi
index 245eb4dbe..21cd124ab 100644
--- a/spacy/tokens/span_group.pyi
+++ b/spacy/tokens/span_group.pyi
@@ -1,4 +1,4 @@
-from typing import Any, Dict, Iterable
+from typing import Any, Dict, Iterable, Optional
 from .doc import Doc
 from .span import Span
 
@@ -24,4 +24,4 @@ class SpanGroup:
     def __getitem__(self, i: int) -> Span: ...
     def to_bytes(self) -> bytes: ...
     def from_bytes(self, bytes_data: bytes) -> SpanGroup: ...
-    def copy(self) -> SpanGroup: ...
+    def copy(self, doc: Optional[Doc] = ...) -> SpanGroup: ...
diff --git a/spacy/tokens/span_group.pyx b/spacy/tokens/span_group.pyx
index bb0fab24f..1aa3c0bc8 100644
--- a/spacy/tokens/span_group.pyx
+++ b/spacy/tokens/span_group.pyx
@@ -241,15 +241,18 @@ cdef class SpanGroup:
     cdef void push_back(self, SpanC span) nogil:
         self.c.push_back(span)
 
-    def copy(self)  -> SpanGroup:
+    def copy(self, doc: Optional["Doc"] = None) -> SpanGroup:
         """Clones the span group.
 
+        doc (Doc): New reference document to which the copy is bound.
         RETURNS (SpanGroup): A copy of the span group.
 
         DOCS: https://spacy.io/api/spangroup#copy
         """
+        if doc is None:
+            doc = self.doc
         return SpanGroup(
-            self.doc,
+            doc,
             name=self.name,
             attrs=deepcopy(self.attrs),
             spans=list(self),
diff --git a/website/docs/api/spangroup.md b/website/docs/api/spangroup.md
index 8dbdefc01..2d1cf73c4 100644
--- a/website/docs/api/spangroup.md
+++ b/website/docs/api/spangroup.md
@@ -255,9 +255,10 @@ Return a copy of the span group.
 > new_group = doc.spans["errors"].copy()
 > ```
 
-| Name        | Description                                     |
-| ----------- | ----------------------------------------------- |
-| **RETURNS** | A copy of the `SpanGroup` object. ~~SpanGroup~~ |
+| Name        | Description                                                                                        |
+| ----------- | -------------------------------------------------------------------------------------------------- |
+| `doc`       | The document to which the copy is bound. Defaults to `None` for the current doc. ~~Optional[Doc]~~ |
+| **RETURNS** | A copy of the `SpanGroup` object. ~~SpanGroup~~                                                    |
 
 ## SpanGroup.to_bytes {#to_bytes tag="method"}
 

From 78f5503a29b3ab27b860220499346b79d26e666b Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Thu, 1 Sep 2022 19:37:23 +0200
Subject: [PATCH 079/174] Check for any non-Doc returned value for components
 (#11424)

---
 spacy/errors.py              |  5 +++--
 spacy/language.py            |  4 ++--
 spacy/tests/test_language.py | 22 ++++++++++++++++++++++
 3 files changed, 27 insertions(+), 4 deletions(-)

diff --git a/spacy/errors.py b/spacy/errors.py
index 608305a06..5ee1476c2 100644
--- a/spacy/errors.py
+++ b/spacy/errors.py
@@ -230,8 +230,9 @@ class Errors(metaclass=ErrorsWithCodes):
             "initialized component.")
     E004 = ("Can't set up pipeline component: a factory for '{name}' already "
             "exists. Existing factory: {func}. New factory: {new_func}")
-    E005 = ("Pipeline component '{name}' returned None. If you're using a "
-            "custom component, maybe you forgot to return the processed Doc?")
+    E005 = ("Pipeline component '{name}' returned {returned_type} instead of a "
+            "Doc. If you're using a custom component, maybe you forgot to "
+            "return the processed Doc?")
     E006 = ("Invalid constraints for adding pipeline component. You can only "
             "set one of the following: before (component name or index), "
             "after (component name or index), first (True) or last (True). "
diff --git a/spacy/language.py b/spacy/language.py
index ec330753c..34a06e576 100644
--- a/spacy/language.py
+++ b/spacy/language.py
@@ -1028,8 +1028,8 @@ class Language:
                 raise ValueError(Errors.E109.format(name=name)) from e
             except Exception as e:
                 error_handler(name, proc, [doc], e)
-            if doc is None:
-                raise ValueError(Errors.E005.format(name=name))
+            if not isinstance(doc, Doc):
+                raise ValueError(Errors.E005.format(name=name, returned_type=type(doc)))
         return doc
 
     def disable_pipes(self, *names) -> "DisabledPipes":
diff --git a/spacy/tests/test_language.py b/spacy/tests/test_language.py
index 6f3ba8acc..03a98d32f 100644
--- a/spacy/tests/test_language.py
+++ b/spacy/tests/test_language.py
@@ -670,3 +670,25 @@ def test_dot_in_factory_names(nlp):
 
     with pytest.raises(ValueError, match="not permitted"):
         Language.factory("my.evil.component.v1", func=evil_component)
+
+
+def test_component_return():
+    """Test that an error is raised if components return a type other than a
+    doc."""
+    nlp = English()
+
+    @Language.component("test_component_good_pipe")
+    def good_pipe(doc):
+        return doc
+
+    nlp.add_pipe("test_component_good_pipe")
+    nlp("text")
+    nlp.remove_pipe("test_component_good_pipe")
+
+    @Language.component("test_component_bad_pipe")
+    def bad_pipe(doc):
+        return doc.text
+
+    nlp.add_pipe("test_component_bad_pipe")
+    with pytest.raises(ValueError, match="instead of a Doc"):
+        nlp("text")

From d1760ebe027852a10b3ba7c5c7a187859bdae76b Mon Sep 17 00:00:00 2001
From: Madeesh Kannan <shadeMe@users.noreply.github.com>
Date: Fri, 2 Sep 2022 09:09:48 +0200
Subject: [PATCH 080/174] Better handling of unexpected types in `SetPredicate`
 (#11312)

* `Matcher`: Better type checking of values in `SetPredicate`
`SetPredicate`: Emit warning and return `False` on unexpected value types

* Rename `value_type_mismatch` variable

* Inline warning

* Remove unexpected type warning from `_SetPredicate`

* Ensure that `str` values are not interpreted as sequences
Check elements of sequence values for convertibility to `str` or `int`

* Add more `INTERSECT` and `IN` test cases

* Test for inputs with multiple characters

* Return `False` early instead of using a boolean flag

* Remove superfluous `int` check, parentheses

* Apply suggestions from code review

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

* Appy suggestions from code review

* Clarify test comment

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
---
 spacy/matcher/matcher.pyx               | 23 +++++++++++++++--------
 spacy/tests/matcher/test_matcher_api.py | 20 +++++++++++++++++++-
 2 files changed, 34 insertions(+), 9 deletions(-)

diff --git a/spacy/matcher/matcher.pyx b/spacy/matcher/matcher.pyx
index 5105f69ed..e1dba01a2 100644
--- a/spacy/matcher/matcher.pyx
+++ b/spacy/matcher/matcher.pyx
@@ -1,5 +1,5 @@
 # cython: infer_types=True, cython: profile=True
-from typing import List
+from typing import List, Iterable
 
 from libcpp.vector cimport vector
 from libc.stdint cimport int32_t, int8_t
@@ -867,20 +867,27 @@ class _SetPredicate:
 
     def __call__(self, Token token):
         if self.is_extension:
-            value = get_string_id(token._.get(self.attr))
+            value = token._.get(self.attr)
         else:
             value = get_token_attr_for_matcher(token.c, self.attr)
 
-        if self.predicate in ("IS_SUBSET", "IS_SUPERSET", "INTERSECTS"):
+        if self.predicate in ("IN", "NOT_IN"):
+            if isinstance(value, (str, int)):
+                value = get_string_id(value)
+            else:
+                return False
+        elif self.predicate in ("IS_SUBSET", "IS_SUPERSET", "INTERSECTS"):
+            # ensure that all values are enclosed in a set
             if self.attr == MORPH:
                 # break up MORPH into individual Feat=Val values
                 value = set(get_string_id(v) for v in MorphAnalysis.from_id(self.vocab, value))
+            elif isinstance(value, (str, int)):
+                value = set((get_string_id(value),))
+            elif isinstance(value, Iterable) and all(isinstance(v, (str, int)) for v in value):
+                value = set(get_string_id(v) for v in value)
             else:
-                # treat a single value as a list
-                if isinstance(value, (str, int)):
-                    value = set([get_string_id(value)])
-                else:
-                    value = set(get_string_id(v) for v in value)
+                return False
+
         if self.predicate == "IN":
             return value in self.value
         elif self.predicate == "NOT_IN":
diff --git a/spacy/tests/matcher/test_matcher_api.py b/spacy/tests/matcher/test_matcher_api.py
index 7c16da9f8..ac905eeb4 100644
--- a/spacy/tests/matcher/test_matcher_api.py
+++ b/spacy/tests/matcher/test_matcher_api.py
@@ -368,6 +368,16 @@ def test_matcher_intersect_value_operator(en_vocab):
     doc[0]._.ext = ["A", "B"]
     assert len(matcher(doc)) == 1
 
+    # INTERSECTS matches nothing for iterables that aren't all str or int
+    matcher = Matcher(en_vocab)
+    pattern = [{"_": {"ext": {"INTERSECTS": ["Abx", "C"]}}}]
+    matcher.add("M", [pattern])
+    doc = Doc(en_vocab, words=["a", "b", "c"])
+    doc[0]._.ext = [["Abx"], "B"]
+    assert len(matcher(doc)) == 0
+    doc[0]._.ext = ["Abx", "B"]
+    assert len(matcher(doc)) == 1
+
     # INTERSECTS with an empty pattern list matches nothing
     matcher = Matcher(en_vocab)
     pattern = [{"_": {"ext": {"INTERSECTS": []}}}]
@@ -476,14 +486,22 @@ def test_matcher_extension_set_membership(en_vocab):
     assert len(matches) == 0
 
 
-@pytest.mark.xfail(reason="IN predicate must handle sequence values in extensions")
 def test_matcher_extension_in_set_predicate(en_vocab):
     matcher = Matcher(en_vocab)
     Token.set_extension("ext", default=[])
     pattern = [{"_": {"ext": {"IN": ["A", "C"]}}}]
     matcher.add("M", [pattern])
     doc = Doc(en_vocab, words=["a", "b", "c"])
+
+    # The IN predicate expects an exact match between the
+    # extension value and one of the pattern's values.
     doc[0]._.ext = ["A", "B"]
+    assert len(matcher(doc)) == 0
+
+    doc[0]._.ext = ["A"]
+    assert len(matcher(doc)) == 0
+
+    doc[0]._.ext = "A"
     assert len(matcher(doc)) == 1
 
 

From 71884d0942c9b45f0ce5408496aec1aff2f0a4b7 Mon Sep 17 00:00:00 2001
From: "github-actions[bot]"
 <41898282+github-actions[bot]@users.noreply.github.com>
Date: Fri, 2 Sep 2022 11:43:20 +0200
Subject: [PATCH 081/174] Auto-format code with black (#11427)

Co-authored-by: explosion-bot <explosion-bot@users.noreply.github.com>
---
 spacy/lang/la/__init__.py             |  2 +-
 spacy/lang/la/lex_attrs.py            |  4 +-
 spacy/lang/la/tokenizer_exceptions.py | 70 ++++++++++++++++++++++-----
 spacy/tests/conftest.py               |  2 +-
 spacy/tests/lang/la/test_exception.py |  1 +
 spacy/tests/lang/la/test_text.py      |  4 +-
 6 files changed, 67 insertions(+), 16 deletions(-)

diff --git a/spacy/lang/la/__init__.py b/spacy/lang/la/__init__.py
index 5f2cccee3..15b87c5b9 100644
--- a/spacy/lang/la/__init__.py
+++ b/spacy/lang/la/__init__.py
@@ -6,7 +6,7 @@ from .lex_attrs import LEX_ATTRS
 
 class LatinDefaults(BaseDefaults):
     tokenizer_exceptions = TOKENIZER_EXCEPTIONS
-    stop_words = STOP_WORDS    
+    stop_words = STOP_WORDS
     lex_attr_getters = LEX_ATTRS
 
 
diff --git a/spacy/lang/la/lex_attrs.py b/spacy/lang/la/lex_attrs.py
index 9348a811a..9efb4dd3c 100644
--- a/spacy/lang/la/lex_attrs.py
+++ b/spacy/lang/la/lex_attrs.py
@@ -2,7 +2,9 @@ from ...attrs import LIKE_NUM
 import re
 
 # cf. Goyvaerts/Levithan 2009; case-insensitive, allow 4
-roman_numerals_compile = re.compile(r'(?i)^(?=[MDCLXVI])M*(C[MD]|D?C{0,4})(X[CL]|L?X{0,4})(I[XV]|V?I{0,4})$')
+roman_numerals_compile = re.compile(
+    r"(?i)^(?=[MDCLXVI])M*(C[MD]|D?C{0,4})(X[CL]|L?X{0,4})(I[XV]|V?I{0,4})$"
+)
 
 _num_words = set(
     """
diff --git a/spacy/lang/la/tokenizer_exceptions.py b/spacy/lang/la/tokenizer_exceptions.py
index 905304188..060f6e085 100644
--- a/spacy/lang/la/tokenizer_exceptions.py
+++ b/spacy/lang/la/tokenizer_exceptions.py
@@ -9,21 +9,67 @@ _exc = {
     "tecum": [{ORTH: "te"}, {ORTH: "cum"}],
     "nobiscum": [{ORTH: "nobis"}, {ORTH: "cum"}],
     "vobiscum": [{ORTH: "vobis"}, {ORTH: "cum"}],
-    "uobiscum": [{ORTH: "uobis"}, {ORTH: "cum"}],    
+    "uobiscum": [{ORTH: "uobis"}, {ORTH: "cum"}],
 }
 
 for orth in [
-
-    'A.', 'Agr.', 'Ap.', 'C.', 'Cn.', 'D.', 'F.', 'K.', 'L.', "M'.", 'M.', 'Mam.', 'N.', 'Oct.', 
-    'Opet.', 'P.', 'Paul.', 'Post.', 'Pro.', 'Q.', 'S.', 'Ser.', 'Sert.', 'Sex.', 'St.', 'Sta.', 
-    'T.', 'Ti.', 'V.', 'Vol.', 'Vop.', 'U.', 'Uol.', 'Uop.',
-
-    'Ian.', 'Febr.', 'Mart.', 'Apr.', 'Mai.', 'Iun.', 'Iul.', 'Aug.', 'Sept.', 'Oct.', 'Nov.', 'Nou.', 
-    'Dec.',
-    
-    'Non.', 'Id.', 'A.D.', 
-
-    'Coll.', 'Cos.', 'Ord.', 'Pl.', 'S.C.', 'Suff.', 'Trib.',
+    "A.",
+    "Agr.",
+    "Ap.",
+    "C.",
+    "Cn.",
+    "D.",
+    "F.",
+    "K.",
+    "L.",
+    "M'.",
+    "M.",
+    "Mam.",
+    "N.",
+    "Oct.",
+    "Opet.",
+    "P.",
+    "Paul.",
+    "Post.",
+    "Pro.",
+    "Q.",
+    "S.",
+    "Ser.",
+    "Sert.",
+    "Sex.",
+    "St.",
+    "Sta.",
+    "T.",
+    "Ti.",
+    "V.",
+    "Vol.",
+    "Vop.",
+    "U.",
+    "Uol.",
+    "Uop.",
+    "Ian.",
+    "Febr.",
+    "Mart.",
+    "Apr.",
+    "Mai.",
+    "Iun.",
+    "Iul.",
+    "Aug.",
+    "Sept.",
+    "Oct.",
+    "Nov.",
+    "Nou.",
+    "Dec.",
+    "Non.",
+    "Id.",
+    "A.D.",
+    "Coll.",
+    "Cos.",
+    "Ord.",
+    "Pl.",
+    "S.C.",
+    "Suff.",
+    "Trib.",
 ]:
     _exc[orth] = [{ORTH: orth}]
 
diff --git a/spacy/tests/conftest.py b/spacy/tests/conftest.py
index 0395ba7ca..742bfcc6a 100644
--- a/spacy/tests/conftest.py
+++ b/spacy/tests/conftest.py
@@ -258,7 +258,7 @@ def ko_tokenizer_tokenizer():
 
 @pytest.fixture(scope="module")
 def la_tokenizer():
-    return get_lang_class("la")().tokenizer    
+    return get_lang_class("la")().tokenizer
 
 
 @pytest.fixture(scope="session")
diff --git a/spacy/tests/lang/la/test_exception.py b/spacy/tests/lang/la/test_exception.py
index 04bc1d489..966ae22cf 100644
--- a/spacy/tests/lang/la/test_exception.py
+++ b/spacy/tests/lang/la/test_exception.py
@@ -1,5 +1,6 @@
 import pytest
 
+
 def test_la_tokenizer_handles_exc_in_text(la_tokenizer):
     text = "scio te omnia facturum, ut nobiscum quam primum sis"
     tokens = la_tokenizer(text)
diff --git a/spacy/tests/lang/la/test_text.py b/spacy/tests/lang/la/test_text.py
index 11676b92b..48e7359a4 100644
--- a/spacy/tests/lang/la/test_text.py
+++ b/spacy/tests/lang/la/test_text.py
@@ -1,6 +1,7 @@
 import pytest
 from spacy.lang.la.lex_attrs import like_num
 
+
 @pytest.mark.parametrize(
     "text,match",
     [
@@ -13,7 +14,7 @@ from spacy.lang.la.lex_attrs import like_num
         ("ix", True),
         ("MMXXII", True),
         ("0", True),
-        ("1", True),        
+        ("1", True),
         ("quattuor", True),
         ("decem", True),
         ("tertius", True),
@@ -27,6 +28,7 @@ def test_lex_attrs_like_number(la_tokenizer, text, match):
     assert len(tokens) == 1
     assert tokens[0].like_num == match
 
+
 @pytest.mark.parametrize("word", ["quinque"])
 def test_la_lex_attrs_capitals(word):
     assert like_num(word)

From 977dc33312dd189b5b4ae1d791031d090c169c24 Mon Sep 17 00:00:00 2001
From: Paul O'Leary McCann <polm@dampfkraft.com>
Date: Fri, 2 Sep 2022 18:58:21 +0900
Subject: [PATCH 082/174] Add a way to get the URL to download a pipeline to
 the CLI (#11175)

* Add a dry run flag to download

* Remove --dry-run, add --url option to `spacy info` instead

* Make mypy happy

* Print only the URL, so it's easier to use in scripts

* Don't add the egg hash unless downloading an sdist

* Update spacy/cli/info.py

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Add two implementations of requirements

* Clean up requirements sample slightly

This should make mypy happy

* Update URL help string

* Remove requirements option

* Add url option to docs

* Add URL to spacy info model output, when available

* Add types-setuptools to testing reqs

* Add types-setuptools to requirements

* Add "compatible", expand docstring

* Update spacy/cli/info.py

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

* Run prettier on CLI docs

* Update docs

Add a sidebar about finding download URLs, with some examples of the new
command.

* Add download URLs to table on model page

* Apply suggestions from code review

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

* Updates from review

* download url -> download link

* Update docs

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
---
 requirements.txt                         |  1 +
 spacy/cli/download.py                    | 32 ++++++++++---
 spacy/cli/info.py                        | 58 +++++++++++++++++++++++-
 spacy/tests/package/test_requirements.py |  1 +
 website/docs/api/cli.md                  | 17 +++----
 website/docs/usage/models.md             | 36 ++++++++++-----
 website/src/templates/models.js          | 10 ++++
 7 files changed, 127 insertions(+), 28 deletions(-)

diff --git a/requirements.txt b/requirements.txt
index 3b8d66e0e..3e8501b2f 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -34,4 +34,5 @@ mypy>=0.910,<0.970; platform_machine!='aarch64'
 types-dataclasses>=0.1.3; python_version < "3.7"
 types-mock>=0.1.1
 types-requests
+types-setuptools>=57.0.0
 black>=22.0,<23.0
diff --git a/spacy/cli/download.py b/spacy/cli/download.py
index b7de88729..0c9a32b93 100644
--- a/spacy/cli/download.py
+++ b/spacy/cli/download.py
@@ -20,7 +20,7 @@ def download_cli(
     ctx: typer.Context,
     model: str = Arg(..., help="Name of pipeline package to download"),
     direct: bool = Opt(False, "--direct", "-d", "-D", help="Force direct download of name + version"),
-    sdist: bool = Opt(False, "--sdist", "-S", help="Download sdist (.tar.gz) archive instead of pre-built binary wheel")
+    sdist: bool = Opt(False, "--sdist", "-S", help="Download sdist (.tar.gz) archive instead of pre-built binary wheel"),
     # fmt: on
 ):
     """
@@ -36,7 +36,12 @@ def download_cli(
     download(model, direct, sdist, *ctx.args)
 
 
-def download(model: str, direct: bool = False, sdist: bool = False, *pip_args) -> None:
+def download(
+    model: str,
+    direct: bool = False,
+    sdist: bool = False,
+    *pip_args,
+) -> None:
     if (
         not (is_package("spacy") or is_package("spacy-nightly"))
         and "--no-deps" not in pip_args
@@ -50,13 +55,10 @@ def download(model: str, direct: bool = False, sdist: bool = False, *pip_args) -
             "dependencies, you'll have to install them manually."
         )
         pip_args = pip_args + ("--no-deps",)
-    suffix = SDIST_SUFFIX if sdist else WHEEL_SUFFIX
-    dl_tpl = "{m}-{v}/{m}-{v}{s}#egg={m}=={v}"
     if direct:
         components = model.split("-")
         model_name = "".join(components[:-1])
         version = components[-1]
-        download_model(dl_tpl.format(m=model_name, v=version, s=suffix), pip_args)
     else:
         model_name = model
         if model in OLD_MODEL_SHORTCUTS:
@@ -67,13 +69,26 @@ def download(model: str, direct: bool = False, sdist: bool = False, *pip_args) -
             model_name = OLD_MODEL_SHORTCUTS[model]
         compatibility = get_compatibility()
         version = get_version(model_name, compatibility)
-        download_model(dl_tpl.format(m=model_name, v=version, s=suffix), pip_args)
+
+    filename = get_model_filename(model_name, version, sdist)
+
+    download_model(filename, pip_args)
     msg.good(
         "Download and installation successful",
         f"You can now load the package via spacy.load('{model_name}')",
     )
 
 
+def get_model_filename(model_name: str, version: str, sdist: bool = False) -> str:
+    dl_tpl = "{m}-{v}/{m}-{v}{s}"
+    egg_tpl = "#egg={m}=={v}"
+    suffix = SDIST_SUFFIX if sdist else WHEEL_SUFFIX
+    filename = dl_tpl.format(m=model_name, v=version, s=suffix)
+    if sdist:
+        filename += egg_tpl.format(m=model_name, v=version)
+    return filename
+
+
 def get_compatibility() -> dict:
     if is_prerelease_version(about.__version__):
         version: Optional[str] = about.__version__
@@ -105,6 +120,11 @@ def get_version(model: str, comp: dict) -> str:
     return comp[model][0]
 
 
+def get_latest_version(model: str) -> str:
+    comp = get_compatibility()
+    return get_version(model, comp)
+
+
 def download_model(
     filename: str, user_pip_args: Optional[Sequence[str]] = None
 ) -> None:
diff --git a/spacy/cli/info.py b/spacy/cli/info.py
index e6a1cb616..e6ac4270f 100644
--- a/spacy/cli/info.py
+++ b/spacy/cli/info.py
@@ -1,10 +1,13 @@
 from typing import Optional, Dict, Any, Union, List
 import platform
+import pkg_resources
+import json
 from pathlib import Path
 from wasabi import Printer, MarkdownRenderer
 import srsly
 
 from ._util import app, Arg, Opt, string_to_list
+from .download import get_model_filename, get_latest_version
 from .. import util
 from .. import about
 
@@ -16,6 +19,7 @@ def info_cli(
     markdown: bool = Opt(False, "--markdown", "-md", help="Generate Markdown for GitHub issues"),
     silent: bool = Opt(False, "--silent", "-s", "-S", help="Don't print anything (just return)"),
     exclude: str = Opt("labels", "--exclude", "-e", help="Comma-separated keys to exclude from the print-out"),
+    url: bool = Opt(False, "--url", "-u", help="Print the URL to download the most recent compatible version of the pipeline"),
     # fmt: on
 ):
     """
@@ -23,10 +27,19 @@ def info_cli(
     print its meta information. Flag --markdown prints details in Markdown for easy
     copy-pasting to GitHub issues.
 
+    Flag --url prints only the download URL of the most recent compatible
+    version of the pipeline.
+
     DOCS: https://spacy.io/api/cli#info
     """
     exclude = string_to_list(exclude)
-    info(model, markdown=markdown, silent=silent, exclude=exclude)
+    info(
+        model,
+        markdown=markdown,
+        silent=silent,
+        exclude=exclude,
+        url=url,
+    )
 
 
 def info(
@@ -35,11 +48,20 @@ def info(
     markdown: bool = False,
     silent: bool = True,
     exclude: Optional[List[str]] = None,
+    url: bool = False,
 ) -> Union[str, dict]:
     msg = Printer(no_print=silent, pretty=not silent)
     if not exclude:
         exclude = []
-    if model:
+    if url:
+        if model is not None:
+            title = f"Download info for pipeline '{model}'"
+            data = info_model_url(model)
+            print(data["download_url"])
+            return data
+        else:
+            msg.fail("--url option requires a pipeline name", exits=1)
+    elif model:
         title = f"Info about pipeline '{model}'"
         data = info_model(model, silent=silent)
     else:
@@ -99,11 +121,43 @@ def info_model(model: str, *, silent: bool = True) -> Dict[str, Any]:
         meta["source"] = str(model_path.resolve())
     else:
         meta["source"] = str(model_path)
+    download_url = info_installed_model_url(model)
+    if download_url:
+        meta["download_url"] = download_url
     return {
         k: v for k, v in meta.items() if k not in ("accuracy", "performance", "speed")
     }
 
 
+def info_installed_model_url(model: str) -> Optional[str]:
+    """Given a pipeline name, get the download URL if available, otherwise
+    return None.
+
+    This is only available for pipelines installed as modules that have
+    dist-info available.
+    """
+    try:
+        dist = pkg_resources.get_distribution(model)
+        data = json.loads(dist.get_metadata("direct_url.json"))
+        return data["url"]
+    except pkg_resources.DistributionNotFound:
+        # no such package
+        return None
+    except Exception:
+        # something else, like no file or invalid JSON
+        return None
+
+def info_model_url(model: str) -> Dict[str, Any]:
+    """Return the download URL for the latest version of a pipeline."""
+    version = get_latest_version(model)
+
+    filename = get_model_filename(model, version)
+    download_url = about.__download_url__ + "/" + filename
+    release_tpl = "https://github.com/explosion/spacy-models/releases/tag/{m}-{v}"
+    release_url = release_tpl.format(m=model, v=version)
+    return {"download_url": download_url, "release_url": release_url}
+
+
 def get_markdown(
     data: Dict[str, Any],
     title: Optional[str] = None,
diff --git a/spacy/tests/package/test_requirements.py b/spacy/tests/package/test_requirements.py
index e20227455..b403f274f 100644
--- a/spacy/tests/package/test_requirements.py
+++ b/spacy/tests/package/test_requirements.py
@@ -17,6 +17,7 @@ def test_build_dependencies():
         "types-dataclasses",
         "types-mock",
         "types-requests",
+        "types-setuptools",
     ]
     # ignore language-specific packages that shouldn't be installed by all
     libs_ignore_setup = [
diff --git a/website/docs/api/cli.md b/website/docs/api/cli.md
index cbd1f794a..e5cd3089b 100644
--- a/website/docs/api/cli.md
+++ b/website/docs/api/cli.md
@@ -77,14 +77,15 @@ $ python -m spacy info [--markdown] [--silent] [--exclude]
 $ python -m spacy info [model] [--markdown] [--silent] [--exclude]
 ```
 
-| Name                                             | Description                                                                                   |
-| ------------------------------------------------ | --------------------------------------------------------------------------------------------- |
-| `model`                                          | A trained pipeline, i.e. package name or path (optional). ~~Optional[str] \(option)~~         |
-| `--markdown`, `-md`                              | Print information as Markdown. ~~bool (flag)~~                                                |
-| `--silent`, `-s` <Tag variant="new">2.0.12</Tag> | Don't print anything, just return the values. ~~bool (flag)~~                                 |
-| `--exclude`, `-e`                                | Comma-separated keys to exclude from the print-out. Defaults to `"labels"`. ~~Optional[str]~~ |
-| `--help`, `-h`                                   | Show help message and available arguments. ~~bool (flag)~~                                    |
-| **PRINTS**                                       | Information about your spaCy installation.                                                    |
+| Name                                             | Description                                                                                                             |
+| ------------------------------------------------ | ----------------------------------------------------------------------------------------------------------------------- |
+| `model`                                          | A trained pipeline, i.e. package name or path (optional). ~~Optional[str] \(option)~~                                   |
+| `--markdown`, `-md`                              | Print information as Markdown. ~~bool (flag)~~                                                                          |
+| `--silent`, `-s` <Tag variant="new">2.0.12</Tag> | Don't print anything, just return the values. ~~bool (flag)~~                                                           |
+| `--exclude`, `-e`                                | Comma-separated keys to exclude from the print-out. Defaults to `"labels"`. ~~Optional[str]~~                           |
+| `--url`, `-u` <Tag variant="new">3.5.0</Tag>     | Print the URL to download the most recent compatible version of the pipeline. Requires a pipeline name. ~~bool (flag)~~ |
+| `--help`, `-h`                                   | Show help message and available arguments. ~~bool (flag)~~                                                              |
+| **PRINTS**                                       | Information about your spaCy installation.                                                                              |
 
 ## validate {#validate new="2" tag="command"}
 
diff --git a/website/docs/usage/models.md b/website/docs/usage/models.md
index 56992e7e3..6971ac8b4 100644
--- a/website/docs/usage/models.md
+++ b/website/docs/usage/models.md
@@ -365,15 +365,32 @@ pipeline package can be found.
 To download a trained pipeline directly using
 [pip](https://pypi.python.org/pypi/pip), point `pip install` to the URL or local
 path of the wheel file or archive. Installing the wheel is usually more
-efficient. To find the direct link to a package, head over to the
-[releases](https://github.com/explosion/spacy-models/releases), right click on
-the archive link and copy it to your clipboard.
+efficient.
+
+> #### Pipeline Package URLs {#pipeline-urls}
+>
+> Pretrained pipeline distributions are hosted on
+> [Github Releases](https://github.com/explosion/spacy-models/releases), and you
+> can find download links there, as well as on the model page. You can also get
+> URLs directly from the command line by using `spacy info` with the `--url`
+> flag, which may be useful for automation.
+>
+> ```bash
+> spacy info en_core_web_sm --url
+> ```
+>
+> This command will print the URL for the latest version of a pipeline
+> compatible with the version of spaCy you're using. Note that in order to look
+> up the compatibility information an internet connection is required.
 
 ```bash
 # With external URL
 $ pip install https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.0.0/en_core_web_sm-3.0.0-py3-none-any.whl
 $ pip install https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.0.0/en_core_web_sm-3.0.0.tar.gz
 
+# Using spacy info to get the external URL
+$ pip install $(spacy info en_core_web_sm --url)
+
 # With local file
 $ pip install /Users/you/en_core_web_sm-3.0.0-py3-none-any.whl
 $ pip install /Users/you/en_core_web_sm-3.0.0.tar.gz
@@ -514,21 +531,16 @@ should be specifying them directly.
 Because pipeline packages are valid Python packages, you can add them to your
 application's `requirements.txt`. If you're running your own internal PyPi
 installation, you can upload the pipeline packages there. pip's
-[requirements file format](https://pip.pypa.io/en/latest/reference/pip_install/#requirements-file-format)
-supports both package names to download via a PyPi server, as well as direct
-URLs.
+[requirements file format](https://pip.pypa.io/en/latest/reference/requirements-file-format/)
+supports both package names to download via a PyPi server, as well as
+[direct URLs](#pipeline-urls).
 
 ```text
 ### requirements.txt
 spacy>=3.0.0,<4.0.0
-https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.0.0/en_core_web_sm-3.0.0.tar.gz#egg=en_core_web_sm
+en_core_web_sm @ https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.4.0/en_core_web_sm-3.4.0-py3-none-any.whl
 ```
 
-Specifying `#egg=` with the package name tells pip which package to expect from
-the download URL. This way, the package won't be re-downloaded and overwritten
-if it's already installed - just like when you're downloading a package from
-PyPi.
-
 All pipeline packages are versioned and specify their spaCy dependency. This
 ensures cross-compatibility and lets you specify exact version requirements for
 each pipeline. If you've [trained](/usage/training) your own pipeline, you can
diff --git a/website/src/templates/models.js b/website/src/templates/models.js
index df53f8c3c..16a2360d5 100644
--- a/website/src/templates/models.js
+++ b/website/src/templates/models.js
@@ -76,6 +76,7 @@ const MODEL_META = {
     benchmark_ner: 'NER accuracy',
     benchmark_speed: 'Speed',
     compat: 'Latest compatible package version for your spaCy installation',
+    download_link: 'Download link for the pipeline',
 }
 
 const LABEL_SCHEME_META = {
@@ -138,6 +139,13 @@ function formatAccuracy(data, lang) {
         .filter(item => item)
 }
 
+function formatDownloadLink(lang, name, version) {
+  const fullName = `${lang}_${name}-${version}`
+  const filename = `${fullName}-py3-none-any.whl`
+  const url = `https://github.com/explosion/spacy-models/releases/download/${fullName}/${filename}`
+  return <Link to={url} hideIcon>{filename}</Link>
+}
+
 function formatModelMeta(data) {
     return {
         fullName: `${data.lang}_${data.name}-${data.version}`,
@@ -154,6 +162,7 @@ function formatModelMeta(data) {
         labels: isEmptyObj(data.labels) ? null : data.labels,
         vectors: formatVectors(data.vectors),
         accuracy: formatAccuracy(data.performance, data.lang),
+        download_link: formatDownloadLink(data.lang, data.name, data.version),
     }
 }
 
@@ -244,6 +253,7 @@ const Model = ({
         { label: 'Components', content: components, help: MODEL_META.components },
         { label: 'Pipeline', content: pipeline, help: MODEL_META.pipeline },
         { label: 'Vectors', content: meta.vectors, help: MODEL_META.vecs },
+        { label: 'Download Link', content: meta.download_link, help: MODEL_META.download_link },
         { label: 'Sources', content: sources, help: MODEL_META.sources },
         { label: 'Author', content: author },
         { label: 'License', content: license },

From ff0522f8daac603e4dfb2773e1a73da61acc621d Mon Sep 17 00:00:00 2001
From: Paul O'Leary McCann <polm@dampfkraft.com>
Date: Thu, 1 Sep 2022 11:35:52 +0900
Subject: [PATCH 083/174] Fix asent pip package name

---
 website/meta/universe.json | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/website/meta/universe.json b/website/meta/universe.json
index 6c8caa6a6..9145855c6 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -1192,7 +1192,7 @@
             "slogan": "Fast, flexible and transparent sentiment analysis",
             "description": "Asent is a rule-based sentiment analysis library for Python made using spaCy. It is inspired by VADER, but uses a more modular ruleset, that allows the user to change e.g. the method for finding negations. Furthermore it includes visualisers to visualize the model predictions, making the model easily interpretable.",
             "github": "kennethenevoldsen/asent",
-            "pip": "aseny",
+            "pip": "asent",
             "code_example": [
                 "import spacy",
                 "import asent",

From 515d5c65d5f5d05eb8d2777e59cb5680dfcb4bd9 Mon Sep 17 00:00:00 2001
From: Paul O'Leary McCann <polm@dampfkraft.com>
Date: Wed, 7 Sep 2022 22:24:22 +0900
Subject: [PATCH 084/174] Add dev docs on satellite packages (#11435)

* Add dev docs on satellite packages

* Apply suggestions from code review

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Add displacy link

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
---
 extra/DEVELOPER_DOCS/Satellite Packages.md | 82 ++++++++++++++++++++++
 1 file changed, 82 insertions(+)
 create mode 100644 extra/DEVELOPER_DOCS/Satellite Packages.md

diff --git a/extra/DEVELOPER_DOCS/Satellite Packages.md b/extra/DEVELOPER_DOCS/Satellite Packages.md
new file mode 100644
index 000000000..02b06a90e
--- /dev/null
+++ b/extra/DEVELOPER_DOCS/Satellite Packages.md	
@@ -0,0 +1,82 @@
+# spaCy Satellite Packages
+
+This is a list of all the active repos relevant to spaCy besides the main one, with short descriptions, history, and current status. Archived repos will not be covered.
+
+## Always Included in spaCy
+
+These packages are always pulled in when you install spaCy. Most of them are direct dependencies, but some are transitive dependencies through other packages.
+
+- [spacy-legacy](https://github.com/explosion/spacy-legacy): When an architecture in spaCy changes enough to get a new version, the old version is frozen and moved to spacy-legacy. This allows us to keep the core library slim while also preserving backwards compatability.
+- [thinc](https://github.com/explosion/thinc): Thinc is the machine learning library that powers trainable components in spaCy. It wraps backends like Numpy, PyTorch, and Tensorflow to provide a functional interface for specifying architectures.
+- [catalogue](https://github.com/explosion/catalogue): Small library for adding function registries, like those used for model architectures in spaCy.
+- [confection](https://github.com/explosion/confection): This library contains the functionality for config parsing that was formerly contained directly in Thinc.
+- [spacy-loggers](https://github.com/explosion/spacy-loggers): Contains loggers beyond the default logger available in spaCy&#39;s core code base. This includes loggers integrated with third-party services, which may differ in release cadence from spaCy itself.
+- [wasabi](https://github.com/explosion/wasabi): A command line formatting library, used for terminal output in spaCy.
+- [srsly](https://github.com/explosion/srsly): A wrapper that vendors several serialization libraries for spaCy. Includes parsers for JSON, JSONL, MessagePack, (extended) Pickle, and YAML.
+- [preshed](https://github.com/explosion/preshed): A Cython library for low-level data structures like hash maps, used for memory efficient data storage.
+- [cython-blis](https://github.com/explosion/cython-blis): Fast matrix multiplication using BLIS without depending on system libraries. Required by Thinc, rather than spaCy directly.
+- [murmurhash](https://github.com/explosion/murmurhash): A wrapper library for a C++ murmurhash implementation, used for string IDs in spaCy and preshed.
+- [cymem](https://github.com/explosion/cymem): A small library for RAII-style memory management in Cython. 
+
+## Optional Extensions for spaCy
+
+These are repos that can be used by spaCy but aren&#39;t part of a default installation. Many of these are wrappers to integrate various kinds of third-party libraries.
+
+- [spacy-transformers](https://github.com/explosion/spacy-transformers): A wrapper for the [HuggingFace Transformers](https://huggingface.co/docs/transformers/index) library, this handles the extensive conversion necessary to coordinate spaCy&#39;s powerful `Doc` representation, training pipeline, and the Transformer embeddings. When released, this was known as `spacy-pytorch-transformers`, but it changed to the current name when HuggingFace update the name of their library as well.
+- [spacy-huggingface-hub](https://github.com/explosion/spacy-huggingface-hub): This package has a CLI script for uploading a packaged spaCy pipeline (created with `spacy package`) to the [Hugging Face Hub](https://huggingface.co/models).
+- [spacy-alignments](https://github.com/explosion/spacy-alignments): A wrapper for the tokenizations library (mentioned below) with a modified build system to simplify cross-platform wheel creation. Used in spacy-transformers for aligning spaCy and HuggingFace tokenizations.
+- [spacy-experimental](https://github.com/explosion/spacy-experimental): Experimental components that are not quite ready for inclusion in the main spaCy library. Usually there are unresolved questions around their APIs, so the experimental library allows us to expose them to the community for feedback before fully integrating them. 
+- [spacy-lookups-data](https://github.com/explosion/spacy-lookups-data): A repository of linguistic data, such as lemmas, that takes up a lot of disk space. Originally created to reduce the size of the spaCy core library. This is mainly useful if you want the data included but aren&#39;t using a pretrained pipeline; for the affected languages, the relevant data is included in pretrained pipelines directly.
+- [coreferee](https://github.com/explosion/coreferee): Coreference resolution for English, French, German and Polish, optimised for limited training data and easily extensible for further languages. Used as a spaCy pipeline component.
+- [spacy-stanza](https://github.com/explosion/spacy-stanza): This is a wrapper that allows the use of Stanford&#39;s Stanza library in spaCy. 
+- [spacy-streamlit](https://github.com/explosion/spacy-streamlit): A wrapper for the Streamlit dashboard building library to help with integrating [displaCy](https://spacy.io/api/top-level/#displacy).
+- [spacymoji](https://github.com/explosion/spacymoji): A library to add extra support for emoji to spaCy, such as including character names.
+- [thinc-apple-ops](https://github.com/explosion/thinc-apple-ops): A special backend for OSX that uses Apple&#39;s native libraries for improved performance.
+- [os-signpost](https://github.com/explosion/os-signpost): A Python package that allows you to use the `OSSignposter` API in OSX for performance analysis.
+- [spacy-ray](https://github.com/explosion/spacy-ray): A wrapper to integrate spaCy with Ray, a distributed training framework. Currently a work in progress.
+
+## Prodigy
+
+[Prodigy](https://prodi.gy) is Explosion&#39;s easy to use and highly customizable tool for annotating data. Prodigy itself requires a license, but the repos below contain documentation, examples, and editor or notebook integrations.
+
+- [prodigy-recipes](https://github.com/explosion/prodigy-recipes): Sample recipes for Prodigy, along with notebooks and other examples of usage.
+- [vscode-prodigy](https://github.com/explosion/vscode-prodigy): A VS Code extension that lets you run Prodigy inside VS Code.
+- [jupyterlab-prodigy](https://github.com/explosion/jupyterlab-prodigy): An extension for JupyterLab that lets you run Prodigy inside JupyterLab.
+
+## Independent Tools or Projects
+
+These are tools that may be related to or use spaCy, but are functional independent projects in their own right as well.
+
+- [floret](https://github.com/explosion/floret): A modification of fastText to use Bloom Embeddings. Can be used to add vectors with subword features to spaCy, and also works independently in the same manner as fastText.
+- [sense2vec](https://github.com/explosion/sense2vec): A library to make embeddings of noun phrases or words coupled with their part of speech. This library uses spaCy.
+- [spacy-vectors-builder](https://github.com/explosion/spacy-vectors-builder): This is a spaCy project that builds vectors using floret and a lot of input text. It handles downloading the input data as well as the actual building of vectors.
+- [holmes-extractor](https://github.com/explosion/holmes-extractor): Information extraction from English and German texts based on predicate logic. Uses spaCy.
+- [healthsea](https://github.com/explosion/healthsea): Healthsea is a project to extract information from comments about health supplements. Structurally, it&#39;s a self-contained, large spaCy project.
+- [spacy-pkuseg](https://github.com/explosion/spacy-pkuseg): A fork of the pkuseg Chinese tokenizer. Used for Chinese support in spaCy, but also works independently.
+- [ml-datasets](https://github.com/explosion/ml-datasets): This repo includes loaders for several standard machine learning datasets, like MNIST or WikiNER, and has historically been used in spaCy example code and documentation.
+
+## Documentation and Informational Repos
+
+These repos are used to support the spaCy docs or otherwise present information about spaCy or other Explosion projects.
+
+- [projects](https://github.com/explosion/projects): The projects repo is used to show detailed examples of spaCy usage. Individual projects can be checked out using the spaCy command line tool, rather than checking out the projects repo directly.
+- [spacy-course](https://github.com/explosion/spacy-course): Home to the interactive spaCy course for learning about how to use the library and some basic NLP principles.
+- [spacy-io-binder](https://github.com/explosion/spacy-io-binder): Home to the notebooks used for interactive examples in the documentation.
+
+## Organizational / Meta
+
+These repos are used for organizing data around spaCy, but are not something an end user would need to install as part of using the library.
+
+- [spacy-models](https://github.com/explosion/spacy-models): This repo contains metadata (but not training data) for all the spaCy models. This includes information about where their training data came from, version compatability, and performance information. It also includes tests for the model packages, and the built models are hosted as releases of this repo.
+- [wheelwright](https://github.com/explosion/wheelwright): A tool for automating our PyPI builds and releases.
+- [ec2buildwheel](https://github.com/explosion/ec2buildwheel): A small project that allows you to build Python packages in the manner of cibuildwheel, but on any EC2 image. Used by wheelwright.
+
+## Other
+
+Repos that don&#39;t fit in any of the above categories.
+
+- [blis](https://github.com/explosion/blis): A fork of the official BLIS library. The main branch is not updated, but work continues in various branches. This is used for cython-blis.
+- [tokenizations](https://github.com/explosion/tokenizations): A library originally by Yohei Tamura to align strings with tolerance to some variations in features like case and diacritics, used for aligning tokens and wordpieces. Adopted and maintained by Explosion, but usually spacy-alignments is used instead.
+- [conll-2012](https://github.com/explosion/conll-2012): A repo to hold some slightly cleaned up versions of the official scripts for the CoNLL 2012 shared task involving coreference resolution. Used in the coref project.
+- [fastapi-explosion-extras](https://github.com/explosion/fastapi-explosion-extras): Some small tweaks to FastAPI used at Explosion.
+

From 1f23c615d7a7326ca5a38a7d768b8b70caaa0e17 Mon Sep 17 00:00:00 2001
From: Raphael Mitsch <r.mitsch@outlook.com>
Date: Thu, 8 Sep 2022 10:38:07 +0200
Subject: [PATCH 085/174] Refactor KB for easier customization (#11268)

* Add implementation of batching + backwards compatibility fixes. Tests indicate issue with batch disambiguation for custom singular entity lookups.

* Fix tests. Add distinction w.r.t. batch size.

* Remove redundant and add new comments.

* Adjust comments. Fix variable naming in EL prediction.

* Fix mypy errors.

* Remove KB entity type config option. Change return types of candidate retrieval functions to Iterable from Iterator. Fix various other issues.

* Update spacy/pipeline/entity_linker.py

Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com>

* Update spacy/pipeline/entity_linker.py

Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com>

* Update spacy/kb_base.pyx

Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com>

* Update spacy/kb_base.pyx

Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com>

* Update spacy/pipeline/entity_linker.py

Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com>

* Add error messages to NotImplementedErrors. Remove redundant comment.

* Fix imports.

* Remove redundant comments.

* Rename KnowledgeBase to InMemoryLookupKB and BaseKnowledgeBase to KnowledgeBase.

* Fix tests.

* Update spacy/errors.py

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Move KB into subdirectory.

* Adjust imports after KB move to dedicated subdirectory.

* Fix config imports.

* Move Candidate + retrieval functions to separate module. Fix other, small issues.

* Fix docstrings and error message w.r.t. class names. Fix typing for candidate retrieval functions.

* Update spacy/kb/kb_in_memory.pyx

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Update spacy/ml/models/entity_linker.py

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Fix typing.

* Change typing of mentions to be Span instead of Union[Span, str].

* Update docs.

* Update EntityLinker and _architecture docs.

* Update website/docs/api/entitylinker.md

Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com>

* Adjust message for E1046.

* Re-add section for Candidate in kb.md, add reference to dedicated page.

* Update docs and docstrings.

* Re-add section + reference for KnowledgeBase.get_alias_candidates() in docs.

* Update spacy/kb/candidate.pyx

* Update spacy/kb/kb_in_memory.pyx

* Update spacy/pipeline/legacy/entity_linker.py

* Remove canididate.md. Remove mistakenly added config snippet in entity_linker.py.

Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com>
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
---
 setup.py                                      |   4 +-
 spacy/errors.py                               |  10 +-
 spacy/kb/__init__.py                          |   3 +
 spacy/kb/candidate.pxd                        |  12 +
 spacy/kb/candidate.pyx                        |  74 +++++
 spacy/kb/kb.pxd                               |  10 +
 spacy/kb/kb.pyx                               | 108 +++++++
 spacy/{kb.pxd => kb/kb_in_memory.pxd}         |  24 +-
 spacy/{kb.pyx => kb/kb_in_memory.pyx}         |  96 ++----
 spacy/ml/models/entity_linker.py              |  30 +-
 spacy/pipeline/entity_linker.py               | 184 +++++++----
 spacy/pipeline/legacy/entity_linker.py        |   5 +-
 spacy/tests/pipeline/test_entity_linker.py    |  98 +++---
 .../tests/serialize/test_resource_warning.py  |   8 +-
 spacy/tests/serialize/test_serialize_kb.py    |  16 +-
 website/docs/api/architectures.md             |  14 +-
 website/docs/api/entitylinker.md              |   5 +-
 website/docs/api/kb.md                        | 219 +++++--------
 website/docs/api/kb_in_memory.md              | 302 ++++++++++++++++++
 website/docs/usage/101/_architecture.md       |   4 +-
 20 files changed, 854 insertions(+), 372 deletions(-)
 create mode 100644 spacy/kb/__init__.py
 create mode 100644 spacy/kb/candidate.pxd
 create mode 100644 spacy/kb/candidate.pyx
 create mode 100644 spacy/kb/kb.pxd
 create mode 100644 spacy/kb/kb.pyx
 rename spacy/{kb.pxd => kb/kb_in_memory.pxd} (92%)
 rename spacy/{kb.pyx => kb/kb_in_memory.pyx} (90%)
 create mode 100644 website/docs/api/kb_in_memory.md

diff --git a/setup.py b/setup.py
index ec1bd35fa..899d940ed 100755
--- a/setup.py
+++ b/setup.py
@@ -30,7 +30,9 @@ MOD_NAMES = [
     "spacy.lexeme",
     "spacy.vocab",
     "spacy.attrs",
-    "spacy.kb",
+    "spacy.kb.candidate",
+    "spacy.kb.kb",
+    "spacy.kb.kb_in_memory",
     "spacy.ml.parser_model",
     "spacy.morphology",
     "spacy.pipeline.dep_parser",
diff --git a/spacy/errors.py b/spacy/errors.py
index 5ee1476c2..e2201284f 100644
--- a/spacy/errors.py
+++ b/spacy/errors.py
@@ -709,9 +709,9 @@ class Errors(metaclass=ErrorsWithCodes):
             "`nlp.enable_pipe` instead.")
     E927 = ("Can't write to frozen list Maybe you're trying to modify a computed "
             "property or default function argument?")
-    E928 = ("A KnowledgeBase can only be serialized to/from from a directory, "
+    E928 = ("An InMemoryLookupKB can only be serialized to/from from a directory, "
             "but the provided argument {loc} points to a file.")
-    E929 = ("Couldn't read KnowledgeBase from {loc}. The path does not seem to exist.")
+    E929 = ("Couldn't read InMemoryLookupKB from {loc}. The path does not seem to exist.")
     E930 = ("Received invalid get_examples callback in `{method}`. "
             "Expected function that returns an iterable of Example objects but "
             "got: {obj}")
@@ -941,6 +941,12 @@ class Errors(metaclass=ErrorsWithCodes):
              "`{arg2}`={arg2_values} but these arguments are conflicting.")
     E1043 = ("Expected None or a value in range [{range_start}, {range_end}] for entity linker threshold, but got "
              "{value}.")
+    E1044 = ("Expected `candidates_batch_size` to be >= 1, but got: {value}")
+    E1045 = ("Encountered {parent} subclass without `{parent}.{method}` "
+             "method in '{name}'. If you want to use this method, make "
+             "sure it's overwritten on the subclass.")
+    E1046 = ("{cls_name} is an abstract class and cannot be instantiated. If you are looking for spaCy's default "
+             "knowledge base, use `InMemoryLookupKB`.")
 
 
 # Deprecated model shortcuts, only used in errors and warnings
diff --git a/spacy/kb/__init__.py b/spacy/kb/__init__.py
new file mode 100644
index 000000000..1d70a9b34
--- /dev/null
+++ b/spacy/kb/__init__.py
@@ -0,0 +1,3 @@
+from .kb import KnowledgeBase
+from .kb_in_memory import InMemoryLookupKB
+from .candidate import Candidate, get_candidates, get_candidates_batch
diff --git a/spacy/kb/candidate.pxd b/spacy/kb/candidate.pxd
new file mode 100644
index 000000000..942ce9dd0
--- /dev/null
+++ b/spacy/kb/candidate.pxd
@@ -0,0 +1,12 @@
+from .kb cimport KnowledgeBase
+from libcpp.vector cimport vector
+from ..typedefs cimport hash_t
+
+# Object used by the Entity Linker that summarizes one entity-alias candidate combination.
+cdef class Candidate:
+    cdef readonly KnowledgeBase kb
+    cdef hash_t entity_hash
+    cdef float entity_freq
+    cdef vector[float] entity_vector
+    cdef hash_t alias_hash
+    cdef float prior_prob
diff --git a/spacy/kb/candidate.pyx b/spacy/kb/candidate.pyx
new file mode 100644
index 000000000..c89efeb03
--- /dev/null
+++ b/spacy/kb/candidate.pyx
@@ -0,0 +1,74 @@
+# cython: infer_types=True, profile=True
+
+from typing import Iterable
+from .kb cimport KnowledgeBase
+from ..tokens import Span
+
+cdef class Candidate:
+    """A `Candidate` object refers to a textual mention (`alias`) that may or may not be resolved
+    to a specific `entity` from a Knowledge Base. This will be used as input for the entity linking
+    algorithm which will disambiguate the various candidates to the correct one.
+    Each candidate (alias, entity) pair is assigned a certain prior probability.
+
+    DOCS: https://spacy.io/api/kb/#candidate-init
+    """
+
+    def __init__(self, KnowledgeBase kb, entity_hash, entity_freq, entity_vector, alias_hash, prior_prob):
+        self.kb = kb
+        self.entity_hash = entity_hash
+        self.entity_freq = entity_freq
+        self.entity_vector = entity_vector
+        self.alias_hash = alias_hash
+        self.prior_prob = prior_prob
+
+    @property
+    def entity(self) -> int:
+        """RETURNS (uint64): hash of the entity's KB ID/name"""
+        return self.entity_hash
+
+    @property
+    def entity_(self) -> str:
+        """RETURNS (str): ID/name of this entity in the KB"""
+        return self.kb.vocab.strings[self.entity_hash]
+
+    @property
+    def alias(self) -> int:
+        """RETURNS (uint64): hash of the alias"""
+        return self.alias_hash
+
+    @property
+    def alias_(self) -> str:
+        """RETURNS (str): ID of the original alias"""
+        return self.kb.vocab.strings[self.alias_hash]
+
+    @property
+    def entity_freq(self) -> float:
+        return self.entity_freq
+
+    @property
+    def entity_vector(self) -> Iterable[float]:
+        return self.entity_vector
+
+    @property
+    def prior_prob(self) -> float:
+        return self.prior_prob
+
+
+def get_candidates(kb: KnowledgeBase, mention: Span) -> Iterable[Candidate]:
+    """
+    Return candidate entities for a given mention and fetching appropriate entries from the index.
+    kb (KnowledgeBase): Knowledge base to query.
+    mention (Span): Entity mention for which to identify candidates.
+    RETURNS (Iterable[Candidate]): Identified candidates.
+    """
+    return kb.get_candidates(mention)
+
+
+def get_candidates_batch(kb: KnowledgeBase, mentions: Iterable[Span]) -> Iterable[Iterable[Candidate]]:
+    """
+    Return candidate entities for the given mentions and fetching appropriate entries from the index.
+    kb (KnowledgeBase): Knowledge base to query.
+    mention (Iterable[Span]): Entity mentions for which to identify candidates.
+    RETURNS (Iterable[Iterable[Candidate]]): Identified candidates.
+    """
+    return kb.get_candidates_batch(mentions)
diff --git a/spacy/kb/kb.pxd b/spacy/kb/kb.pxd
new file mode 100644
index 000000000..1adeef8ae
--- /dev/null
+++ b/spacy/kb/kb.pxd
@@ -0,0 +1,10 @@
+"""Knowledge-base for entity or concept linking."""
+
+from cymem.cymem cimport Pool
+from libc.stdint cimport int64_t
+from ..vocab cimport Vocab
+
+cdef class KnowledgeBase:
+    cdef Pool mem
+    cdef readonly Vocab vocab
+    cdef readonly int64_t entity_vector_length
diff --git a/spacy/kb/kb.pyx b/spacy/kb/kb.pyx
new file mode 100644
index 000000000..ce4bc0138
--- /dev/null
+++ b/spacy/kb/kb.pyx
@@ -0,0 +1,108 @@
+# cython: infer_types=True, profile=True
+
+from pathlib import Path
+from typing import Iterable, Tuple, Union
+from cymem.cymem cimport Pool
+
+from .candidate import Candidate
+from ..tokens import Span
+from ..util import SimpleFrozenList
+from ..errors import Errors
+
+
+cdef class KnowledgeBase:
+    """A `KnowledgeBase` instance stores unique identifiers for entities and their textual aliases,
+    to support entity linking of named entities to real-world concepts.
+    This is an abstract class and requires its operations to be implemented.
+
+    DOCS: https://spacy.io/api/kb
+    """
+
+    def __init__(self, vocab: Vocab, entity_vector_length: int):
+        """Create a KnowledgeBase."""
+        # Make sure abstract KB is not instantiated.
+        if self.__class__ == KnowledgeBase:
+            raise TypeError(
+                Errors.E1046.format(cls_name=self.__class__.__name__)
+            )
+
+        self.vocab = vocab
+        self.entity_vector_length = entity_vector_length
+        self.mem = Pool()
+
+    def get_candidates_batch(self, mentions: Iterable[Span]) -> Iterable[Iterable[Candidate]]:
+        """
+        Return candidate entities for specified texts. Each candidate defines the entity, the original alias,
+        and the prior probability of that alias resolving to that entity.
+        If no candidate is found for a given text, an empty list is returned.
+        mentions (Iterable[Span]): Mentions for which to get candidates.
+        RETURNS (Iterable[Iterable[Candidate]]): Identified candidates.
+        """
+        return [self.get_candidates(span) for span in mentions]
+
+    def get_candidates(self, mention: Span) -> Iterable[Candidate]:
+        """
+        Return candidate entities for specified text. Each candidate defines the entity, the original alias,
+        and the prior probability of that alias resolving to that entity.
+        If the no candidate is found for a given text, an empty list is returned.
+        mention (Span): Mention for which to get candidates.
+        RETURNS (Iterable[Candidate]): Identified candidates.
+        """
+        raise NotImplementedError(
+            Errors.E1045.format(parent="KnowledgeBase", method="get_candidates", name=self.__name__)
+        )
+
+    def get_vectors(self, entities: Iterable[str]) -> Iterable[Iterable[float]]:
+        """
+        Return vectors for entities.
+        entity (str): Entity name/ID.
+        RETURNS (Iterable[Iterable[float]]): Vectors for specified entities.
+        """
+        return [self.get_vector(entity) for entity in entities]
+
+    def get_vector(self, str entity) -> Iterable[float]:
+        """
+        Return vector for entity.
+        entity (str): Entity name/ID.
+        RETURNS (Iterable[float]): Vector for specified entity.
+        """
+        raise NotImplementedError(
+            Errors.E1045.format(parent="KnowledgeBase", method="get_vector", name=self.__name__)
+        )
+
+    def to_bytes(self, **kwargs) -> bytes:
+        """Serialize the current state to a binary string.
+        RETURNS (bytes): Current state as binary string.
+        """
+        raise NotImplementedError(
+            Errors.E1045.format(parent="KnowledgeBase", method="to_bytes", name=self.__name__)
+        )
+
+    def from_bytes(self, bytes_data: bytes, *, exclude: Tuple[str] = tuple()):
+        """Load state from a binary string.
+        bytes_data (bytes): KB state.
+        exclude (Tuple[str]): Properties to exclude when restoring KB.
+        """
+        raise NotImplementedError(
+            Errors.E1045.format(parent="KnowledgeBase", method="from_bytes", name=self.__name__)
+        )
+
+    def to_disk(self, path: Union[str, Path], exclude: Iterable[str] = SimpleFrozenList()) -> None:
+        """
+        Write KnowledgeBase content to disk.
+        path (Union[str, Path]): Target file path.
+        exclude (Iterable[str]): List of components to exclude.
+        """
+        raise NotImplementedError(
+            Errors.E1045.format(parent="KnowledgeBase", method="to_disk", name=self.__name__)
+        )
+
+    def from_disk(self, path: Union[str, Path], exclude: Iterable[str] = SimpleFrozenList()) -> None:
+        """
+        Load KnowledgeBase content from disk.
+        path (Union[str, Path]): Target file path.
+        exclude (Iterable[str]): List of components to exclude.
+        """
+        raise NotImplementedError(
+            Errors.E1045.format(parent="KnowledgeBase", method="from_disk", name=self.__name__)
+        )
diff --git a/spacy/kb.pxd b/spacy/kb/kb_in_memory.pxd
similarity index 92%
rename from spacy/kb.pxd
rename to spacy/kb/kb_in_memory.pxd
index a823dbe1e..825a6bde9 100644
--- a/spacy/kb.pxd
+++ b/spacy/kb/kb_in_memory.pxd
@@ -1,14 +1,12 @@
 """Knowledge-base for entity or concept linking."""
-from cymem.cymem cimport Pool
 from preshed.maps cimport PreshMap
 from libcpp.vector cimport vector
 from libc.stdint cimport int32_t, int64_t
 from libc.stdio cimport FILE
 
-from .vocab cimport Vocab
-from .typedefs cimport hash_t
-from .structs cimport KBEntryC, AliasC
-
+from ..typedefs cimport hash_t
+from ..structs cimport KBEntryC, AliasC
+from .kb cimport KnowledgeBase
 
 ctypedef vector[KBEntryC] entry_vec
 ctypedef vector[AliasC] alias_vec
@@ -16,21 +14,7 @@ ctypedef vector[float] float_vec
 ctypedef vector[float_vec] float_matrix
 
 
-# Object used by the Entity Linker that summarizes one entity-alias candidate combination.
-cdef class Candidate:
-    cdef readonly KnowledgeBase kb
-    cdef hash_t entity_hash
-    cdef float entity_freq
-    cdef vector[float] entity_vector
-    cdef hash_t alias_hash
-    cdef float prior_prob
-
-
-cdef class KnowledgeBase:
-    cdef Pool mem
-    cdef readonly Vocab vocab
-    cdef int64_t entity_vector_length
-
+cdef class InMemoryLookupKB(KnowledgeBase):
     # This maps 64bit keys (hash of unique entity string)
     # to 64bit values (position of the _KBEntryC struct in the _entries vector).
     # The PreshMap is pretty space efficient, as it uses open addressing. So
diff --git a/spacy/kb.pyx b/spacy/kb/kb_in_memory.pyx
similarity index 90%
rename from spacy/kb.pyx
rename to spacy/kb/kb_in_memory.pyx
index ae1983a8d..485e52c2f 100644
--- a/spacy/kb.pyx
+++ b/spacy/kb/kb_in_memory.pyx
@@ -1,8 +1,7 @@
 # cython: infer_types=True, profile=True
-from typing import Iterator, Iterable, Callable, Dict, Any
+from typing import Iterable, Callable, Dict, Any, Union
 
 import srsly
-from cymem.cymem cimport Pool
 from preshed.maps cimport PreshMap
 from cpython.exc cimport PyErr_SetFromErrno
 from libc.stdio cimport fopen, fclose, fread, fwrite, feof, fseek
@@ -12,85 +11,28 @@ from libcpp.vector cimport vector
 from pathlib import Path
 import warnings
 
-from .typedefs cimport hash_t
-from .errors import Errors, Warnings
-from . import util
-from .util import SimpleFrozenList, ensure_path
-
-cdef class Candidate:
-    """A `Candidate` object refers to a textual mention (`alias`) that may or may not be resolved
-    to a specific `entity` from a Knowledge Base. This will be used as input for the entity linking
-    algorithm which will disambiguate the various candidates to the correct one.
-    Each candidate (alias, entity) pair is assigned to a certain prior probability.
-
-    DOCS: https://spacy.io/api/kb/#candidate_init
-    """
-
-    def __init__(self, KnowledgeBase kb, entity_hash, entity_freq, entity_vector, alias_hash, prior_prob):
-        self.kb = kb
-        self.entity_hash = entity_hash
-        self.entity_freq = entity_freq
-        self.entity_vector = entity_vector
-        self.alias_hash = alias_hash
-        self.prior_prob = prior_prob
-
-    @property
-    def entity(self):
-        """RETURNS (uint64): hash of the entity's KB ID/name"""
-        return self.entity_hash
-
-    @property
-    def entity_(self):
-        """RETURNS (str): ID/name of this entity in the KB"""
-        return self.kb.vocab.strings[self.entity_hash]
-
-    @property
-    def alias(self):
-        """RETURNS (uint64): hash of the alias"""
-        return self.alias_hash
-
-    @property
-    def alias_(self):
-        """RETURNS (str): ID of the original alias"""
-        return self.kb.vocab.strings[self.alias_hash]
-
-    @property
-    def entity_freq(self):
-        return self.entity_freq
-
-    @property
-    def entity_vector(self):
-        return self.entity_vector
-
-    @property
-    def prior_prob(self):
-        return self.prior_prob
+from ..tokens import Span
+from ..typedefs cimport hash_t
+from ..errors import Errors, Warnings
+from .. import util
+from ..util import SimpleFrozenList, ensure_path
+from ..vocab cimport Vocab
+from .kb cimport KnowledgeBase
+from .candidate import Candidate as Candidate
 
 
-def get_candidates(KnowledgeBase kb, span) -> Iterator[Candidate]:
-    """
-    Return candidate entities for a given span by using the text of the span as the alias
-    and fetching appropriate entries from the index.
-    This particular function is optimized to work with the built-in KB functionality,
-    but any other custom candidate generation method can be used in combination with the KB as well.
-    """
-    return kb.get_alias_candidates(span.text)
-
-
-cdef class KnowledgeBase:
-    """A `KnowledgeBase` instance stores unique identifiers for entities and their textual aliases,
+cdef class InMemoryLookupKB(KnowledgeBase):
+    """An `InMemoryLookupKB` instance stores unique identifiers for entities and their textual aliases,
     to support entity linking of named entities to real-world concepts.
 
-    DOCS: https://spacy.io/api/kb
+    DOCS: https://spacy.io/api/kb_in_memory
     """
 
     def __init__(self, Vocab vocab, entity_vector_length):
-        """Create a KnowledgeBase."""
-        self.mem = Pool()
-        self.entity_vector_length = entity_vector_length
+        """Create an InMemoryLookupKB."""
+        super().__init__(vocab, entity_vector_length)
         self._entry_index = PreshMap()
         self._alias_index = PreshMap()
-        self.vocab = vocab
         self._create_empty_vectors(dummy_hash=self.vocab.strings[""])
 
     def _initialize_entities(self, int64_t nr_entities):
@@ -104,11 +46,6 @@ cdef class KnowledgeBase:
         self._alias_index = PreshMap(nr_aliases + 1)
         self._aliases_table = alias_vec(nr_aliases + 1)
 
-    @property
-    def entity_vector_length(self):
-        """RETURNS (uint64): length of the entity vectors"""
-        return self.entity_vector_length
-
     def __len__(self):
         return self.get_size_entities()
 
@@ -286,7 +223,10 @@ cdef class KnowledgeBase:
             alias_entry.probs = probs
             self._aliases_table[alias_index] = alias_entry
 
-    def get_alias_candidates(self, str alias) -> Iterator[Candidate]:
+    def get_candidates(self, mention: Span) -> Iterable[Candidate]:
+        return self.get_alias_candidates(mention.text)  # type: ignore
+
+    def get_alias_candidates(self, str alias) -> Iterable[Candidate]:
         """
         Return candidate entities for an alias. Each candidate defines the entity, the original alias,
         and the prior probability of that alias resolving to that entity.
diff --git a/spacy/ml/models/entity_linker.py b/spacy/ml/models/entity_linker.py
index d847342a3..4d18d216a 100644
--- a/spacy/ml/models/entity_linker.py
+++ b/spacy/ml/models/entity_linker.py
@@ -1,11 +1,12 @@
 from pathlib import Path
 from typing import Optional, Callable, Iterable, List, Tuple
 from thinc.types import Floats2d
-from thinc.api import chain, clone, list2ragged, reduce_mean, residual
-from thinc.api import Model, Maxout, Linear, noop, tuplify, Ragged
+from thinc.api import chain, list2ragged, reduce_mean, residual
+from thinc.api import Model, Maxout, Linear, tuplify, Ragged
 
 from ...util import registry
-from ...kb import KnowledgeBase, Candidate, get_candidates
+from ...kb import KnowledgeBase, InMemoryLookupKB
+from ...kb import Candidate, get_candidates, get_candidates_batch
 from ...vocab import Vocab
 from ...tokens import Span, Doc
 from ..extract_spans import extract_spans
@@ -78,9 +79,11 @@ def span_maker_forward(model, docs: List[Doc], is_train) -> Tuple[Ragged, Callab
 
 
 @registry.misc("spacy.KBFromFile.v1")
-def load_kb(kb_path: Path) -> Callable[[Vocab], KnowledgeBase]:
-    def kb_from_file(vocab):
-        kb = KnowledgeBase(vocab, entity_vector_length=1)
+def load_kb(
+    kb_path: Path,
+) -> Callable[[Vocab], KnowledgeBase]:
+    def kb_from_file(vocab: Vocab):
+        kb = InMemoryLookupKB(vocab, entity_vector_length=1)
         kb.from_disk(kb_path)
         return kb
 
@@ -88,9 +91,11 @@ def load_kb(kb_path: Path) -> Callable[[Vocab], KnowledgeBase]:
 
 
 @registry.misc("spacy.EmptyKB.v1")
-def empty_kb(entity_vector_length: int) -> Callable[[Vocab], KnowledgeBase]:
-    def empty_kb_factory(vocab):
-        return KnowledgeBase(vocab=vocab, entity_vector_length=entity_vector_length)
+def empty_kb(
+    entity_vector_length: int,
+) -> Callable[[Vocab], KnowledgeBase]:
+    def empty_kb_factory(vocab: Vocab):
+        return InMemoryLookupKB(vocab=vocab, entity_vector_length=entity_vector_length)
 
     return empty_kb_factory
 
@@ -98,3 +103,10 @@ def empty_kb(entity_vector_length: int) -> Callable[[Vocab], KnowledgeBase]:
 @registry.misc("spacy.CandidateGenerator.v1")
 def create_candidates() -> Callable[[KnowledgeBase, Span], Iterable[Candidate]]:
     return get_candidates
+
+
+@registry.misc("spacy.CandidateBatchGenerator.v1")
+def create_candidates_batch() -> Callable[
+    [KnowledgeBase, Iterable[Span]], Iterable[Iterable[Candidate]]
+]:
+    return get_candidates_batch
diff --git a/spacy/pipeline/entity_linker.py b/spacy/pipeline/entity_linker.py
index 73a90b268..62845287b 100644
--- a/spacy/pipeline/entity_linker.py
+++ b/spacy/pipeline/entity_linker.py
@@ -53,9 +53,11 @@ DEFAULT_NEL_MODEL = Config().from_str(default_model_config)["model"]
         "incl_context": True,
         "entity_vector_length": 64,
         "get_candidates": {"@misc": "spacy.CandidateGenerator.v1"},
+        "get_candidates_batch": {"@misc": "spacy.CandidateBatchGenerator.v1"},
         "overwrite": True,
         "scorer": {"@scorers": "spacy.entity_linker_scorer.v1"},
         "use_gold_ents": True,
+        "candidates_batch_size": 1,
         "threshold": None,
     },
     default_score_weights={
@@ -75,9 +77,13 @@ def make_entity_linker(
     incl_context: bool,
     entity_vector_length: int,
     get_candidates: Callable[[KnowledgeBase, Span], Iterable[Candidate]],
+    get_candidates_batch: Callable[
+        [KnowledgeBase, Iterable[Span]], Iterable[Iterable[Candidate]]
+    ],
     overwrite: bool,
     scorer: Optional[Callable],
     use_gold_ents: bool,
+    candidates_batch_size: int,
     threshold: Optional[float] = None,
 ):
     """Construct an EntityLinker component.
@@ -90,17 +96,21 @@ def make_entity_linker(
     incl_prior (bool): Whether or not to include prior probabilities from the KB in the model.
     incl_context (bool): Whether or not to include the local context in the model.
     entity_vector_length (int): Size of encoding vectors in the KB.
-    get_candidates (Callable[[KnowledgeBase, "Span"], Iterable[Candidate]]): Function that
+    get_candidates (Callable[[KnowledgeBase, Span], Iterable[Candidate]]): Function that
         produces a list of candidates, given a certain knowledge base and a textual mention.
+    get_candidates_batch (
+        Callable[[KnowledgeBase, Iterable[Span]], Iterable[Iterable[Candidate]]], Iterable[Candidate]]
+        ): Function that produces a list of candidates, given a certain knowledge base and several textual mentions.
     scorer (Optional[Callable]): The scoring method.
     use_gold_ents (bool): Whether to copy entities from gold docs or not. If false, another
         component must provide entity annotations.
+    candidates_batch_size (int): Size of batches for entity candidate generation.
     threshold (Optional[float]): Confidence threshold for entity predictions. If confidence is below the threshold,
         prediction is discarded. If None, predictions are not filtered by any threshold.
     """
 
     if not model.attrs.get("include_span_maker", False):
-        # The only difference in arguments here is that use_gold_ents is not available
+        # The only difference in arguments here is that use_gold_ents and threshold aren't available.
         return EntityLinker_v1(
             nlp.vocab,
             model,
@@ -124,9 +134,11 @@ def make_entity_linker(
         incl_context=incl_context,
         entity_vector_length=entity_vector_length,
         get_candidates=get_candidates,
+        get_candidates_batch=get_candidates_batch,
         overwrite=overwrite,
         scorer=scorer,
         use_gold_ents=use_gold_ents,
+        candidates_batch_size=candidates_batch_size,
         threshold=threshold,
     )
 
@@ -160,9 +172,13 @@ class EntityLinker(TrainablePipe):
         incl_context: bool,
         entity_vector_length: int,
         get_candidates: Callable[[KnowledgeBase, Span], Iterable[Candidate]],
+        get_candidates_batch: Callable[
+            [KnowledgeBase, Iterable[Span]], Iterable[Iterable[Candidate]]
+        ],
         overwrite: bool = BACKWARD_OVERWRITE,
         scorer: Optional[Callable] = entity_linker_score,
         use_gold_ents: bool,
+        candidates_batch_size: int,
         threshold: Optional[float] = None,
     ) -> None:
         """Initialize an entity linker.
@@ -178,10 +194,14 @@ class EntityLinker(TrainablePipe):
         entity_vector_length (int): Size of encoding vectors in the KB.
         get_candidates (Callable[[KnowledgeBase, Span], Iterable[Candidate]]): Function that
             produces a list of candidates, given a certain knowledge base and a textual mention.
-        scorer (Optional[Callable]): The scoring method. Defaults to
-            Scorer.score_links.
+        get_candidates_batch (
+            Callable[[KnowledgeBase, Iterable[Span]], Iterable[Iterable[Candidate]]],
+            Iterable[Candidate]]
+            ): Function that produces a list of candidates, given a certain knowledge base and several textual mentions.
+        scorer (Optional[Callable]): The scoring method. Defaults to Scorer.score_links.
         use_gold_ents (bool): Whether to copy entities from gold docs or not. If false, another
             component must provide entity annotations.
+        candidates_batch_size (int): Size of batches for entity candidate generation.
         threshold (Optional[float]): Confidence threshold for entity predictions. If confidence is below the
             threshold, prediction is discarded. If None, predictions are not filtered by any threshold.
         DOCS: https://spacy.io/api/entitylinker#init
@@ -204,22 +224,27 @@ class EntityLinker(TrainablePipe):
         self.incl_prior = incl_prior
         self.incl_context = incl_context
         self.get_candidates = get_candidates
+        self.get_candidates_batch = get_candidates_batch
         self.cfg: Dict[str, Any] = {"overwrite": overwrite}
         self.distance = CosineDistance(normalize=False)
         # how many neighbour sentences to take into account
-        # create an empty KB by default. If you want to load a predefined one, specify it in 'initialize'.
+        # create an empty KB by default
         self.kb = empty_kb(entity_vector_length)(self.vocab)
         self.scorer = scorer
         self.use_gold_ents = use_gold_ents
+        self.candidates_batch_size = candidates_batch_size
         self.threshold = threshold
 
+        if candidates_batch_size < 1:
+            raise ValueError(Errors.E1044)
+
     def set_kb(self, kb_loader: Callable[[Vocab], KnowledgeBase]):
         """Define the KB of this pipe by providing a function that will
         create it using this object's vocab."""
         if not callable(kb_loader):
             raise ValueError(Errors.E885.format(arg_type=type(kb_loader)))
 
-        self.kb = kb_loader(self.vocab)
+        self.kb = kb_loader(self.vocab)  # type: ignore
 
     def validate_kb(self) -> None:
         # Raise an error if the knowledge base is not initialized.
@@ -241,8 +266,8 @@ class EntityLinker(TrainablePipe):
         get_examples (Callable[[], Iterable[Example]]): Function that
             returns a representative sample of gold-standard Example objects.
         nlp (Language): The current nlp object the component is part of.
-        kb_loader (Callable[[Vocab], KnowledgeBase]): A function that creates a KnowledgeBase from a Vocab instance.
-            Note that providing this argument, will overwrite all data accumulated in the current KB.
+        kb_loader (Callable[[Vocab], KnowledgeBase]): A function that creates a KnowledgeBase from a Vocab
+            instance. Note that providing this argument will overwrite all data accumulated in the current KB.
             Use this only when loading a KB as-such from file.
 
         DOCS: https://spacy.io/api/entitylinker#initialize
@@ -419,66 +444,93 @@ class EntityLinker(TrainablePipe):
             if len(doc) == 0:
                 continue
             sentences = [s for s in doc.sents]
-            # Looping through each entity (TODO: rewrite)
-            for ent in doc.ents:
-                sent_index = sentences.index(ent.sent)
-                assert sent_index >= 0
 
-                if self.incl_context:
-                    # get n_neighbour sentences, clipped to the length of the document
-                    start_sentence = max(0, sent_index - self.n_sents)
-                    end_sentence = min(len(sentences) - 1, sent_index + self.n_sents)
-                    start_token = sentences[start_sentence].start
-                    end_token = sentences[end_sentence].end
-                    sent_doc = doc[start_token:end_token].as_doc()
-                    # currently, the context is the same for each entity in a sentence (should be refined)
-                    sentence_encoding = self.model.predict([sent_doc])[0]
-                    sentence_encoding_t = sentence_encoding.T
-                    sentence_norm = xp.linalg.norm(sentence_encoding_t)
-                entity_count += 1
-                if ent.label_ in self.labels_discard:
-                    # ignoring this entity - setting to NIL
-                    final_kb_ids.append(self.NIL)
-                else:
-                    candidates = list(self.get_candidates(self.kb, ent))
-                    if not candidates:
-                        # no prediction possible for this entity - setting to NIL
-                        final_kb_ids.append(self.NIL)
-                    elif len(candidates) == 1 and self.threshold is None:
-                        # shortcut for efficiency reasons: take the 1 candidate
-                        final_kb_ids.append(candidates[0].entity_)
-                    else:
-                        random.shuffle(candidates)
-                        # set all prior probabilities to 0 if incl_prior=False
-                        prior_probs = xp.asarray([c.prior_prob for c in candidates])
-                        if not self.incl_prior:
-                            prior_probs = xp.asarray([0.0 for _ in candidates])
-                        scores = prior_probs
-                        # add in similarity from the context
-                        if self.incl_context:
-                            entity_encodings = xp.asarray(
-                                [c.entity_vector for c in candidates]
-                            )
-                            entity_norm = xp.linalg.norm(entity_encodings, axis=1)
-                            if len(entity_encodings) != len(prior_probs):
-                                raise RuntimeError(
-                                    Errors.E147.format(
-                                        method="predict",
-                                        msg="vectors not of equal length",
-                                    )
-                                )
-                            # cosine similarity
-                            sims = xp.dot(entity_encodings, sentence_encoding_t) / (
-                                sentence_norm * entity_norm
-                            )
-                            if sims.shape != prior_probs.shape:
-                                raise ValueError(Errors.E161)
-                            scores = prior_probs + sims - (prior_probs * sims)
-                        final_kb_ids.append(
-                            candidates[scores.argmax().item()].entity_
-                            if self.threshold is None or scores.max() >= self.threshold
-                            else EntityLinker.NIL
+            # Loop over entities in batches.
+            for ent_idx in range(0, len(doc.ents), self.candidates_batch_size):
+                ent_batch = doc.ents[ent_idx : ent_idx + self.candidates_batch_size]
+
+                # Look up candidate entities.
+                valid_ent_idx = [
+                    idx
+                    for idx in range(len(ent_batch))
+                    if ent_batch[idx].label_ not in self.labels_discard
+                ]
+
+                batch_candidates = list(
+                    self.get_candidates_batch(
+                        self.kb, [ent_batch[idx] for idx in valid_ent_idx]
+                    )
+                    if self.candidates_batch_size > 1
+                    else [
+                        self.get_candidates(self.kb, ent_batch[idx])
+                        for idx in valid_ent_idx
+                    ]
+                )
+
+                # Looping through each entity in batch (TODO: rewrite)
+                for j, ent in enumerate(ent_batch):
+                    sent_index = sentences.index(ent.sent)
+                    assert sent_index >= 0
+
+                    if self.incl_context:
+                        # get n_neighbour sentences, clipped to the length of the document
+                        start_sentence = max(0, sent_index - self.n_sents)
+                        end_sentence = min(
+                            len(sentences) - 1, sent_index + self.n_sents
                         )
+                        start_token = sentences[start_sentence].start
+                        end_token = sentences[end_sentence].end
+                        sent_doc = doc[start_token:end_token].as_doc()
+                        # currently, the context is the same for each entity in a sentence (should be refined)
+                        sentence_encoding = self.model.predict([sent_doc])[0]
+                        sentence_encoding_t = sentence_encoding.T
+                        sentence_norm = xp.linalg.norm(sentence_encoding_t)
+                    entity_count += 1
+                    if ent.label_ in self.labels_discard:
+                        # ignoring this entity - setting to NIL
+                        final_kb_ids.append(self.NIL)
+                    else:
+                        candidates = list(batch_candidates[j])
+                        if not candidates:
+                            # no prediction possible for this entity - setting to NIL
+                            final_kb_ids.append(self.NIL)
+                        elif len(candidates) == 1 and self.threshold is None:
+                            # shortcut for efficiency reasons: take the 1 candidate
+                            final_kb_ids.append(candidates[0].entity_)
+                        else:
+                            random.shuffle(candidates)
+                            # set all prior probabilities to 0 if incl_prior=False
+                            prior_probs = xp.asarray([c.prior_prob for c in candidates])
+                            if not self.incl_prior:
+                                prior_probs = xp.asarray([0.0 for _ in candidates])
+                            scores = prior_probs
+                            # add in similarity from the context
+                            if self.incl_context:
+                                entity_encodings = xp.asarray(
+                                    [c.entity_vector for c in candidates]
+                                )
+                                entity_norm = xp.linalg.norm(entity_encodings, axis=1)
+                                if len(entity_encodings) != len(prior_probs):
+                                    raise RuntimeError(
+                                        Errors.E147.format(
+                                            method="predict",
+                                            msg="vectors not of equal length",
+                                        )
+                                    )
+                                # cosine similarity
+                                sims = xp.dot(entity_encodings, sentence_encoding_t) / (
+                                    sentence_norm * entity_norm
+                                )
+                                if sims.shape != prior_probs.shape:
+                                    raise ValueError(Errors.E161)
+                                scores = prior_probs + sims - (prior_probs * sims)
+                            final_kb_ids.append(
+                                candidates[scores.argmax().item()].entity_
+                                if self.threshold is None
+                                or scores.max() >= self.threshold
+                                else EntityLinker.NIL
+                            )
+
         if not (len(final_kb_ids) == entity_count):
             err = Errors.E147.format(
                 method="predict", msg="result variables not of equal length"
diff --git a/spacy/pipeline/legacy/entity_linker.py b/spacy/pipeline/legacy/entity_linker.py
index 2f8a1f8ea..c14dfa1db 100644
--- a/spacy/pipeline/legacy/entity_linker.py
+++ b/spacy/pipeline/legacy/entity_linker.py
@@ -68,8 +68,7 @@ class EntityLinker_v1(TrainablePipe):
         entity_vector_length (int): Size of encoding vectors in the KB.
         get_candidates (Callable[[KnowledgeBase, Span], Iterable[Candidate]]): Function that
             produces a list of candidates, given a certain knowledge base and a textual mention.
-        scorer (Optional[Callable]): The scoring method. Defaults to
-            Scorer.score_links.
+        scorer (Optional[Callable]): The scoring method. Defaults to Scorer.score_links.
         DOCS: https://spacy.io/api/entitylinker#init
         """
         self.vocab = vocab
@@ -115,7 +114,7 @@ class EntityLinker_v1(TrainablePipe):
         get_examples (Callable[[], Iterable[Example]]): Function that
             returns a representative sample of gold-standard Example objects.
         nlp (Language): The current nlp object the component is part of.
-        kb_loader (Callable[[Vocab], KnowledgeBase]): A function that creates a KnowledgeBase from a Vocab instance.
+        kb_loader (Callable[[Vocab], KnowledgeBase]): A function that creates an InMemoryLookupKB from a Vocab instance.
             Note that providing this argument, will overwrite all data accumulated in the current KB.
             Use this only when loading a KB as-such from file.
 
diff --git a/spacy/tests/pipeline/test_entity_linker.py b/spacy/tests/pipeline/test_entity_linker.py
index 82bc976bb..4d683acc5 100644
--- a/spacy/tests/pipeline/test_entity_linker.py
+++ b/spacy/tests/pipeline/test_entity_linker.py
@@ -6,7 +6,7 @@ from numpy.testing import assert_equal
 from spacy import registry, util
 from spacy.attrs import ENT_KB_ID
 from spacy.compat import pickle
-from spacy.kb import Candidate, KnowledgeBase, get_candidates
+from spacy.kb import Candidate, InMemoryLookupKB, get_candidates, KnowledgeBase
 from spacy.lang.en import English
 from spacy.ml import load_kb
 from spacy.pipeline import EntityLinker
@@ -34,7 +34,7 @@ def assert_almost_equal(a, b):
 def test_issue4674():
     """Test that setting entities with overlapping identifiers does not mess up IO"""
     nlp = English()
-    kb = KnowledgeBase(nlp.vocab, entity_vector_length=3)
+    kb = InMemoryLookupKB(nlp.vocab, entity_vector_length=3)
     vector1 = [0.9, 1.1, 1.01]
     vector2 = [1.8, 2.25, 2.01]
     with pytest.warns(UserWarning):
@@ -51,7 +51,7 @@ def test_issue4674():
             dir_path.mkdir()
         file_path = dir_path / "kb"
         kb.to_disk(str(file_path))
-        kb2 = KnowledgeBase(nlp.vocab, entity_vector_length=3)
+        kb2 = InMemoryLookupKB(nlp.vocab, entity_vector_length=3)
         kb2.from_disk(str(file_path))
     assert kb2.get_size_entities() == 1
 
@@ -59,9 +59,9 @@ def test_issue4674():
 @pytest.mark.issue(6730)
 def test_issue6730(en_vocab):
     """Ensure that the KB does not accept empty strings, but otherwise IO works fine."""
-    from spacy.kb import KnowledgeBase
+    from spacy.kb.kb_in_memory import InMemoryLookupKB
 
-    kb = KnowledgeBase(en_vocab, entity_vector_length=3)
+    kb = InMemoryLookupKB(en_vocab, entity_vector_length=3)
     kb.add_entity(entity="1", freq=148, entity_vector=[1, 2, 3])
 
     with pytest.raises(ValueError):
@@ -127,7 +127,7 @@ def test_issue7065_b():
 
     def create_kb(vocab):
         # create artificial KB
-        mykb = KnowledgeBase(vocab, entity_vector_length=vector_length)
+        mykb = InMemoryLookupKB(vocab, entity_vector_length=vector_length)
         mykb.add_entity(entity="Q270853", freq=12, entity_vector=[9, 1, -7])
         mykb.add_alias(
             alias="No. 8",
@@ -190,7 +190,7 @@ def test_no_entities():
 
     def create_kb(vocab):
         # create artificial KB
-        mykb = KnowledgeBase(vocab, entity_vector_length=vector_length)
+        mykb = InMemoryLookupKB(vocab, entity_vector_length=vector_length)
         mykb.add_entity(entity="Q2146908", freq=12, entity_vector=[6, -4, 3])
         mykb.add_alias("Russ Cochran", ["Q2146908"], [0.9])
         return mykb
@@ -231,7 +231,7 @@ def test_partial_links():
 
     def create_kb(vocab):
         # create artificial KB
-        mykb = KnowledgeBase(vocab, entity_vector_length=vector_length)
+        mykb = InMemoryLookupKB(vocab, entity_vector_length=vector_length)
         mykb.add_entity(entity="Q2146908", freq=12, entity_vector=[6, -4, 3])
         mykb.add_alias("Russ Cochran", ["Q2146908"], [0.9])
         return mykb
@@ -263,7 +263,7 @@ def test_partial_links():
 
 def test_kb_valid_entities(nlp):
     """Test the valid construction of a KB with 3 entities and two aliases"""
-    mykb = KnowledgeBase(nlp.vocab, entity_vector_length=3)
+    mykb = InMemoryLookupKB(nlp.vocab, entity_vector_length=3)
 
     # adding entities
     mykb.add_entity(entity="Q1", freq=19, entity_vector=[8, 4, 3])
@@ -292,7 +292,7 @@ def test_kb_valid_entities(nlp):
 
 def test_kb_invalid_entities(nlp):
     """Test the invalid construction of a KB with an alias linked to a non-existing entity"""
-    mykb = KnowledgeBase(nlp.vocab, entity_vector_length=1)
+    mykb = InMemoryLookupKB(nlp.vocab, entity_vector_length=1)
 
     # adding entities
     mykb.add_entity(entity="Q1", freq=19, entity_vector=[1])
@@ -308,7 +308,7 @@ def test_kb_invalid_entities(nlp):
 
 def test_kb_invalid_probabilities(nlp):
     """Test the invalid construction of a KB with wrong prior probabilities"""
-    mykb = KnowledgeBase(nlp.vocab, entity_vector_length=1)
+    mykb = InMemoryLookupKB(nlp.vocab, entity_vector_length=1)
 
     # adding entities
     mykb.add_entity(entity="Q1", freq=19, entity_vector=[1])
@@ -322,7 +322,7 @@ def test_kb_invalid_probabilities(nlp):
 
 def test_kb_invalid_combination(nlp):
     """Test the invalid construction of a KB with non-matching entity and probability lists"""
-    mykb = KnowledgeBase(nlp.vocab, entity_vector_length=1)
+    mykb = InMemoryLookupKB(nlp.vocab, entity_vector_length=1)
 
     # adding entities
     mykb.add_entity(entity="Q1", freq=19, entity_vector=[1])
@@ -338,7 +338,7 @@ def test_kb_invalid_combination(nlp):
 
 def test_kb_invalid_entity_vector(nlp):
     """Test the invalid construction of a KB with non-matching entity vector lengths"""
-    mykb = KnowledgeBase(nlp.vocab, entity_vector_length=3)
+    mykb = InMemoryLookupKB(nlp.vocab, entity_vector_length=3)
 
     # adding entities
     mykb.add_entity(entity="Q1", freq=19, entity_vector=[1, 2, 3])
@@ -376,7 +376,7 @@ def test_kb_initialize_empty(nlp):
 
 def test_kb_serialize(nlp):
     """Test serialization of the KB"""
-    mykb = KnowledgeBase(nlp.vocab, entity_vector_length=1)
+    mykb = InMemoryLookupKB(nlp.vocab, entity_vector_length=1)
     with make_tempdir() as d:
         # normal read-write behaviour
         mykb.to_disk(d / "kb")
@@ -393,12 +393,12 @@ def test_kb_serialize(nlp):
 @pytest.mark.issue(9137)
 def test_kb_serialize_2(nlp):
     v = [5, 6, 7, 8]
-    kb1 = KnowledgeBase(vocab=nlp.vocab, entity_vector_length=4)
+    kb1 = InMemoryLookupKB(vocab=nlp.vocab, entity_vector_length=4)
     kb1.set_entities(["E1"], [1], [v])
     assert kb1.get_vector("E1") == v
     with make_tempdir() as d:
         kb1.to_disk(d / "kb")
-        kb2 = KnowledgeBase(vocab=nlp.vocab, entity_vector_length=4)
+        kb2 = InMemoryLookupKB(vocab=nlp.vocab, entity_vector_length=4)
         kb2.from_disk(d / "kb")
         assert kb2.get_vector("E1") == v
 
@@ -408,7 +408,7 @@ def test_kb_set_entities(nlp):
     v = [5, 6, 7, 8]
     v1 = [1, 1, 1, 0]
     v2 = [2, 2, 2, 3]
-    kb1 = KnowledgeBase(vocab=nlp.vocab, entity_vector_length=4)
+    kb1 = InMemoryLookupKB(vocab=nlp.vocab, entity_vector_length=4)
     kb1.set_entities(["E0"], [1], [v])
     assert kb1.get_entity_strings() == ["E0"]
     kb1.set_entities(["E1", "E2"], [1, 9], [v1, v2])
@@ -417,7 +417,7 @@ def test_kb_set_entities(nlp):
     assert kb1.get_vector("E2") == v2
     with make_tempdir() as d:
         kb1.to_disk(d / "kb")
-        kb2 = KnowledgeBase(vocab=nlp.vocab, entity_vector_length=4)
+        kb2 = InMemoryLookupKB(vocab=nlp.vocab, entity_vector_length=4)
         kb2.from_disk(d / "kb")
         assert set(kb2.get_entity_strings()) == {"E1", "E2"}
         assert kb2.get_vector("E1") == v1
@@ -428,7 +428,7 @@ def test_kb_serialize_vocab(nlp):
     """Test serialization of the KB and custom strings"""
     entity = "MyFunnyID"
     assert entity not in nlp.vocab.strings
-    mykb = KnowledgeBase(nlp.vocab, entity_vector_length=1)
+    mykb = InMemoryLookupKB(nlp.vocab, entity_vector_length=1)
     assert not mykb.contains_entity(entity)
     mykb.add_entity(entity, freq=342, entity_vector=[3])
     assert mykb.contains_entity(entity)
@@ -436,14 +436,14 @@ def test_kb_serialize_vocab(nlp):
     with make_tempdir() as d:
         # normal read-write behaviour
         mykb.to_disk(d / "kb")
-        mykb_new = KnowledgeBase(Vocab(), entity_vector_length=1)
+        mykb_new = InMemoryLookupKB(Vocab(), entity_vector_length=1)
         mykb_new.from_disk(d / "kb")
         assert entity in mykb_new.vocab.strings
 
 
 def test_candidate_generation(nlp):
     """Test correct candidate generation"""
-    mykb = KnowledgeBase(nlp.vocab, entity_vector_length=1)
+    mykb = InMemoryLookupKB(nlp.vocab, entity_vector_length=1)
     doc = nlp("douglas adam Adam shrubbery")
 
     douglas_ent = doc[0:1]
@@ -481,7 +481,7 @@ def test_el_pipe_configuration(nlp):
     ruler.add_patterns([pattern])
 
     def create_kb(vocab):
-        kb = KnowledgeBase(vocab, entity_vector_length=1)
+        kb = InMemoryLookupKB(vocab, entity_vector_length=1)
         kb.add_entity(entity="Q2", freq=12, entity_vector=[2])
         kb.add_entity(entity="Q3", freq=5, entity_vector=[3])
         kb.add_alias(alias="douglas", entities=["Q2", "Q3"], probabilities=[0.8, 0.1])
@@ -500,10 +500,21 @@ def test_el_pipe_configuration(nlp):
     def get_lowercased_candidates(kb, span):
         return kb.get_alias_candidates(span.text.lower())
 
+    def get_lowercased_candidates_batch(kb, spans):
+        return [get_lowercased_candidates(kb, span) for span in spans]
+
     @registry.misc("spacy.LowercaseCandidateGenerator.v1")
-    def create_candidates() -> Callable[[KnowledgeBase, "Span"], Iterable[Candidate]]:
+    def create_candidates() -> Callable[
+        [InMemoryLookupKB, "Span"], Iterable[Candidate]
+    ]:
         return get_lowercased_candidates
 
+    @registry.misc("spacy.LowercaseCandidateBatchGenerator.v1")
+    def create_candidates_batch() -> Callable[
+        [InMemoryLookupKB, Iterable["Span"]], Iterable[Iterable[Candidate]]
+    ]:
+        return get_lowercased_candidates_batch
+
     # replace the pipe with a new one with with a different candidate generator
     entity_linker = nlp.replace_pipe(
         "entity_linker",
@@ -511,6 +522,9 @@ def test_el_pipe_configuration(nlp):
         config={
             "incl_context": False,
             "get_candidates": {"@misc": "spacy.LowercaseCandidateGenerator.v1"},
+            "get_candidates_batch": {
+                "@misc": "spacy.LowercaseCandidateBatchGenerator.v1"
+            },
         },
     )
     entity_linker.set_kb(create_kb)
@@ -532,7 +546,7 @@ def test_nel_nsents(nlp):
 
 def test_vocab_serialization(nlp):
     """Test that string information is retained across storage"""
-    mykb = KnowledgeBase(nlp.vocab, entity_vector_length=1)
+    mykb = InMemoryLookupKB(nlp.vocab, entity_vector_length=1)
 
     # adding entities
     mykb.add_entity(entity="Q1", freq=27, entity_vector=[1])
@@ -552,7 +566,7 @@ def test_vocab_serialization(nlp):
 
     with make_tempdir() as d:
         mykb.to_disk(d / "kb")
-        kb_new_vocab = KnowledgeBase(Vocab(), entity_vector_length=1)
+        kb_new_vocab = InMemoryLookupKB(Vocab(), entity_vector_length=1)
         kb_new_vocab.from_disk(d / "kb")
 
         candidates = kb_new_vocab.get_alias_candidates("adam")
@@ -568,7 +582,7 @@ def test_vocab_serialization(nlp):
 
 def test_append_alias(nlp):
     """Test that we can append additional alias-entity pairs"""
-    mykb = KnowledgeBase(nlp.vocab, entity_vector_length=1)
+    mykb = InMemoryLookupKB(nlp.vocab, entity_vector_length=1)
 
     # adding entities
     mykb.add_entity(entity="Q1", freq=27, entity_vector=[1])
@@ -599,7 +613,7 @@ def test_append_alias(nlp):
 @pytest.mark.filterwarnings("ignore:\\[W036")
 def test_append_invalid_alias(nlp):
     """Test that append an alias will throw an error if prior probs are exceeding 1"""
-    mykb = KnowledgeBase(nlp.vocab, entity_vector_length=1)
+    mykb = InMemoryLookupKB(nlp.vocab, entity_vector_length=1)
 
     # adding entities
     mykb.add_entity(entity="Q1", freq=27, entity_vector=[1])
@@ -621,7 +635,7 @@ def test_preserving_links_asdoc(nlp):
     vector_length = 1
 
     def create_kb(vocab):
-        mykb = KnowledgeBase(vocab, entity_vector_length=vector_length)
+        mykb = InMemoryLookupKB(vocab, entity_vector_length=vector_length)
         # adding entities
         mykb.add_entity(entity="Q1", freq=19, entity_vector=[1])
         mykb.add_entity(entity="Q2", freq=8, entity_vector=[1])
@@ -723,7 +737,7 @@ def test_overfitting_IO():
         # create artificial KB - assign same prior weight to the two russ cochran's
         # Q2146908 (Russ Cochran): American golfer
         # Q7381115 (Russ Cochran): publisher
-        mykb = KnowledgeBase(vocab, entity_vector_length=vector_length)
+        mykb = InMemoryLookupKB(vocab, entity_vector_length=vector_length)
         mykb.add_entity(entity="Q2146908", freq=12, entity_vector=[6, -4, 3])
         mykb.add_entity(entity="Q7381115", freq=12, entity_vector=[9, 1, -7])
         mykb.add_alias(
@@ -805,7 +819,7 @@ def test_kb_serialization():
         kb_dir = tmp_dir / "kb"
         nlp1 = English()
         assert "Q2146908" not in nlp1.vocab.strings
-        mykb = KnowledgeBase(nlp1.vocab, entity_vector_length=vector_length)
+        mykb = InMemoryLookupKB(nlp1.vocab, entity_vector_length=vector_length)
         mykb.add_entity(entity="Q2146908", freq=12, entity_vector=[6, -4, 3])
         mykb.add_alias(alias="Russ Cochran", entities=["Q2146908"], probabilities=[0.8])
         assert "Q2146908" in nlp1.vocab.strings
@@ -828,7 +842,7 @@ def test_kb_serialization():
 def test_kb_pickle():
     # Test that the KB can be pickled
     nlp = English()
-    kb_1 = KnowledgeBase(nlp.vocab, entity_vector_length=3)
+    kb_1 = InMemoryLookupKB(nlp.vocab, entity_vector_length=3)
     kb_1.add_entity(entity="Q2146908", freq=12, entity_vector=[6, -4, 3])
     assert not kb_1.contains_alias("Russ Cochran")
     kb_1.add_alias(alias="Russ Cochran", entities=["Q2146908"], probabilities=[0.8])
@@ -842,7 +856,7 @@ def test_kb_pickle():
 def test_nel_pickle():
     # Test that a pipeline with an EL component can be pickled
     def create_kb(vocab):
-        kb = KnowledgeBase(vocab, entity_vector_length=3)
+        kb = InMemoryLookupKB(vocab, entity_vector_length=3)
         kb.add_entity(entity="Q2146908", freq=12, entity_vector=[6, -4, 3])
         kb.add_alias(alias="Russ Cochran", entities=["Q2146908"], probabilities=[0.8])
         return kb
@@ -864,7 +878,7 @@ def test_nel_pickle():
 def test_kb_to_bytes():
     # Test that the KB's to_bytes method works correctly
     nlp = English()
-    kb_1 = KnowledgeBase(nlp.vocab, entity_vector_length=3)
+    kb_1 = InMemoryLookupKB(nlp.vocab, entity_vector_length=3)
     kb_1.add_entity(entity="Q2146908", freq=12, entity_vector=[6, -4, 3])
     kb_1.add_entity(entity="Q66", freq=9, entity_vector=[1, 2, 3])
     kb_1.add_alias(alias="Russ Cochran", entities=["Q2146908"], probabilities=[0.8])
@@ -874,7 +888,7 @@ def test_kb_to_bytes():
     )
     assert kb_1.contains_alias("Russ Cochran")
     kb_bytes = kb_1.to_bytes()
-    kb_2 = KnowledgeBase(nlp.vocab, entity_vector_length=3)
+    kb_2 = InMemoryLookupKB(nlp.vocab, entity_vector_length=3)
     assert not kb_2.contains_alias("Russ Cochran")
     kb_2 = kb_2.from_bytes(kb_bytes)
     # check that both KBs are exactly the same
@@ -897,7 +911,7 @@ def test_kb_to_bytes():
 def test_nel_to_bytes():
     # Test that a pipeline with an EL component can be converted to bytes
     def create_kb(vocab):
-        kb = KnowledgeBase(vocab, entity_vector_length=3)
+        kb = InMemoryLookupKB(vocab, entity_vector_length=3)
         kb.add_entity(entity="Q2146908", freq=12, entity_vector=[6, -4, 3])
         kb.add_alias(alias="Russ Cochran", entities=["Q2146908"], probabilities=[0.8])
         return kb
@@ -987,7 +1001,7 @@ def test_legacy_architectures(name, config):
         train_examples.append(Example.from_dict(doc, annotation))
 
     def create_kb(vocab):
-        mykb = KnowledgeBase(vocab, entity_vector_length=vector_length)
+        mykb = InMemoryLookupKB(vocab, entity_vector_length=vector_length)
         mykb.add_entity(entity="Q2146908", freq=12, entity_vector=[6, -4, 3])
         mykb.add_entity(entity="Q7381115", freq=12, entity_vector=[9, 1, -7])
         mykb.add_alias(
@@ -1054,7 +1068,7 @@ def test_no_gold_ents(patterns):
 
     def create_kb(vocab):
         # create artificial KB
-        mykb = KnowledgeBase(vocab, entity_vector_length=vector_length)
+        mykb = InMemoryLookupKB(vocab, entity_vector_length=vector_length)
         mykb.add_entity(entity="Q613241", freq=12, entity_vector=[6, -4, 3])
         mykb.add_alias("Kirby", ["Q613241"], [0.9])
         # Placeholder
@@ -1104,7 +1118,7 @@ def test_tokenization_mismatch():
 
     def create_kb(vocab):
         # create placeholder KB
-        mykb = KnowledgeBase(vocab, entity_vector_length=vector_length)
+        mykb = InMemoryLookupKB(vocab, entity_vector_length=vector_length)
         mykb.add_entity(entity="Q613241", freq=12, entity_vector=[6, -4, 3])
         mykb.add_alias("Kirby", ["Q613241"], [0.9])
         return mykb
@@ -1121,6 +1135,12 @@ def test_tokenization_mismatch():
     nlp.evaluate(train_examples)
 
 
+def test_abstract_kb_instantiation():
+    """Test whether instantiation of abstract KB base class fails."""
+    with pytest.raises(TypeError):
+        KnowledgeBase(None, 3)
+
+
 # fmt: off
 @pytest.mark.parametrize(
     "meet_threshold,config",
@@ -1151,7 +1171,7 @@ def test_threshold(meet_threshold: bool, config: Dict[str, Any]):
 
     def create_kb(vocab):
         # create artificial KB
-        mykb = KnowledgeBase(vocab, entity_vector_length=3)
+        mykb = InMemoryLookupKB(vocab, entity_vector_length=3)
         mykb.add_entity(entity=entity_id, freq=12, entity_vector=[6, -4, 3])
         mykb.add_alias(
             alias="Mahler",
diff --git a/spacy/tests/serialize/test_resource_warning.py b/spacy/tests/serialize/test_resource_warning.py
index a00b2a688..38701c6d9 100644
--- a/spacy/tests/serialize/test_resource_warning.py
+++ b/spacy/tests/serialize/test_resource_warning.py
@@ -3,7 +3,7 @@ from unittest import TestCase
 import pytest
 import srsly
 from numpy import zeros
-from spacy.kb import KnowledgeBase, Writer
+from spacy.kb.kb_in_memory import InMemoryLookupKB, Writer
 from spacy.vectors import Vectors
 from spacy.language import Language
 from spacy.pipeline import TrainablePipe
@@ -71,7 +71,7 @@ def entity_linker():
     nlp = Language()
 
     def create_kb(vocab):
-        kb = KnowledgeBase(vocab, entity_vector_length=1)
+        kb = InMemoryLookupKB(vocab, entity_vector_length=1)
         kb.add_entity("test", 0.0, zeros((1, 1), dtype="f"))
         return kb
 
@@ -120,7 +120,7 @@ def test_writer_with_path_py35():
 
 def test_save_and_load_knowledge_base():
     nlp = Language()
-    kb = KnowledgeBase(nlp.vocab, entity_vector_length=1)
+    kb = InMemoryLookupKB(nlp.vocab, entity_vector_length=1)
     with make_tempdir() as d:
         path = d / "kb"
         try:
@@ -129,7 +129,7 @@ def test_save_and_load_knowledge_base():
             pytest.fail(str(e))
 
         try:
-            kb_loaded = KnowledgeBase(nlp.vocab, entity_vector_length=1)
+            kb_loaded = InMemoryLookupKB(nlp.vocab, entity_vector_length=1)
             kb_loaded.from_disk(path)
         except Exception as e:
             pytest.fail(str(e))
diff --git a/spacy/tests/serialize/test_serialize_kb.py b/spacy/tests/serialize/test_serialize_kb.py
index 1e0ae3c76..8d3653ab1 100644
--- a/spacy/tests/serialize/test_serialize_kb.py
+++ b/spacy/tests/serialize/test_serialize_kb.py
@@ -2,7 +2,7 @@ from typing import Callable
 
 from spacy import util
 from spacy.util import ensure_path, registry, load_model_from_config
-from spacy.kb import KnowledgeBase
+from spacy.kb.kb_in_memory import InMemoryLookupKB
 from spacy.vocab import Vocab
 from thinc.api import Config
 
@@ -22,7 +22,7 @@ def test_serialize_kb_disk(en_vocab):
             dir_path.mkdir()
         file_path = dir_path / "kb"
         kb1.to_disk(str(file_path))
-        kb2 = KnowledgeBase(vocab=en_vocab, entity_vector_length=3)
+        kb2 = InMemoryLookupKB(vocab=en_vocab, entity_vector_length=3)
         kb2.from_disk(str(file_path))
 
     # final assertions
@@ -30,7 +30,7 @@ def test_serialize_kb_disk(en_vocab):
 
 
 def _get_dummy_kb(vocab):
-    kb = KnowledgeBase(vocab, entity_vector_length=3)
+    kb = InMemoryLookupKB(vocab, entity_vector_length=3)
     kb.add_entity(entity="Q53", freq=33, entity_vector=[0, 5, 3])
     kb.add_entity(entity="Q17", freq=2, entity_vector=[7, 1, 0])
     kb.add_entity(entity="Q007", freq=7, entity_vector=[0, 0, 7])
@@ -104,7 +104,7 @@ def test_serialize_subclassed_kb():
     custom_field = 666
     """
 
-    class SubKnowledgeBase(KnowledgeBase):
+    class SubInMemoryLookupKB(InMemoryLookupKB):
         def __init__(self, vocab, entity_vector_length, custom_field):
             super().__init__(vocab, entity_vector_length)
             self.custom_field = custom_field
@@ -112,9 +112,9 @@ def test_serialize_subclassed_kb():
     @registry.misc("spacy.CustomKB.v1")
     def custom_kb(
         entity_vector_length: int, custom_field: int
-    ) -> Callable[[Vocab], KnowledgeBase]:
+    ) -> Callable[[Vocab], InMemoryLookupKB]:
         def custom_kb_factory(vocab):
-            kb = SubKnowledgeBase(
+            kb = SubInMemoryLookupKB(
                 vocab=vocab,
                 entity_vector_length=entity_vector_length,
                 custom_field=custom_field,
@@ -129,7 +129,7 @@ def test_serialize_subclassed_kb():
     nlp.initialize()
 
     entity_linker = nlp.get_pipe("entity_linker")
-    assert type(entity_linker.kb) == SubKnowledgeBase
+    assert type(entity_linker.kb) == SubInMemoryLookupKB
     assert entity_linker.kb.entity_vector_length == 342
     assert entity_linker.kb.custom_field == 666
 
@@ -139,6 +139,6 @@ def test_serialize_subclassed_kb():
         nlp2 = util.load_model_from_path(tmp_dir)
         entity_linker2 = nlp2.get_pipe("entity_linker")
         # After IO, the KB is the standard one
-        assert type(entity_linker2.kb) == KnowledgeBase
+        assert type(entity_linker2.kb) == InMemoryLookupKB
         assert entity_linker2.kb.entity_vector_length == 342
         assert not hasattr(entity_linker2.kb, "custom_field")
diff --git a/website/docs/api/architectures.md b/website/docs/api/architectures.md
index 2537faff6..a3cb07b44 100644
--- a/website/docs/api/architectures.md
+++ b/website/docs/api/architectures.md
@@ -587,8 +587,8 @@ consists of either two or three subnetworks:
   run once for each batch.
 - **lower**: Construct a feature-specific vector for each `(token, feature)`
   pair. This is also run once for each batch. Constructing the state
-  representation is then a matter of summing the component features and
-  applying the non-linearity.
+  representation is then a matter of summing the component features and applying
+  the non-linearity.
 - **upper** (optional): A feed-forward network that predicts scores from the
   state representation. If not present, the output from the lower model is used
   as action scores directly.
@@ -628,8 +628,8 @@ same signature, but the `use_upper` argument was `True` by default.
 > ```
 
 Build a tagger model, using a provided token-to-vector component. The tagger
-model adds a linear layer with softmax activation to predict scores given
-the token vectors.
+model adds a linear layer with softmax activation to predict scores given the
+token vectors.
 
 | Name        | Description                                                                                |
 | ----------- | ------------------------------------------------------------------------------------------ |
@@ -919,6 +919,6 @@ A function that reads an existing `KnowledgeBase` from file.
 
 A function that takes as input a [`KnowledgeBase`](/api/kb) and a
 [`Span`](/api/span) object denoting a named entity, and returns a list of
-plausible [`Candidate`](/api/kb/#candidate) objects. The default
-`CandidateGenerator` uses the text of a mention to find its potential
-aliases in the `KnowledgeBase`. Note that this function is case-dependent.
+plausible [`Candidate`](/api/kb#candidate) objects. The default
+`CandidateGenerator` uses the text of a mention to find its potential aliases in
+the `KnowledgeBase`. Note that this function is case-dependent.
diff --git a/website/docs/api/entitylinker.md b/website/docs/api/entitylinker.md
index 43e08a39c..40ec8afb5 100644
--- a/website/docs/api/entitylinker.md
+++ b/website/docs/api/entitylinker.md
@@ -14,7 +14,8 @@ entities) to unique identifiers, grounding the named entities into the "real
 world". It requires a `KnowledgeBase`, as well as a function to generate
 plausible candidates from that `KnowledgeBase` given a certain textual mention,
 and a machine learning model to pick the right candidate, given the local
-context of the mention.
+context of the mention. `EntityLinker` defaults to using the
+[`InMemoryLookupKB`](/api/kb_in_memory) implementation.
 
 ## Assigned Attributes {#assigned-attributes}
 
@@ -170,7 +171,7 @@ with the current vocab.
 >
 > ```python
 > def create_kb(vocab):
->     kb = KnowledgeBase(vocab, entity_vector_length=128)
+>     kb = InMemoryLookupKB(vocab, entity_vector_length=128)
 >     kb.add_entity(...)
 >     kb.add_alias(...)
 >     return kb
diff --git a/website/docs/api/kb.md b/website/docs/api/kb.md
index e7a8fcd6f..b217a1678 100644
--- a/website/docs/api/kb.md
+++ b/website/docs/api/kb.md
@@ -4,27 +4,45 @@ teaser:
   A storage class for entities and aliases of a specific knowledge base
   (ontology)
 tag: class
-source: spacy/kb.pyx
+source: spacy/kb/kb.pyx
 new: 2.2
 ---
 
-The `KnowledgeBase` object provides a method to generate
-[`Candidate`](/api/kb/#candidate) objects, which are plausible external
+The `KnowledgeBase` object is an abstract class providing a method to generate
+[`Candidate`](/api/kb#candidate) objects, which are plausible external
 identifiers given a certain textual mention. Each such `Candidate` holds
 information from the relevant KB entities, such as its frequency in text and
 possible aliases. Each entity in the knowledge base also has a pretrained entity
 vector of a fixed size.
 
+Beyond that, `KnowledgeBase` classes have to implement a number of utility
+functions called by the [`EntityLinker`](/api/entitylinker) component.
+
+<Infobox variant="warning">
+
+This class was not abstract up to spaCy version 3.5. The `KnowledgeBase`
+implementation up to that point is available as `InMemoryLookupKB` from 3.5
+onwards.
+
+</Infobox>
+
 ## KnowledgeBase.\_\_init\_\_ {#init tag="method"}
 
-Create the knowledge base.
+`KnowledgeBase` is an abstract class and cannot be instantiated. Its child
+classes should call `__init__()` to set up some necessary attributes.
 
 > #### Example
 >
 > ```python
 > from spacy.kb import KnowledgeBase
+> from spacy.vocab import Vocab
+>
+> class FullyImplementedKB(KnowledgeBase):
+>   def __init__(self, vocab: Vocab, entity_vector_length: int):
+>       super().__init__(vocab, entity_vector_length)
+>       ...
 > vocab = nlp.vocab
-> kb = KnowledgeBase(vocab=vocab, entity_vector_length=64)
+> kb = FullyImplementedKB(vocab=vocab, entity_vector_length=64)
 > ```
 
 | Name                   | Description                                      |
@@ -40,133 +58,66 @@ The length of the fixed-size entity vectors in the knowledge base.
 | ----------- | ------------------------------------------------ |
 | **RETURNS** | Length of the fixed-size entity vectors. ~~int~~ |
 
-## KnowledgeBase.add_entity {#add_entity tag="method"}
+## KnowledgeBase.get_candidates {#get_candidates tag="method"}
 
-Add an entity to the knowledge base, specifying its corpus frequency and entity
-vector, which should be of length
-[`entity_vector_length`](/api/kb#entity_vector_length).
+Given a certain textual mention as input, retrieve a list of candidate entities
+of type [`Candidate`](/api/kb#candidate).
 
 > #### Example
 >
 > ```python
-> kb.add_entity(entity="Q42", freq=32, entity_vector=vector1)
-> kb.add_entity(entity="Q463035", freq=111, entity_vector=vector2)
+> from spacy.lang.en import English
+> nlp = English()
+> doc = nlp("Douglas Adams wrote 'The Hitchhiker's Guide to the Galaxy'.")
+> candidates = kb.get_candidates(doc[0:2])
 > ```
 
-| Name            | Description                                                |
-| --------------- | ---------------------------------------------------------- |
-| `entity`        | The unique entity identifier. ~~str~~                      |
-| `freq`          | The frequency of the entity in a typical corpus. ~~float~~ |
-| `entity_vector` | The pretrained vector of the entity. ~~numpy.ndarray~~     |
+| Name        | Description                                                          |
+| ----------- | -------------------------------------------------------------------- |
+| `mention`   | The textual mention or alias. ~~Span~~                               |
+| **RETURNS** | An iterable of relevant `Candidate` objects. ~~Iterable[Candidate]~~ |
 
-## KnowledgeBase.set_entities {#set_entities tag="method"}
+## KnowledgeBase.get_candidates_batch {#get_candidates_batch tag="method"}
 
-Define the full list of entities in the knowledge base, specifying the corpus
-frequency and entity vector for each entity.
+Same as [`get_candidates()`](/api/kb#get_candidates), but for an arbitrary
+number of mentions. The [`EntityLinker`](/api/entitylinker) component will call
+`get_candidates_batch()` instead of `get_candidates()`, if the config parameter
+`candidates_batch_size` is greater or equal than 1.
+
+The default implementation of `get_candidates_batch()` executes
+`get_candidates()` in a loop. We recommend implementing a more efficient way to
+retrieve candidates for multiple mentions at once, if performance is of concern
+to you.
 
 > #### Example
 >
 > ```python
-> kb.set_entities(entity_list=["Q42", "Q463035"], freq_list=[32, 111], vector_list=[vector1, vector2])
+> from spacy.lang.en import English
+> nlp = English()
+> doc = nlp("Douglas Adams wrote 'The Hitchhiker's Guide to the Galaxy'.")
+> candidates = kb.get_candidates((doc[0:2], doc[3:]))
 > ```
 
-| Name          | Description                                                      |
-| ------------- | ---------------------------------------------------------------- |
-| `entity_list` | List of unique entity identifiers. ~~Iterable[Union[str, int]]~~ |
-| `freq_list`   | List of entity frequencies. ~~Iterable[int]~~                    |
-| `vector_list` | List of entity vectors. ~~Iterable[numpy.ndarray]~~              |
-
-## KnowledgeBase.add_alias {#add_alias tag="method"}
-
-Add an alias or mention to the knowledge base, specifying its potential KB
-identifiers and their prior probabilities. The entity identifiers should refer
-to entities previously added with [`add_entity`](/api/kb#add_entity) or
-[`set_entities`](/api/kb#set_entities). The sum of the prior probabilities
-should not exceed 1. Note that an empty string can not be used as alias.
-
-> #### Example
->
-> ```python
-> kb.add_alias(alias="Douglas", entities=["Q42", "Q463035"], probabilities=[0.6, 0.3])
-> ```
-
-| Name            | Description                                                                       |
-| --------------- | --------------------------------------------------------------------------------- |
-| `alias`         | The textual mention or alias. Can not be the empty string. ~~str~~                |
-| `entities`      | The potential entities that the alias may refer to. ~~Iterable[Union[str, int]]~~ |
-| `probabilities` | The prior probabilities of each entity. ~~Iterable[float]~~                       |
-
-## KnowledgeBase.\_\_len\_\_ {#len tag="method"}
-
-Get the total number of entities in the knowledge base.
-
-> #### Example
->
-> ```python
-> total_entities = len(kb)
-> ```
-
-| Name        | Description                                           |
-| ----------- | ----------------------------------------------------- |
-| **RETURNS** | The number of entities in the knowledge base. ~~int~~ |
-
-## KnowledgeBase.get_entity_strings {#get_entity_strings tag="method"}
-
-Get a list of all entity IDs in the knowledge base.
-
-> #### Example
->
-> ```python
-> all_entities = kb.get_entity_strings()
-> ```
-
-| Name        | Description                                               |
-| ----------- | --------------------------------------------------------- |
-| **RETURNS** | The list of entities in the knowledge base. ~~List[str]~~ |
-
-## KnowledgeBase.get_size_aliases {#get_size_aliases tag="method"}
-
-Get the total number of aliases in the knowledge base.
-
-> #### Example
->
-> ```python
-> total_aliases = kb.get_size_aliases()
-> ```
-
-| Name        | Description                                          |
-| ----------- | ---------------------------------------------------- |
-| **RETURNS** | The number of aliases in the knowledge base. ~~int~~ |
-
-## KnowledgeBase.get_alias_strings {#get_alias_strings tag="method"}
-
-Get a list of all aliases in the knowledge base.
-
-> #### Example
->
-> ```python
-> all_aliases = kb.get_alias_strings()
-> ```
-
-| Name        | Description                                              |
-| ----------- | -------------------------------------------------------- |
-| **RETURNS** | The list of aliases in the knowledge base. ~~List[str]~~ |
+| Name        | Description                                                                                  |
+| ----------- | -------------------------------------------------------------------------------------------- |
+| `mentions`  | The textual mention or alias. ~~Iterable[Span]~~                                             |
+| **RETURNS** | An iterable of iterable with relevant `Candidate` objects. ~~Iterable[Iterable[Candidate]]~~ |
 
 ## KnowledgeBase.get_alias_candidates {#get_alias_candidates tag="method"}
 
-Given a certain textual mention as input, retrieve a list of candidate entities
-of type [`Candidate`](/api/kb/#candidate).
+<Infobox variant="warning">
+This method is _not_ available from spaCy 3.5 onwards.
+</Infobox>
 
-> #### Example
->
-> ```python
-> candidates = kb.get_alias_candidates("Douglas")
-> ```
-
-| Name        | Description                                                   |
-| ----------- | ------------------------------------------------------------- |
-| `alias`     | The textual mention or alias. ~~str~~                         |
-| **RETURNS** | The list of relevant `Candidate` objects. ~~List[Candidate]~~ |
+From spaCy 3.5 on `KnowledgeBase` is an abstract class (with
+[`InMemoryLookupKB`](/api/kb_in_memory) being a drop-in replacement) to allow
+more flexibility in customizing knowledge bases. Some of its methods were moved
+to [`InMemoryLookupKB`](/api/kb_in_memory) during this refactoring, one of those
+being `get_alias_candidates()`. This method is now available as
+[`InMemoryLookupKB.get_alias_candidates()`](/api/kb_in_memory#get_alias_candidates).
+Note: [`InMemoryLookupKB.get_candidates()`](/api/kb_in_memory#get_candidates)
+defaults to
+[`InMemoryLookupKB.get_alias_candidates()`](/api/kb_in_memory#get_alias_candidates).
 
 ## KnowledgeBase.get_vector {#get_vector tag="method"}
 
@@ -178,27 +129,30 @@ Given a certain entity ID, retrieve its pretrained entity vector.
 > vector = kb.get_vector("Q42")
 > ```
 
-| Name        | Description                          |
-| ----------- | ------------------------------------ |
-| `entity`    | The entity ID. ~~str~~               |
-| **RETURNS** | The entity vector. ~~numpy.ndarray~~ |
+| Name        | Description                            |
+| ----------- | -------------------------------------- |
+| `entity`    | The entity ID. ~~str~~                 |
+| **RETURNS** | The entity vector. ~~Iterable[float]~~ |
 
-## KnowledgeBase.get_prior_prob {#get_prior_prob tag="method"}
+## KnowledgeBase.get_vectors {#get_vectors tag="method"}
 
-Given a certain entity ID and a certain textual mention, retrieve the prior
-probability of the fact that the mention links to the entity ID.
+Same as [`get_vector()`](/api/kb#get_vector), but for an arbitrary number of
+entity IDs.
+
+The default implementation of `get_vectors()` executes `get_vector()` in a loop.
+We recommend implementing a more efficient way to retrieve vectors for multiple
+entities at once, if performance is of concern to you.
 
 > #### Example
 >
 > ```python
-> probability = kb.get_prior_prob("Q42", "Douglas")
+> vectors = kb.get_vectors(("Q42", "Q3107329"))
 > ```
 
-| Name        | Description                                                               |
-| ----------- | ------------------------------------------------------------------------- |
-| `entity`    | The entity ID. ~~str~~                                                    |
-| `alias`     | The textual mention or alias. ~~str~~                                     |
-| **RETURNS** | The prior probability of the `alias` referring to the `entity`. ~~float~~ |
+| Name        | Description                                               |
+| ----------- | --------------------------------------------------------- |
+| `entities`  | The entity IDs. ~~Iterable[str]~~                         |
+| **RETURNS** | The entity vectors. ~~Iterable[Iterable[numpy.ndarray]]~~ |
 
 ## KnowledgeBase.to_disk {#to_disk tag="method"}
 
@@ -207,12 +161,13 @@ Save the current state of the knowledge base to a directory.
 > #### Example
 >
 > ```python
-> kb.to_disk(loc)
+> kb.to_disk(path)
 > ```
 
-| Name  | Description                                                                                                                                |
-| ----- | ------------------------------------------------------------------------------------------------------------------------------------------ |
-| `loc` | A path to a directory, which will be created if it doesn't exist. Paths may be either strings or `Path`-like objects. ~~Union[str, Path]~~ |
+| Name      | Description                                                                                                                                |
+| --------- | ------------------------------------------------------------------------------------------------------------------------------------------ |
+| `path`    | A path to a directory, which will be created if it doesn't exist. Paths may be either strings or `Path`-like objects. ~~Union[str, Path]~~ |
+| `exclude` | List of components to exclude. ~~Iterable[str]~~                                                                                           |
 
 ## KnowledgeBase.from_disk {#from_disk tag="method"}
 
@@ -222,16 +177,16 @@ Restore the state of the knowledge base from a given directory. Note that the
 > #### Example
 >
 > ```python
-> from spacy.kb import KnowledgeBase
 > from spacy.vocab import Vocab
 > vocab = Vocab().from_disk("/path/to/vocab")
-> kb = KnowledgeBase(vocab=vocab, entity_vector_length=64)
+> kb = FullyImplementedKB(vocab=vocab, entity_vector_length=64)
 > kb.from_disk("/path/to/kb")
 > ```
 
 | Name        | Description                                                                                     |
 | ----------- | ----------------------------------------------------------------------------------------------- |
 | `loc`       | A path to a directory. Paths may be either strings or `Path`-like objects. ~~Union[str, Path]~~ |
+| `exclude`   | List of components to exclude. ~~Iterable[str]~~                                                |
 | **RETURNS** | The modified `KnowledgeBase` object. ~~KnowledgeBase~~                                          |
 
 ## Candidate {#candidate tag="class"}
diff --git a/website/docs/api/kb_in_memory.md b/website/docs/api/kb_in_memory.md
new file mode 100644
index 000000000..c9ce624f0
--- /dev/null
+++ b/website/docs/api/kb_in_memory.md
@@ -0,0 +1,302 @@
+---
+title: InMemoryLookupKB
+teaser:
+  The default implementation of the KnowledgeBase interface. Stores all
+  information in-memory.
+tag: class
+source: spacy/kb/kb_in_memory.pyx
+new: 3.5
+---
+
+The `InMemoryLookupKB` class inherits from [`KnowledgeBase`](/api/kb) and
+implements all of its methods. It stores all KB data in-memory and generates
+[`Candidate`](/api/kb#candidate) objects by exactly matching mentions with
+entity names. It's highly optimized for both a low memory footprint and speed of
+retrieval.
+
+## InMemoryLookupKB.\_\_init\_\_ {#init tag="method"}
+
+Create the knowledge base.
+
+> #### Example
+>
+> ```python
+> from spacy.kb import KnowledgeBase
+> vocab = nlp.vocab
+> kb = KnowledgeBase(vocab=vocab, entity_vector_length=64)
+> ```
+
+| Name                   | Description                                      |
+| ---------------------- | ------------------------------------------------ |
+| `vocab`                | The shared vocabulary. ~~Vocab~~                 |
+| `entity_vector_length` | Length of the fixed-size entity vectors. ~~int~~ |
+
+## InMemoryLookupKB.entity_vector_length {#entity_vector_length tag="property"}
+
+The length of the fixed-size entity vectors in the knowledge base.
+
+| Name        | Description                                      |
+| ----------- | ------------------------------------------------ |
+| **RETURNS** | Length of the fixed-size entity vectors. ~~int~~ |
+
+## InMemoryLookupKB.add_entity {#add_entity tag="method"}
+
+Add an entity to the knowledge base, specifying its corpus frequency and entity
+vector, which should be of length
+[`entity_vector_length`](/api/kb_in_memory#entity_vector_length).
+
+> #### Example
+>
+> ```python
+> kb.add_entity(entity="Q42", freq=32, entity_vector=vector1)
+> kb.add_entity(entity="Q463035", freq=111, entity_vector=vector2)
+> ```
+
+| Name            | Description                                                |
+| --------------- | ---------------------------------------------------------- |
+| `entity`        | The unique entity identifier. ~~str~~                      |
+| `freq`          | The frequency of the entity in a typical corpus. ~~float~~ |
+| `entity_vector` | The pretrained vector of the entity. ~~numpy.ndarray~~     |
+
+## InMemoryLookupKB.set_entities {#set_entities tag="method"}
+
+Define the full list of entities in the knowledge base, specifying the corpus
+frequency and entity vector for each entity.
+
+> #### Example
+>
+> ```python
+> kb.set_entities(entity_list=["Q42", "Q463035"], freq_list=[32, 111], vector_list=[vector1, vector2])
+> ```
+
+| Name          | Description                                                      |
+| ------------- | ---------------------------------------------------------------- |
+| `entity_list` | List of unique entity identifiers. ~~Iterable[Union[str, int]]~~ |
+| `freq_list`   | List of entity frequencies. ~~Iterable[int]~~                    |
+| `vector_list` | List of entity vectors. ~~Iterable[numpy.ndarray]~~              |
+
+## InMemoryLookupKB.add_alias {#add_alias tag="method"}
+
+Add an alias or mention to the knowledge base, specifying its potential KB
+identifiers and their prior probabilities. The entity identifiers should refer
+to entities previously added with [`add_entity`](/api/kb_in_memory#add_entity)
+or [`set_entities`](/api/kb_in_memory#set_entities). The sum of the prior
+probabilities should not exceed 1. Note that an empty string can not be used as
+alias.
+
+> #### Example
+>
+> ```python
+> kb.add_alias(alias="Douglas", entities=["Q42", "Q463035"], probabilities=[0.6, 0.3])
+> ```
+
+| Name            | Description                                                                       |
+| --------------- | --------------------------------------------------------------------------------- |
+| `alias`         | The textual mention or alias. Can not be the empty string. ~~str~~                |
+| `entities`      | The potential entities that the alias may refer to. ~~Iterable[Union[str, int]]~~ |
+| `probabilities` | The prior probabilities of each entity. ~~Iterable[float]~~                       |
+
+## InMemoryLookupKB.\_\_len\_\_ {#len tag="method"}
+
+Get the total number of entities in the knowledge base.
+
+> #### Example
+>
+> ```python
+> total_entities = len(kb)
+> ```
+
+| Name        | Description                                           |
+| ----------- | ----------------------------------------------------- |
+| **RETURNS** | The number of entities in the knowledge base. ~~int~~ |
+
+## InMemoryLookupKB.get_entity_strings {#get_entity_strings tag="method"}
+
+Get a list of all entity IDs in the knowledge base.
+
+> #### Example
+>
+> ```python
+> all_entities = kb.get_entity_strings()
+> ```
+
+| Name        | Description                                               |
+| ----------- | --------------------------------------------------------- |
+| **RETURNS** | The list of entities in the knowledge base. ~~List[str]~~ |
+
+## InMemoryLookupKB.get_size_aliases {#get_size_aliases tag="method"}
+
+Get the total number of aliases in the knowledge base.
+
+> #### Example
+>
+> ```python
+> total_aliases = kb.get_size_aliases()
+> ```
+
+| Name        | Description                                          |
+| ----------- | ---------------------------------------------------- |
+| **RETURNS** | The number of aliases in the knowledge base. ~~int~~ |
+
+## InMemoryLookupKB.get_alias_strings {#get_alias_strings tag="method"}
+
+Get a list of all aliases in the knowledge base.
+
+> #### Example
+>
+> ```python
+> all_aliases = kb.get_alias_strings()
+> ```
+
+| Name        | Description                                              |
+| ----------- | -------------------------------------------------------- |
+| **RETURNS** | The list of aliases in the knowledge base. ~~List[str]~~ |
+
+## InMemoryLookupKB.get_candidates {#get_candidates tag="method"}
+
+Given a certain textual mention as input, retrieve a list of candidate entities
+of type [`Candidate`](/api/kb#candidate). Wraps
+[`get_alias_candidates()`](/api/kb_in_memory#get_alias_candidates).
+
+> #### Example
+>
+> ```python
+> from spacy.lang.en import English
+> nlp = English()
+> doc = nlp("Douglas Adams wrote 'The Hitchhiker's Guide to the Galaxy'.")
+> candidates = kb.get_candidates(doc[0:2])
+> ```
+
+| Name        | Description                                                          |
+| ----------- | -------------------------------------------------------------------- |
+| `mention`   | The textual mention or alias. ~~Span~~                               |
+| **RETURNS** | An iterable of relevant `Candidate` objects. ~~Iterable[Candidate]~~ |
+
+## InMemoryLookupKB.get_candidates_batch {#get_candidates_batch tag="method"}
+
+Same as [`get_candidates()`](/api/kb_in_memory#get_candidates), but for an
+arbitrary number of mentions. The [`EntityLinker`](/api/entitylinker) component
+will call `get_candidates_batch()` instead of `get_candidates()`, if the config
+parameter `candidates_batch_size` is greater or equal than 1.
+
+The default implementation of `get_candidates_batch()` executes
+`get_candidates()` in a loop. We recommend implementing a more efficient way to
+retrieve candidates for multiple mentions at once, if performance is of concern
+to you.
+
+> #### Example
+>
+> ```python
+> from spacy.lang.en import English
+> nlp = English()
+> doc = nlp("Douglas Adams wrote 'The Hitchhiker's Guide to the Galaxy'.")
+> candidates = kb.get_candidates((doc[0:2], doc[3:]))
+> ```
+
+| Name        | Description                                                                                  |
+| ----------- | -------------------------------------------------------------------------------------------- |
+| `mentions`  | The textual mention or alias. ~~Iterable[Span]~~                                             |
+| **RETURNS** | An iterable of iterable with relevant `Candidate` objects. ~~Iterable[Iterable[Candidate]]~~ |
+
+## InMemoryLookupKB.get_alias_candidates {#get_alias_candidates tag="method"}
+
+Given a certain textual mention as input, retrieve a list of candidate entities
+of type [`Candidate`](/api/kb#candidate).
+
+> #### Example
+>
+> ```python
+> candidates = kb.get_alias_candidates("Douglas")
+> ```
+
+| Name        | Description                                                   |
+| ----------- | ------------------------------------------------------------- |
+| `alias`     | The textual mention or alias. ~~str~~                         |
+| **RETURNS** | The list of relevant `Candidate` objects. ~~List[Candidate]~~ |
+
+## InMemoryLookupKB.get_vector {#get_vector tag="method"}
+
+Given a certain entity ID, retrieve its pretrained entity vector.
+
+> #### Example
+>
+> ```python
+> vector = kb.get_vector("Q42")
+> ```
+
+| Name        | Description                          |
+| ----------- | ------------------------------------ |
+| `entity`    | The entity ID. ~~str~~               |
+| **RETURNS** | The entity vector. ~~numpy.ndarray~~ |
+
+## InMemoryLookupKB.get_vectors {#get_vectors tag="method"}
+
+Same as [`get_vector()`](/api/kb_in_memory#get_vector), but for an arbitrary
+number of entity IDs.
+
+The default implementation of `get_vectors()` executes `get_vector()` in a loop.
+We recommend implementing a more efficient way to retrieve vectors for multiple
+entities at once, if performance is of concern to you.
+
+> #### Example
+>
+> ```python
+> vectors = kb.get_vectors(("Q42", "Q3107329"))
+> ```
+
+| Name        | Description                                               |
+| ----------- | --------------------------------------------------------- |
+| `entities`  | The entity IDs. ~~Iterable[str]~~                         |
+| **RETURNS** | The entity vectors. ~~Iterable[Iterable[numpy.ndarray]]~~ |
+
+## InMemoryLookupKB.get_prior_prob {#get_prior_prob tag="method"}
+
+Given a certain entity ID and a certain textual mention, retrieve the prior
+probability of the fact that the mention links to the entity ID.
+
+> #### Example
+>
+> ```python
+> probability = kb.get_prior_prob("Q42", "Douglas")
+> ```
+
+| Name        | Description                                                               |
+| ----------- | ------------------------------------------------------------------------- |
+| `entity`    | The entity ID. ~~str~~                                                    |
+| `alias`     | The textual mention or alias. ~~str~~                                     |
+| **RETURNS** | The prior probability of the `alias` referring to the `entity`. ~~float~~ |
+
+## InMemoryLookupKB.to_disk {#to_disk tag="method"}
+
+Save the current state of the knowledge base to a directory.
+
+> #### Example
+>
+> ```python
+> kb.to_disk(path)
+> ```
+
+| Name      | Description                                                                                                                                |
+| --------- | ------------------------------------------------------------------------------------------------------------------------------------------ |
+| `path`    | A path to a directory, which will be created if it doesn't exist. Paths may be either strings or `Path`-like objects. ~~Union[str, Path]~~ |
+| `exclude` | List of components to exclude. ~~Iterable[str]~~                                                                                           |
+
+## InMemoryLookupKB.from_disk {#from_disk tag="method"}
+
+Restore the state of the knowledge base from a given directory. Note that the
+[`Vocab`](/api/vocab) should also be the same as the one used to create the KB.
+
+> #### Example
+>
+> ```python
+> from spacy.vocab import Vocab
+> vocab = Vocab().from_disk("/path/to/vocab")
+> kb = FullyImplementedKB(vocab=vocab, entity_vector_length=64)
+> kb.from_disk("/path/to/kb")
+> ```
+
+| Name        | Description                                                                                     |
+| ----------- | ----------------------------------------------------------------------------------------------- |
+| `loc`       | A path to a directory. Paths may be either strings or `Path`-like objects. ~~Union[str, Path]~~ |
+| `exclude`   | List of components to exclude. ~~Iterable[str]~~                                                |
+| **RETURNS** | The modified `KnowledgeBase` object. ~~KnowledgeBase~~                                          |
diff --git a/website/docs/usage/101/_architecture.md b/website/docs/usage/101/_architecture.md
index 22e2b961e..4ebca2756 100644
--- a/website/docs/usage/101/_architecture.md
+++ b/website/docs/usage/101/_architecture.md
@@ -78,7 +78,9 @@ operates on a `Doc` and gives you access to the matched tokens **in context**.
 | Name                                             | Description                                                                                        |
 | ------------------------------------------------ | -------------------------------------------------------------------------------------------------- |
 | [`Corpus`](/api/corpus)                          | Class for managing annotated corpora for training and evaluation data.                             |
-| [`KnowledgeBase`](/api/kb)                       | Storage for entities and aliases of a knowledge base for entity linking.                           |
+| [`KnowledgeBase`](/api/kb)                       | Abstract base class for storage and retrieval of data for entity linking.                          |
+| [`InMemoryLookupKB`](/api/kb_in_memory)          | Implementation of `KnowledgeBase` storing all data in memory.                                      |
+| [`Candidate`](/api/kb#candidate)                 | Object associating a textual mention with a specific entity contained in a `KnowledgeBase`.        |
 | [`Lookups`](/api/lookups)                        | Container for convenient access to large lookup tables and dictionaries.                           |
 | [`MorphAnalysis`](/api/morphology#morphanalysis) | A morphological analysis.                                                                          |
 | [`Morphology`](/api/morphology)                  | Store morphological analyses and map them to and from hash values.                                 |

From 2602a30d326e561776fecce95ac03cc5df55652b Mon Sep 17 00:00:00 2001
From: Paul O'Leary McCann <polm@dampfkraft.com>
Date: Thu, 8 Sep 2022 20:42:47 +0900
Subject: [PATCH 086/174] Fix DVC command example (#11457)

This command doesn't have the project dir, but it's required.
---
 website/docs/usage/projects.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/website/docs/usage/projects.md b/website/docs/usage/projects.md
index 566ae561b..35150035a 100644
--- a/website/docs/usage/projects.md
+++ b/website/docs/usage/projects.md
@@ -758,7 +758,7 @@ and [`dvc repro`](https://dvc.org/doc/command-reference/repro) to reproduce the
 workflow or individual commands.
 
 ```cli
-$ python -m spacy project dvc [workflow_name]
+$ python -m spacy project dvc [project_dir] [workflow_name]
 ```
 
 <Infobox title="Important note for multiple workflows" variant="warning">

From aac9a58c2935768c7751b8db7043e7c073362c90 Mon Sep 17 00:00:00 2001
From: Madeesh Kannan <shadeMe@users.noreply.github.com>
Date: Fri, 9 Sep 2022 10:46:01 +0200
Subject: [PATCH 087/174] Add docs for the
 `spacy.models_and_pipes_with_nvtx_range.v1` callback (#11463)

* Add docs for the `spacy.models_and_pipes_with_nvtx_range.v1` callback

* Add `new` tag
---
 website/docs/api/top-level.md | 21 +++++++++++++++++++++
 1 file changed, 21 insertions(+)

diff --git a/website/docs/api/top-level.md b/website/docs/api/top-level.md
index 220b2d6e9..bc53fc868 100644
--- a/website/docs/api/top-level.md
+++ b/website/docs/api/top-level.md
@@ -887,6 +887,27 @@ backprop passes.
 | `backprop_color` | Color identifier for backpropagation passes. Defaults to `-1`. ~~int~~                                                       |
 | **CREATES**      | A function that takes the current `nlp` and wraps forward/backprop passes in NVTX ranges. ~~Callable[[Language], Language]~~ |
 
+### spacy.models_and_pipes_with_nvtx_range.v1 {#models_and_pipes_with_nvtx_range tag="registered function" new="3.4"}
+
+> #### Example config
+>
+> ```ini
+> [nlp]
+> after_pipeline_creation = {"@callbacks":"spacy.models_and_pipes_with_nvtx_range.v1"}
+> ```
+
+Recursively wrap both the models and methods of each pipe using
+[NVTX](https://nvidia.github.io/NVTX/) range markers. By default, the following
+methods are wrapped: `pipe`, `predict`, `set_annotations`, `update`, `rehearse`,
+`get_loss`, `initialize`, `begin_update`, `finish_update`, `update`.
+
+| Name                        | Description                                                                                                                                                     |
+| --------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `forward_color`             | Color identifier for model forward passes. Defaults to `-1`. ~~int~~                                                                                            |
+| `backprop_color`            | Color identifier for model backpropagation passes. Defaults to `-1`. ~~int~~                                                                                    |
+| `additional_pipe_functions` | Additional pipeline methods to wrap. Keys are pipeline names and values are lists of method identifiers. Defaults to `None`. ~~Optional[Dict[str, List[str]]]~~ |
+| **CREATES**                 | A function that takes the current `nlp` and wraps pipe models and methods in NVTX ranges. ~~Callable[[Language], Language]~~                                    |
+
 ## Training data and alignment {#gold source="spacy/training"}
 
 ### training.offsets_to_biluo_tags {#offsets_to_biluo_tags tag="function"}

From 0c72c6bb2c04677654ffeda2a706e3df3a58b3cc Mon Sep 17 00:00:00 2001
From: "github-actions[bot]"
 <41898282+github-actions[bot]@users.noreply.github.com>
Date: Fri, 9 Sep 2022 11:21:17 +0200
Subject: [PATCH 088/174] Auto-format code with black (#11468)

Co-authored-by: explosion-bot <explosion-bot@users.noreply.github.com>
---
 spacy/cli/info.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/spacy/cli/info.py b/spacy/cli/info.py
index e6ac4270f..974bc0f4e 100644
--- a/spacy/cli/info.py
+++ b/spacy/cli/info.py
@@ -147,6 +147,7 @@ def info_installed_model_url(model: str) -> Optional[str]:
         # something else, like no file or invalid JSON
         return None
 
+
 def info_model_url(model: str) -> Dict[str, Any]:
     """Return the download URL for the latest version of a pipeline."""
     version = get_latest_version(model)

From 8a86a35eab45a69d795c2950da61058047d1a516 Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Fri, 9 Sep 2022 15:10:04 +0200
Subject: [PATCH 089/174] Remove has_letters in config template (#11465)

Due to problems with the javascript conversion in the website
quickstart, remove the `has_letters` setting to simplify generating
`attrs` for the default `tok2vec`.

Additionally reduce `PREFIX` as in the trained pipelines.
---
 spacy/cli/templates/quickstart_training.jinja              | 7 +------
 .../cli/templates/quickstart_training_recommendations.yml  | 1 -
 2 files changed, 1 insertion(+), 7 deletions(-)

diff --git a/spacy/cli/templates/quickstart_training.jinja b/spacy/cli/templates/quickstart_training.jinja
index ae11dcafc..58864883a 100644
--- a/spacy/cli/templates/quickstart_training.jinja
+++ b/spacy/cli/templates/quickstart_training.jinja
@@ -271,13 +271,8 @@ factory = "tok2vec"
 [components.tok2vec.model.embed]
 @architectures = "spacy.MultiHashEmbed.v2"
 width = ${components.tok2vec.model.encode.width}
-{% if has_letters -%}
 attrs = ["NORM", "PREFIX", "SUFFIX", "SHAPE"]
-rows = [5000, 2500, 2500, 2500]
-{% else -%}
-attrs = ["ORTH", "SHAPE"]
-rows = [5000, 2500]
-{% endif -%}
+rows = [5000, 1000, 2500, 2500]
 include_static_vectors = {{ "true" if optimize == "accuracy" else "false" }}
 
 [components.tok2vec.model.encode]
diff --git a/spacy/cli/templates/quickstart_training_recommendations.yml b/spacy/cli/templates/quickstart_training_recommendations.yml
index a7bf9b74a..27945e27a 100644
--- a/spacy/cli/templates/quickstart_training_recommendations.yml
+++ b/spacy/cli/templates/quickstart_training_recommendations.yml
@@ -271,4 +271,3 @@ zh:
     accuracy:
       name: bert-base-chinese
       size_factor: 3
-  has_letters: false

From 6b83fee58db27cee70ef8d893cbbf7470db4e242 Mon Sep 17 00:00:00 2001
From: kadarakos <kadar.akos@gmail.com>
Date: Fri, 9 Sep 2022 17:17:10 +0200
Subject: [PATCH 090/174] Assets message (#11458)

* new error message when 'project run assets'

* new error message when 'project run assets'

* Update spacy/cli/project/run.py

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
---
 spacy/cli/project/run.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/spacy/cli/project/run.py b/spacy/cli/project/run.py
index 734803bc4..d42d95465 100644
--- a/spacy/cli/project/run.py
+++ b/spacy/cli/project/run.py
@@ -195,6 +195,8 @@ def validate_subcommand(
         msg.fail(f"No commands or workflows defined in {PROJECT_FILE}", exits=1)
     if subcommand not in commands and subcommand not in workflows:
         help_msg = []
+        if subcommand in ["assets", "asset"]:
+            help_msg.append("Did you mean to run: python -m spacy project assets?")
         if commands:
             help_msg.append(f"Available commands: {', '.join(commands)}")
         if workflows:

From 0ec9a696e60933807c189c7be22623a81a840289 Mon Sep 17 00:00:00 2001
From: Madeesh Kannan <shadeMe@users.noreply.github.com>
Date: Mon, 12 Sep 2022 14:55:41 +0200
Subject: [PATCH 091/174] Fix config validation failures caused by NVTX
 pipeline wrappers (#11460)

* Enable Cython<->Python bindings for `Pipe` and `TrainablePipe` methods

* `pipes_with_nvtx_range`: Skip hooking methods whose signature cannot be ascertained

When loading pipelines from a config file, the arguments passed to individual pipeline components is validated by `pydantic` during init. For this, the validation model attempts to parse the function signature of the component's c'tor/entry point so that it can check if all mandatory parameters are present in the config file.

When using the `models_and_pipes_with_nvtx_range` as a `after_pipeline_creation` callback, the methods of all pipeline components get replaced by a NVTX range wrapper **before** the above-mentioned validation takes place. This can be problematic for components that are implemented as Cython extension types - if the extension type is not compiled with Python bindings for its methods, they will have no signatures at runtime. This resulted in `pydantic` matching the *wrapper's* parameters with the those in the config and raising errors.

To avoid this, we now skip applying the wrapper to any (Cython) methods that do not have signatures.
---
 spacy/ml/callbacks.py             | 7 +++++--
 spacy/pipeline/pipe.pyx           | 2 +-
 spacy/pipeline/trainable_pipe.pyx | 2 +-
 3 files changed, 7 insertions(+), 4 deletions(-)

diff --git a/spacy/ml/callbacks.py b/spacy/ml/callbacks.py
index 18290b947..3b60ec2ab 100644
--- a/spacy/ml/callbacks.py
+++ b/spacy/ml/callbacks.py
@@ -89,11 +89,14 @@ def pipes_with_nvtx_range(
                 types.MethodType(nvtx_range_wrapper_for_pipe_method, pipe), func
             )
 
-            # Try to preserve the original function signature.
+            # We need to preserve the original function signature so that
+            # the original parameters are passed to pydantic for validation downstream.
             try:
                 wrapped_func.__signature__ = inspect.signature(func)  # type: ignore
             except:
-                pass
+                # Can fail for Cython methods that do not have bindings.
+                warnings.warn(Warnings.W122.format(method=name, pipe=pipe.name))
+                continue
 
             try:
                 setattr(
diff --git a/spacy/pipeline/pipe.pyx b/spacy/pipeline/pipe.pyx
index 4e3ae1cf0..8407acc45 100644
--- a/spacy/pipeline/pipe.pyx
+++ b/spacy/pipeline/pipe.pyx
@@ -1,4 +1,4 @@
-# cython: infer_types=True, profile=True
+# cython: infer_types=True, profile=True, binding=True
 from typing import Optional, Tuple, Iterable, Iterator, Callable, Union, Dict
 import srsly
 import warnings
diff --git a/spacy/pipeline/trainable_pipe.pyx b/spacy/pipeline/trainable_pipe.pyx
index 76b0733cf..3f0507d4b 100644
--- a/spacy/pipeline/trainable_pipe.pyx
+++ b/spacy/pipeline/trainable_pipe.pyx
@@ -1,4 +1,4 @@
-# cython: infer_types=True, profile=True
+# cython: infer_types=True, profile=True, binding=True
 from typing import Iterable, Iterator, Optional, Dict, Tuple, Callable
 import srsly
 from thinc.api import set_dropout_rate, Model, Optimizer

From cc10a27c59a3e5fe3c2d08667534fcbf22908f06 Mon Sep 17 00:00:00 2001
From: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Date: Mon, 12 Sep 2022 15:36:48 +0200
Subject: [PATCH 092/174] Prevent tok2vec to broadcast to listeners when
 predicting (#11385)

* replicate bug with tok2vec in annotating components

* add overfitting test with a frozen tok2vec

* remove broadcast from predict and check doc.tensor instead

* remove broadcast

* proper error

* slight rephrase of documentation
---
 spacy/errors.py                      |  2 +
 spacy/pipeline/tok2vec.py            | 20 ++++---
 spacy/tests/pipeline/test_tok2vec.py | 81 ++++++++++++++++++++++++++++
 website/docs/usage/training.md       |  2 +-
 4 files changed, 98 insertions(+), 7 deletions(-)

diff --git a/spacy/errors.py b/spacy/errors.py
index e2201284f..7e63dc76c 100644
--- a/spacy/errors.py
+++ b/spacy/errors.py
@@ -538,6 +538,8 @@ class Errors(metaclass=ErrorsWithCodes):
     E199 = ("Unable to merge 0-length span at `doc[{start}:{end}]`.")
     E200 = ("Can't set {attr} from Span.")
     E202 = ("Unsupported {name} mode '{mode}'. Supported modes: {modes}.")
+    E203 = ("If the {name} embedding layer is not updated "
+            "during training, make sure to include it in 'annotating components'")
 
     # New errors added in v3.x
     E853 = ("Unsupported component factory name '{name}'. The character '.' is "
diff --git a/spacy/pipeline/tok2vec.py b/spacy/pipeline/tok2vec.py
index 2e3dde3cb..c742aaeaa 100644
--- a/spacy/pipeline/tok2vec.py
+++ b/spacy/pipeline/tok2vec.py
@@ -123,9 +123,6 @@ class Tok2Vec(TrainablePipe):
             width = self.model.get_dim("nO")
             return [self.model.ops.alloc((0, width)) for doc in docs]
         tokvecs = self.model.predict(docs)
-        batch_id = Tok2VecListener.get_batch_id(docs)
-        for listener in self.listeners:
-            listener.receive(batch_id, tokvecs, _empty_backprop)
         return tokvecs
 
     def set_annotations(self, docs: Sequence[Doc], tokvecses) -> None:
@@ -286,8 +283,19 @@ class Tok2VecListener(Model):
 def forward(model: Tok2VecListener, inputs, is_train: bool):
     """Supply the outputs from the upstream Tok2Vec component."""
     if is_train:
-        model.verify_inputs(inputs)
-        return model._outputs, model._backprop
+        # This might occur during training when the tok2vec layer is frozen / hasn't been updated.
+        # In that case, it should be set to "annotating" so we can retrieve the embeddings from the doc.
+        if model._batch_id is None:
+            outputs = []
+            for doc in inputs:
+                if doc.tensor.size == 0:
+                    raise ValueError(Errors.E203.format(name="tok2vec"))
+                else:
+                    outputs.append(doc.tensor)
+            return outputs, _empty_backprop
+        else:
+            model.verify_inputs(inputs)
+            return model._outputs, model._backprop
     else:
         # This is pretty grim, but it's hard to do better :(.
         # It's hard to avoid relying on the doc.tensor attribute, because the
@@ -306,7 +314,7 @@ def forward(model: Tok2VecListener, inputs, is_train: bool):
                 outputs.append(model.ops.alloc2f(len(doc), width))
             else:
                 outputs.append(doc.tensor)
-        return outputs, lambda dX: []
+        return outputs, _empty_backprop
 
 
 def _empty_backprop(dX):  # for pickling
diff --git a/spacy/tests/pipeline/test_tok2vec.py b/spacy/tests/pipeline/test_tok2vec.py
index 64faf133d..659274db9 100644
--- a/spacy/tests/pipeline/test_tok2vec.py
+++ b/spacy/tests/pipeline/test_tok2vec.py
@@ -230,6 +230,87 @@ def test_tok2vec_listener_callback():
     assert get_dX(Y) is not None
 
 
+def test_tok2vec_listener_overfitting():
+    """ Test that a pipeline with a listener properly overfits, even if 'tok2vec' is in the annotating components """
+    orig_config = Config().from_str(cfg_string)
+    nlp = util.load_model_from_config(orig_config, auto_fill=True, validate=True)
+    train_examples = []
+    for t in TRAIN_DATA:
+        train_examples.append(Example.from_dict(nlp.make_doc(t[0]), t[1]))
+    optimizer = nlp.initialize(get_examples=lambda: train_examples)
+
+    for i in range(50):
+        losses = {}
+        nlp.update(train_examples, sgd=optimizer, losses=losses, annotates=["tok2vec"])
+    assert losses["tagger"] < 0.00001
+
+    # test the trained model
+    test_text = "I like blue eggs"
+    doc = nlp(test_text)
+    assert doc[0].tag_ == "N"
+    assert doc[1].tag_ == "V"
+    assert doc[2].tag_ == "J"
+    assert doc[3].tag_ == "N"
+
+    # Also test the results are still the same after IO
+    with make_tempdir() as tmp_dir:
+        nlp.to_disk(tmp_dir)
+        nlp2 = util.load_model_from_path(tmp_dir)
+        doc2 = nlp2(test_text)
+        assert doc2[0].tag_ == "N"
+        assert doc2[1].tag_ == "V"
+        assert doc2[2].tag_ == "J"
+        assert doc2[3].tag_ == "N"
+
+
+def test_tok2vec_frozen_not_annotating():
+    """ Test that a pipeline with a frozen tok2vec raises an error when the tok2vec is not annotating """
+    orig_config = Config().from_str(cfg_string)
+    nlp = util.load_model_from_config(orig_config, auto_fill=True, validate=True)
+    train_examples = []
+    for t in TRAIN_DATA:
+        train_examples.append(Example.from_dict(nlp.make_doc(t[0]), t[1]))
+    optimizer = nlp.initialize(get_examples=lambda: train_examples)
+
+    for i in range(2):
+        losses = {}
+        with pytest.raises(ValueError, match=r"the tok2vec embedding layer is not updated"):
+            nlp.update(train_examples, sgd=optimizer, losses=losses, exclude=["tok2vec"])
+
+
+def test_tok2vec_frozen_overfitting():
+    """ Test that a pipeline with a frozen & annotating tok2vec can still overfit """
+    orig_config = Config().from_str(cfg_string)
+    nlp = util.load_model_from_config(orig_config, auto_fill=True, validate=True)
+    train_examples = []
+    for t in TRAIN_DATA:
+        train_examples.append(Example.from_dict(nlp.make_doc(t[0]), t[1]))
+    optimizer = nlp.initialize(get_examples=lambda: train_examples)
+
+    for i in range(100):
+        losses = {}
+        nlp.update(train_examples, sgd=optimizer, losses=losses, exclude=["tok2vec"], annotates=["tok2vec"])
+    assert losses["tagger"] < 0.0001
+
+    # test the trained model
+    test_text = "I like blue eggs"
+    doc = nlp(test_text)
+    assert doc[0].tag_ == "N"
+    assert doc[1].tag_ == "V"
+    assert doc[2].tag_ == "J"
+    assert doc[3].tag_ == "N"
+
+    # Also test the results are still the same after IO
+    with make_tempdir() as tmp_dir:
+        nlp.to_disk(tmp_dir)
+        nlp2 = util.load_model_from_path(tmp_dir)
+        doc2 = nlp2(test_text)
+        assert doc2[0].tag_ == "N"
+        assert doc2[1].tag_ == "V"
+        assert doc2[2].tag_ == "J"
+        assert doc2[3].tag_ == "N"
+
+
 def test_replace_listeners():
     orig_config = Config().from_str(cfg_string)
     nlp = util.load_model_from_config(orig_config, auto_fill=True, validate=True)
diff --git a/website/docs/usage/training.md b/website/docs/usage/training.md
index 5e064b269..27a8bbca7 100644
--- a/website/docs/usage/training.md
+++ b/website/docs/usage/training.md
@@ -480,7 +480,7 @@ as-is. They are also excluded when calling
 > parse. So the evaluation results should always reflect what your pipeline will
 > produce at runtime. If you want a frozen component to run (without updating)
 > during training as well, so that downstream components can use its
-> **predictions**, you can add it to the list of
+> **predictions**, you should add it to the list of
 > [`annotating_components`](/usage/training#annotating-components).
 
 ```ini

From 6be6913ba5aaa7aa35deb1a9fcd4418d93824b24 Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Tue, 13 Sep 2022 09:04:53 +0200
Subject: [PATCH 093/174] Update cupy extras (#11279)

* Update cupy extras:

* Extend to v11
* Add `cupy-cuda11x` and `cupy-wheel`
* Update quickstart to use `cupy-wheel` for CUDA 10.2+

* Rename cuda-wheel to cuda-autodetect, remove repeated CUDA in menu
---
 setup.cfg                                 | 36 +++++++++++++----------
 website/src/widgets/quickstart-install.js | 12 ++------
 2 files changed, 22 insertions(+), 26 deletions(-)

diff --git a/setup.cfg b/setup.cfg
index 5fd820a96..2dc5e7042 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -76,37 +76,41 @@ transformers =
 ray =
     spacy_ray>=0.1.0,<1.0.0
 cuda =
-    cupy>=5.0.0b4,<11.0.0
+    cupy>=5.0.0b4,<12.0.0
 cuda80 =
-    cupy-cuda80>=5.0.0b4,<11.0.0
+    cupy-cuda80>=5.0.0b4,<12.0.0
 cuda90 =
-    cupy-cuda90>=5.0.0b4,<11.0.0
+    cupy-cuda90>=5.0.0b4,<12.0.0
 cuda91 =
-    cupy-cuda91>=5.0.0b4,<11.0.0
+    cupy-cuda91>=5.0.0b4,<12.0.0
 cuda92 =
-    cupy-cuda92>=5.0.0b4,<11.0.0
+    cupy-cuda92>=5.0.0b4,<12.0.0
 cuda100 =
-    cupy-cuda100>=5.0.0b4,<11.0.0
+    cupy-cuda100>=5.0.0b4,<12.0.0
 cuda101 =
-    cupy-cuda101>=5.0.0b4,<11.0.0
+    cupy-cuda101>=5.0.0b4,<12.0.0
 cuda102 =
-    cupy-cuda102>=5.0.0b4,<11.0.0
+    cupy-cuda102>=5.0.0b4,<12.0.0
 cuda110 =
-    cupy-cuda110>=5.0.0b4,<11.0.0
+    cupy-cuda110>=5.0.0b4,<12.0.0
 cuda111 =
-    cupy-cuda111>=5.0.0b4,<11.0.0
+    cupy-cuda111>=5.0.0b4,<12.0.0
 cuda112 =
-    cupy-cuda112>=5.0.0b4,<11.0.0
+    cupy-cuda112>=5.0.0b4,<12.0.0
 cuda113 =
-    cupy-cuda113>=5.0.0b4,<11.0.0
+    cupy-cuda113>=5.0.0b4,<12.0.0
 cuda114 =
-    cupy-cuda114>=5.0.0b4,<11.0.0
+    cupy-cuda114>=5.0.0b4,<12.0.0
 cuda115 =
-    cupy-cuda115>=5.0.0b4,<11.0.0
+    cupy-cuda115>=5.0.0b4,<12.0.0
 cuda116 =
-    cupy-cuda116>=5.0.0b4,<11.0.0
+    cupy-cuda116>=5.0.0b4,<12.0.0
 cuda117 =
-    cupy-cuda117>=5.0.0b4,<11.0.0
+    cupy-cuda117>=5.0.0b4,<12.0.0
+cuda11x =
+    cupy-cuda11x>=11.0.0,<12.0.0
+cuda-autodetect =
+    cupy-wheel>=11.0.0,<12.0.0
 apple =
     thinc-apple-ops>=0.1.0.dev0,<1.0.0
 # Language tokenizers with external dependencies
diff --git a/website/src/widgets/quickstart-install.js b/website/src/widgets/quickstart-install.js
index 61c0678dd..0d2186acb 100644
--- a/website/src/widgets/quickstart-install.js
+++ b/website/src/widgets/quickstart-install.js
@@ -9,7 +9,7 @@ const DEFAULT_PLATFORM = 'x86'
 const DEFAULT_MODELS = ['en']
 const DEFAULT_OPT = 'efficiency'
 const DEFAULT_HARDWARE = 'cpu'
-const DEFAULT_CUDA = 'cuda113'
+const DEFAULT_CUDA = 'cuda-autodetect'
 const CUDA = {
     '8.0': 'cuda80',
     '9.0': 'cuda90',
@@ -17,15 +17,7 @@ const CUDA = {
     '9.2': 'cuda92',
     '10.0': 'cuda100',
     '10.1': 'cuda101',
-    '10.2': 'cuda102',
-    '11.0': 'cuda110',
-    '11.1': 'cuda111',
-    '11.2': 'cuda112',
-    '11.3': 'cuda113',
-    '11.4': 'cuda114',
-    '11.5': 'cuda115',
-    '11.6': 'cuda116',
-    '11.7': 'cuda117',
+    '10.2, 11.0+': 'cuda-autodetect',
 }
 const LANG_EXTRAS = ['ja'] // only for languages with models
 

From 3f0c3ad7d30d493cd017b6bb41b174d991bbcdc1 Mon Sep 17 00:00:00 2001
From: Richard Hudson <richard@explosion.ai>
Date: Wed, 14 Sep 2022 09:36:55 +0200
Subject: [PATCH 094/174] Correct alignment example and documentation (#11491)

* Correct example and documentation

* Added altered example.md

* Changes based on review + apply prettier

* Remote unnecessary 'the'

Co-authored-by: Madeesh Kannan <shadeMe@users.noreply.github.com>

Co-authored-by: Madeesh Kannan <shadeMe@users.noreply.github.com>
---
 website/docs/api/example.md               | 16 ++++++++++------
 website/docs/usage/linguistic-features.md | 10 +++++-----
 2 files changed, 15 insertions(+), 11 deletions(-)

diff --git a/website/docs/api/example.md b/website/docs/api/example.md
index ca9d3c056..0228e8935 100644
--- a/website/docs/api/example.md
+++ b/website/docs/api/example.md
@@ -286,10 +286,14 @@ Calculate alignment tables between two tokenizations.
 
 ### Alignment attributes {#alignment-attributes"}
 
-| Name  | Description                                                           |
-| ----- | --------------------------------------------------------------------- |
-| `x2y` | The `Ragged` object holding the alignment from `x` to `y`. ~~Ragged~~ |
-| `y2x` | The `Ragged` object holding the alignment from `y` to `x`. ~~Ragged~~ |
+Alignment attributes are managed using `AlignmentArray`, which is a
+simplified version of Thinc's [Ragged](https://thinc.ai/docs/api-types#ragged)
+type that only supports the `data` and `length` attributes.
+
+| Name  | Description                                                                           |
+| ----- | ------------------------------------------------------------------------------------- |
+| `x2y` | The `AlignmentArray` object holding the alignment from `x` to `y`. ~~AlignmentArray~~ |
+| `y2x` | The `AlignmentArray` object holding the alignment from `y` to `x`. ~~AlignmentArray~~ |
 
 <Infobox title="Important note" variant="warning">
 
@@ -309,10 +313,10 @@ tokenizations add up to the same string. For example, you'll be able to align
 > spacy_tokens = ["obama", "'s", "podcast"]
 > alignment = Alignment.from_strings(bert_tokens, spacy_tokens)
 > a2b = alignment.x2y
-> assert list(a2b.dataXd) == [0, 1, 1, 2]
+> assert list(a2b.data) == [0, 1, 1, 2]
 > ```
 >
-> If `a2b.dataXd[1] == a2b.dataXd[2] == 1`, that means that `A[1]` (`"'"`) and
+> If `a2b.data[1] == a2b.data[2] == 1`, that means that `A[1]` (`"'"`) and
 > `A[2]` (`"s"`) both align to `B[1]` (`"'s"`).
 
 ### Alignment.from_strings {#classmethod tag="function"}
diff --git a/website/docs/usage/linguistic-features.md b/website/docs/usage/linguistic-features.md
index 82472c67e..099678c40 100644
--- a/website/docs/usage/linguistic-features.md
+++ b/website/docs/usage/linguistic-features.md
@@ -1422,9 +1422,9 @@ other_tokens = ["i", "listened", "to", "obama", "'", "s", "podcasts", "."]
 spacy_tokens = ["i", "listened", "to", "obama", "'s", "podcasts", "."]
 align = Alignment.from_strings(other_tokens, spacy_tokens)
 print(f"a -> b, lengths: {align.x2y.lengths}")  # array([1, 1, 1, 1, 1, 1, 1, 1])
-print(f"a -> b, mapping: {align.x2y.dataXd}")  # array([0, 1, 2, 3, 4, 4, 5, 6]) : two tokens both refer to "'s"
+print(f"a -> b, mapping: {align.x2y.data}")  # array([0, 1, 2, 3, 4, 4, 5, 6]) : two tokens both refer to "'s"
 print(f"b -> a, lengths: {align.y2x.lengths}")  # array([1, 1, 1, 1, 2, 1, 1])   : the token "'s" refers to two tokens
-print(f"b -> a, mappings: {align.y2x.dataXd}")  # array([0, 1, 2, 3, 4, 5, 6, 7])
+print(f"b -> a, mappings: {align.y2x.data}")  # array([0, 1, 2, 3, 4, 5, 6, 7])
 ```
 
 Here are some insights from the alignment information generated in the example
@@ -1433,10 +1433,10 @@ above:
 - The one-to-one mappings for the first four tokens are identical, which means
   they map to each other. This makes sense because they're also identical in the
   input: `"i"`, `"listened"`, `"to"` and `"obama"`.
-- The value of `x2y.dataXd[6]` is `5`, which means that `other_tokens[6]`
+- The value of `x2y.data[6]` is `5`, which means that `other_tokens[6]`
   (`"podcasts"`) aligns to `spacy_tokens[5]` (also `"podcasts"`).
-- `x2y.dataXd[4]` and `x2y.dataXd[5]` are both `4`, which means that both tokens
-  4 and 5 of `other_tokens` (`"'"` and `"s"`) align to token 4 of `spacy_tokens`
+- `x2y.data[4]` and `x2y.data[5]` are both `4`, which means that both tokens 4
+  and 5 of `other_tokens` (`"'"` and `"s"`) align to token 4 of `spacy_tokens`
   (`"'s"`).
 
 <Infobox title="Important note" variant="warning">

From 7c98245c0c0f9c6c0c4a523c0bf1a75690e58620 Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Wed, 14 Sep 2022 17:05:22 +0200
Subject: [PATCH 095/174] Add levenshtein from polyleven (#11418)

Add a simple levenshtein distance function using the implementation from
the polyleven library as `spacy.matcher.levenshtein`.
---
 .gitignore                              |   1 +
 licenses/3rd_party_licenses.txt         |  31 ++
 setup.py                                |  11 +
 spacy/matcher/__init__.py               |   3 +-
 spacy/matcher/levenshtein.pyx           |  15 +
 spacy/matcher/polyleven.c               | 384 ++++++++++++++++++++++++
 spacy/tests/matcher/test_levenshtein.py |  36 +++
 7 files changed, 480 insertions(+), 1 deletion(-)
 create mode 100644 spacy/matcher/levenshtein.pyx
 create mode 100644 spacy/matcher/polyleven.c
 create mode 100644 spacy/tests/matcher/test_levenshtein.py

diff --git a/.gitignore b/.gitignore
index ac72f2bbf..ac333f958 100644
--- a/.gitignore
+++ b/.gitignore
@@ -24,6 +24,7 @@ quickstart-training-generator.js
 cythonize.json
 spacy/*.html
 *.cpp
+*.c
 *.so
 
 # Vim / VSCode / editors
diff --git a/licenses/3rd_party_licenses.txt b/licenses/3rd_party_licenses.txt
index d58da9c4a..851e09585 100644
--- a/licenses/3rd_party_licenses.txt
+++ b/licenses/3rd_party_licenses.txt
@@ -127,3 +127,34 @@ distributed under the License is distributed on an "AS IS" BASIS,
 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 See the License for the specific language governing permissions and
 limitations under the License.
+
+
+polyleven
+---------
+
+* Files: spacy/matcher/polyleven.c
+
+MIT License
+
+Copyright (c) 2021 Fujimoto Seiji <fujimoto@ceptord.net>
+Copyright (c) 2021 Max Bachmann <kontakt@maxbachmann.de>
+Copyright (c) 2022 Nick Mazuk
+Copyright (c) 2022 Michael Weiss <code@mweiss.ch>
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
diff --git a/setup.py b/setup.py
index ec1bd35fa..c4138aa93 100755
--- a/setup.py
+++ b/setup.py
@@ -205,6 +205,17 @@ def setup_package():
         get_python_inc(plat_specific=True),
     ]
     ext_modules = []
+    ext_modules.append(
+        Extension(
+            "spacy.matcher.levenshtein",
+            [
+                "spacy/matcher/levenshtein.pyx",
+                "spacy/matcher/polyleven.c",
+            ],
+            language="c",
+            include_dirs=include_dirs,
+        )
+    )
     for name in MOD_NAMES:
         mod_path = name.replace(".", "/") + ".pyx"
         ext = Extension(
diff --git a/spacy/matcher/__init__.py b/spacy/matcher/__init__.py
index 286844787..a4f164847 100644
--- a/spacy/matcher/__init__.py
+++ b/spacy/matcher/__init__.py
@@ -1,5 +1,6 @@
 from .matcher import Matcher
 from .phrasematcher import PhraseMatcher
 from .dependencymatcher import DependencyMatcher
+from .levenshtein import levenshtein
 
-__all__ = ["Matcher", "PhraseMatcher", "DependencyMatcher"]
+__all__ = ["Matcher", "PhraseMatcher", "DependencyMatcher", "levenshtein"]
diff --git a/spacy/matcher/levenshtein.pyx b/spacy/matcher/levenshtein.pyx
new file mode 100644
index 000000000..8463d913d
--- /dev/null
+++ b/spacy/matcher/levenshtein.pyx
@@ -0,0 +1,15 @@
+# cython: profile=True, binding=True, infer_types=True
+from cpython.object cimport PyObject
+from libc.stdint cimport int64_t
+
+from typing import Optional
+
+
+cdef extern from "polyleven.c":
+    int64_t polyleven(PyObject *o1, PyObject *o2, int64_t k)
+
+
+cpdef int64_t levenshtein(a: str, b: str, k: Optional[int] = None):
+    if k is None:
+        k = -1
+    return polyleven(<PyObject*>a, <PyObject*>b, k)
diff --git a/spacy/matcher/polyleven.c b/spacy/matcher/polyleven.c
new file mode 100644
index 000000000..2f2b8826c
--- /dev/null
+++ b/spacy/matcher/polyleven.c
@@ -0,0 +1,384 @@
+/*
+ * Adapted from Polyleven (https://ceptord.net/)
+ *
+ * Source: https://github.com/fujimotos/polyleven/blob/c3f95a080626c5652f0151a2e449963288ccae84/polyleven.c
+ *
+ * Copyright (c) 2021 Fujimoto Seiji <fujimoto@ceptord.net>
+ * Copyright (c) 2021 Max Bachmann <kontakt@maxbachmann.de>
+ * Copyright (c) 2022 Nick Mazuk
+ * Copyright (c) 2022 Michael Weiss <code@mweiss.ch>
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to deal
+ * in the Software without restriction, including without limitation the rights
+ * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+
+#include <Python.h>
+#include <stdint.h>
+
+#define MIN(a,b) ((a) < (b) ? (a) : (b))
+#define MAX(a,b) ((a) > (b) ? (a) : (b))
+#define CDIV(a,b) ((a) / (b) + ((a) % (b) > 0))
+#define BIT(i,n) (((i) >> (n)) & 1)
+#define FLIP(i,n) ((i) ^ ((uint64_t) 1 << (n)))
+#define ISASCII(kd) ((kd) == PyUnicode_1BYTE_KIND)
+
+/*
+ * Bare bone of PyUnicode
+ */
+struct strbuf {
+    void *ptr;
+    int kind;
+    int64_t len;
+};
+
+static void strbuf_init(struct strbuf *s, PyObject *o)
+{
+    s->ptr = PyUnicode_DATA(o);
+    s->kind = PyUnicode_KIND(o);
+    s->len = PyUnicode_GET_LENGTH(o);
+}
+
+#define strbuf_read(s, i) PyUnicode_READ((s)->kind, (s)->ptr, (i))
+
+/*
+ * An encoded mbleven model table.
+ *
+ * Each 8-bit integer represents an edit sequence, with using two
+ * bits for a single operation.
+ *
+ *   01 = DELETE, 10 = INSERT, 11 = REPLACE
+ *
+ * For example, 13 is '1101' in binary notation, so it means
+ * DELETE + REPLACE.
+ */
+static const uint8_t MBLEVEN_MATRIX[] = {
+     3,   0,  0,  0,  0,  0,  0,  0,
+     1,   0,  0,  0,  0,  0,  0,  0,
+     15,  9,  6,  0,  0,  0,  0,  0,
+     13,  7,  0,  0,  0,  0,  0,  0,
+     5,   0,  0,  0,  0,  0,  0,  0,
+     63, 39, 45, 57, 54, 30, 27,  0,
+     61, 55, 31, 37, 25, 22,  0,  0,
+     53, 29, 23,  0,  0,  0,  0,  0,
+     21,  0,  0,  0,  0,  0,  0,  0,
+};
+
+#define MBLEVEN_MATRIX_GET(k, d) ((((k) + (k) * (k)) / 2 - 1) + (d)) * 8
+
+static int64_t mbleven_ascii(char *s1, int64_t len1,
+                             char *s2, int64_t len2, int k)
+{
+    int pos;
+    uint8_t m;
+    int64_t i, j, c, r;
+
+    pos = MBLEVEN_MATRIX_GET(k, len1 - len2);
+    r = k + 1;
+
+    while (MBLEVEN_MATRIX[pos]) {
+        m = MBLEVEN_MATRIX[pos++];
+        i = j = c = 0;
+        while (i < len1 && j < len2) {
+            if (s1[i] != s2[j]) {
+                c++;
+                if (!m) break;
+                if (m & 1) i++;
+                if (m & 2) j++;
+                m >>= 2;
+            } else {
+                i++;
+                j++;
+            }
+        }
+        c += (len1 - i) + (len2 - j);
+        r = MIN(r, c);
+        if (r < 2) {
+            return r;
+        }
+    }
+    return r;
+}
+
+static int64_t mbleven(PyObject *o1, PyObject *o2, int64_t k)
+{
+    int pos;
+    uint8_t m;
+    int64_t i, j, c, r;
+    struct strbuf s1, s2;
+
+    strbuf_init(&s1, o1);
+    strbuf_init(&s2, o2);
+
+    if (s1.len < s2.len)
+        return mbleven(o2, o1, k);
+
+    if (k > 3)
+        return -1;
+
+    if (k < s1.len - s2.len)
+        return k + 1;
+
+    if (ISASCII(s1.kind) && ISASCII(s2.kind))
+        return mbleven_ascii(s1.ptr, s1.len, s2.ptr, s2.len, k);
+
+    pos = MBLEVEN_MATRIX_GET(k, s1.len - s2.len);
+    r = k + 1;
+
+    while (MBLEVEN_MATRIX[pos]) {
+        m = MBLEVEN_MATRIX[pos++];
+        i = j = c = 0;
+        while (i < s1.len && j < s2.len) {
+            if (strbuf_read(&s1, i) != strbuf_read(&s2, j)) {
+                c++;
+                if (!m) break;
+                if (m & 1) i++;
+                if (m & 2) j++;
+                m >>= 2;
+            } else {
+                i++;
+                j++;
+            }
+        }
+        c += (s1.len - i) + (s2.len - j);
+        r = MIN(r, c);
+        if (r < 2) {
+            return r;
+        }
+    }
+    return r;
+}
+
+/*
+ * Data structure to store Peq (equality bit-vector).
+ */
+struct blockmap_entry {
+    uint32_t key[128];
+    uint64_t val[128];
+};
+
+struct blockmap {
+    int64_t nr;
+    struct blockmap_entry *list;
+};
+
+#define blockmap_key(c) ((c) | 0x80000000U)
+#define blockmap_hash(c) ((c) % 128)
+
+static int blockmap_init(struct blockmap *map, struct strbuf *s)
+{
+    int64_t i;
+    struct blockmap_entry *be;
+    uint32_t c, k;
+    uint8_t h;
+
+    map->nr = CDIV(s->len, 64);
+    map->list = calloc(1,  map->nr * sizeof(struct blockmap_entry));
+    if (map->list == NULL) {
+        PyErr_NoMemory();
+        return -1;
+    }
+
+    for (i = 0; i < s->len; i++) {
+        be = &(map->list[i / 64]);
+        c = strbuf_read(s, i);
+        h = blockmap_hash(c);
+        k = blockmap_key(c);
+
+        while (be->key[h] && be->key[h] != k)
+            h = blockmap_hash(h + 1);
+        be->key[h] = k;
+        be->val[h] |= (uint64_t) 1 << (i % 64);
+    }
+    return 0;
+}
+
+static void blockmap_clear(struct blockmap *map)
+{
+    if (map->list)
+        free(map->list);
+    map->list = NULL;
+    map->nr = 0;
+}
+
+static uint64_t blockmap_get(struct blockmap *map, int block, uint32_t c)
+{
+    struct blockmap_entry *be;
+    uint8_t h;
+    uint32_t k;
+
+    h = blockmap_hash(c);
+    k = blockmap_key(c);
+
+    be = &(map->list[block]);
+    while (be->key[h] && be->key[h] != k)
+        h = blockmap_hash(h + 1);
+    return be->key[h] == k ? be->val[h] : 0;
+}
+
+/*
+ * Myers' bit-parallel algorithm
+ *
+ * See: G. Myers. "A fast bit-vector algorithm for approximate string
+ *      matching based on dynamic programming." Journal of the ACM, 1999.
+ */
+static int64_t myers1999_block(struct strbuf *s1, struct strbuf *s2,
+                               struct blockmap *map)
+{
+    uint64_t Eq, Xv, Xh, Ph, Mh, Pv, Mv, Last;
+    uint64_t *Mhc, *Phc;
+    int64_t i, b, hsize, vsize, Score;
+    uint8_t Pb, Mb;
+
+    hsize = CDIV(s1->len, 64);
+    vsize = CDIV(s2->len, 64);
+    Score = s2->len;
+
+    Phc = malloc(hsize * 2 * sizeof(uint64_t));
+    if (Phc == NULL) {
+        PyErr_NoMemory();
+        return -1;
+    }
+    Mhc = Phc + hsize;
+    memset(Phc, -1, hsize * sizeof(uint64_t));
+    memset(Mhc, 0, hsize * sizeof(uint64_t));
+    Last = (uint64_t)1 << ((s2->len - 1) % 64);
+
+    for (b = 0; b < vsize; b++) {
+        Mv = 0;
+        Pv = (uint64_t) -1;
+        Score = s2->len;
+
+        for (i = 0; i < s1->len; i++) {
+            Eq = blockmap_get(map, b, strbuf_read(s1, i));
+
+            Pb = BIT(Phc[i / 64], i % 64);
+            Mb = BIT(Mhc[i / 64], i % 64);
+
+            Xv = Eq | Mv;
+            Xh = ((((Eq | Mb) & Pv) + Pv) ^ Pv) | Eq | Mb;
+
+            Ph = Mv | ~ (Xh | Pv);
+            Mh = Pv & Xh;
+
+            if (Ph & Last) Score++;
+            if (Mh & Last) Score--;
+
+            if ((Ph >> 63) ^ Pb)
+                Phc[i / 64] = FLIP(Phc[i / 64], i % 64);
+
+            if ((Mh >> 63) ^ Mb)
+                Mhc[i / 64] = FLIP(Mhc[i / 64], i % 64);
+
+            Ph = (Ph << 1) | Pb;
+            Mh = (Mh << 1) | Mb;
+
+            Pv = Mh | ~ (Xv | Ph);
+            Mv = Ph & Xv;
+        }
+    }
+    free(Phc);
+    return Score;
+}
+
+static int64_t myers1999_simple(uint8_t *s1, int64_t len1, uint8_t *s2, int64_t len2)
+{
+    uint64_t Peq[256];
+    uint64_t Eq, Xv, Xh, Ph, Mh, Pv, Mv, Last;
+    int64_t i;
+    int64_t Score = len2;
+
+    memset(Peq, 0, sizeof(Peq));
+
+    for (i = 0; i < len2; i++)
+        Peq[s2[i]] |= (uint64_t) 1 << i;
+
+    Mv = 0;
+    Pv = (uint64_t) -1;
+    Last = (uint64_t) 1 << (len2 - 1);
+
+    for (i = 0; i < len1; i++) {
+        Eq = Peq[s1[i]];
+
+        Xv = Eq | Mv;
+        Xh = (((Eq & Pv) + Pv) ^ Pv) | Eq;
+
+        Ph = Mv | ~ (Xh | Pv);
+        Mh = Pv & Xh;
+
+        if (Ph & Last) Score++;
+        if (Mh & Last) Score--;
+
+        Ph = (Ph << 1) | 1;
+        Mh = (Mh << 1);
+
+        Pv = Mh | ~ (Xv | Ph);
+        Mv = Ph & Xv;
+    }
+    return Score;
+}
+
+static int64_t myers1999(PyObject *o1, PyObject *o2)
+{
+    struct strbuf s1, s2;
+    struct blockmap map;
+    int64_t ret;
+
+    strbuf_init(&s1, o1);
+    strbuf_init(&s2, o2);
+
+    if (s1.len < s2.len)
+        return myers1999(o2, o1);
+
+    if (ISASCII(s1.kind) && ISASCII(s2.kind) && s2.len < 65)
+        return myers1999_simple(s1.ptr, s1.len, s2.ptr, s2.len);
+
+    if (blockmap_init(&map, &s2))
+        return -1;
+
+    ret = myers1999_block(&s1, &s2, &map);
+    blockmap_clear(&map);
+    return ret;
+}
+
+/*
+ * Interface functions
+ */
+static int64_t polyleven(PyObject *o1, PyObject *o2, int64_t k)
+{
+    int64_t len1, len2;
+
+    len1 = PyUnicode_GET_LENGTH(o1);
+    len2 = PyUnicode_GET_LENGTH(o2);
+
+    if (len1 < len2)
+        return polyleven(o2, o1, k);
+
+    if (k == 0)
+        return PyUnicode_Compare(o1, o2) ? 1 : 0;
+
+    if (0 < k && k < len1 - len2)
+        return k + 1;
+
+    if (len2 == 0)
+        return len1;
+
+    if (0 < k && k < 4)
+        return mbleven(o1, o2, k);
+
+    return myers1999(o1, o2);
+}
diff --git a/spacy/tests/matcher/test_levenshtein.py b/spacy/tests/matcher/test_levenshtein.py
new file mode 100644
index 000000000..6c7793f63
--- /dev/null
+++ b/spacy/tests/matcher/test_levenshtein.py
@@ -0,0 +1,36 @@
+import pytest
+from spacy.matcher import levenshtein
+
+
+# empty string plus 10 random ASCII, 10 random unicode, and 2 random long tests
+# from polyleven
+@pytest.mark.parametrize(
+    "dist,a,b",
+    [
+        (0, "", ""),
+        (4, "bbcb", "caba"),
+        (3, "abcb", "cacc"),
+        (3, "aa", "ccc"),
+        (1, "cca", "ccac"),
+        (1, "aba", "aa"),
+        (4, "bcbb", "abac"),
+        (3, "acbc", "bba"),
+        (3, "cbba", "a"),
+        (2, "bcc", "ba"),
+        (4, "aaa", "ccbb"),
+        (3, "うあい", "いいうい"),
+        (2, "あううい", "うあい"),
+        (3, "いういい", "うううあ"),
+        (2, "うい", "あいあ"),
+        (2, "いあい", "いう"),
+        (1, "いい", "あいい"),
+        (3, "あうあ", "いいああ"),
+        (4, "いあうう", "ううああ"),
+        (3, "いあいい", "ういああ"),
+        (3, "いいああ", "ううあう"),
+        (166,"TCTGGGCACGGATTCGTCAGATTCCATGTCCATATTTGAGGCTCTTGCAGGCAAAATTTGGGCATGTGAACTCCTTATAGTCCCCGTGC","ATATGGATTGGGGGCATTCAAAGATACGGTTTCCCTTTCTTCAGTTTCGCGCGGCGCACGTCCGGGTGCGAGCCAGTTCGTCTTACTCACATTGTCGACTTCACGAATCGCGCATGATGTGCTTAGCCTGTACTTACGAACGAACTTTCGGTCCAAATACATTCTATCAACACCGAGGTATCCGTGCCACACGCCGAAGCTCGACCGTGTTCGTTGAGAGGTGGAAATGGTAAAAGATGAACATAGTC"),
+        (111,"GGTTCGGCCGAATTCATAGAGCGTGGTAGTCGACGGTATCCCGCCTGGTAGGGGCCCCTTCTACCTAGCGGAAGTTTGTCAGTACTCTATAACACGAGGGCCTCTCACACCCTAGATCGTCCAGCCACTCGAAGATCGCAGCACCCTTACAGAAAGGCATTAATGTTTCTCCTAGCACTTGTGCAATGGTGAAGGAGTGATG","CGTAACACTTCGCGCTACTGGGCTGCAACGTCTTGGGCATACATGCAAGATTATCTAATGCAAGCTTGAGCCCCGCTTGCGGAATTTCCCTAATCGGGGTCCCTTCCTGTTACGATAAGGACGCGTGCACT"),
+    ],
+)
+def test_levenshtein(dist, a, b):
+    assert levenshtein(a, b) == dist

From ca1ad67458d96562ab28d03892e926908cb583e1 Mon Sep 17 00:00:00 2001
From: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Date: Thu, 15 Sep 2022 15:51:19 +0200
Subject: [PATCH 096/174] disable mypy run for Python 3.10 (#11508)

---
 .github/azure-steps.yml | 1 +
 1 file changed, 1 insertion(+)

diff --git a/.github/azure-steps.yml b/.github/azure-steps.yml
index 18224ba8c..c7722391f 100644
--- a/.github/azure-steps.yml
+++ b/.github/azure-steps.yml
@@ -27,6 +27,7 @@ steps:
 
   - script: python -m mypy spacy
     displayName: 'Run mypy'
+    condition: ne(variables['python_version'], '3.10')
 
   - task: DeleteFiles@1
     inputs:

From 0509f908743afc86a185346ca6cb2e4789041732 Mon Sep 17 00:00:00 2001
From: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Date: Thu, 15 Sep 2022 17:29:42 +0200
Subject: [PATCH 097/174] add dot (#11500)

---
 spacy/errors.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/spacy/errors.py b/spacy/errors.py
index 5ee1476c2..f55b378e9 100644
--- a/spacy/errors.py
+++ b/spacy/errors.py
@@ -707,7 +707,7 @@ class Errors(metaclass=ErrorsWithCodes):
             "need to modify the pipeline, use the built-in methods like "
             "`nlp.add_pipe`, `nlp.remove_pipe`, `nlp.disable_pipe` or "
             "`nlp.enable_pipe` instead.")
-    E927 = ("Can't write to frozen list Maybe you're trying to modify a computed "
+    E927 = ("Can't write to frozen list. Maybe you're trying to modify a computed "
             "property or default function argument?")
     E928 = ("A KnowledgeBase can only be serialized to/from from a directory, "
             "but the provided argument {loc} points to a file.")

From d5c8498f2f8c26fdfb1f18aafeeebbe94e6126bb Mon Sep 17 00:00:00 2001
From: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Date: Thu, 15 Sep 2022 17:41:25 +0200
Subject: [PATCH 098/174] disable mypy run for Python 3.10 (#11508) (#11511)

---
 .github/azure-steps.yml | 1 +
 1 file changed, 1 insertion(+)

diff --git a/.github/azure-steps.yml b/.github/azure-steps.yml
index 18224ba8c..c7722391f 100644
--- a/.github/azure-steps.yml
+++ b/.github/azure-steps.yml
@@ -27,6 +27,7 @@ steps:
 
   - script: python -m mypy spacy
     displayName: 'Run mypy'
+    condition: ne(variables['python_version'], '3.10')
 
   - task: DeleteFiles@1
     inputs:

From df0b815c2382f572a127e4a35dba30cf1fa9fe45 Mon Sep 17 00:00:00 2001
From: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Date: Fri, 16 Sep 2022 09:26:33 +0200
Subject: [PATCH 099/174] more explicit Example constructor example (#11489)

* make constructor example for Example more explicit

* shorten example and add spaces
---
 website/docs/api/example.md | 12 +++++++-----
 1 file changed, 7 insertions(+), 5 deletions(-)

diff --git a/website/docs/api/example.md b/website/docs/api/example.md
index 0228e8935..63768d58f 100644
--- a/website/docs/api/example.md
+++ b/website/docs/api/example.md
@@ -23,11 +23,13 @@ both documents.
 > ```python
 > from spacy.tokens import Doc
 > from spacy.training import Example
->
-> words = ["hello", "world", "!"]
-> spaces = [True, False, False]
-> predicted = Doc(nlp.vocab, words=words, spaces=spaces)
-> reference = parse_gold_doc(my_data)
+> pred_words = ["Apply", "some", "sunscreen"]
+> pred_spaces = [True, True, False]
+> gold_words = ["Apply", "some", "sun", "screen"]
+> gold_spaces = [True, True, False, False]
+> gold_tags = ["VERB", "DET", "NOUN", "NOUN"]
+> predicted = Doc(nlp.vocab, words=pred_words, spaces=pred_spaces)
+> reference = Doc(nlp.vocab, words=gold_words, spaces=gold_spaces, tags=gold_tags)
 > example = Example(predicted, reference)
 > ```
 

From 279358be63a6f32c49c2c89d4657a5239f238d9e Mon Sep 17 00:00:00 2001
From: "github-actions[bot]"
 <41898282+github-actions[bot]@users.noreply.github.com>
Date: Fri, 16 Sep 2022 11:50:19 +0200
Subject: [PATCH 100/174] Auto-format code with black (#11513)

Co-authored-by: explosion-bot <explosion-bot@users.noreply.github.com>
---
 spacy/tests/matcher/test_levenshtein.py | 12 ++++++++++--
 1 file changed, 10 insertions(+), 2 deletions(-)

diff --git a/spacy/tests/matcher/test_levenshtein.py b/spacy/tests/matcher/test_levenshtein.py
index 6c7793f63..d30e36132 100644
--- a/spacy/tests/matcher/test_levenshtein.py
+++ b/spacy/tests/matcher/test_levenshtein.py
@@ -28,8 +28,16 @@ from spacy.matcher import levenshtein
         (4, "いあうう", "ううああ"),
         (3, "いあいい", "ういああ"),
         (3, "いいああ", "ううあう"),
-        (166,"TCTGGGCACGGATTCGTCAGATTCCATGTCCATATTTGAGGCTCTTGCAGGCAAAATTTGGGCATGTGAACTCCTTATAGTCCCCGTGC","ATATGGATTGGGGGCATTCAAAGATACGGTTTCCCTTTCTTCAGTTTCGCGCGGCGCACGTCCGGGTGCGAGCCAGTTCGTCTTACTCACATTGTCGACTTCACGAATCGCGCATGATGTGCTTAGCCTGTACTTACGAACGAACTTTCGGTCCAAATACATTCTATCAACACCGAGGTATCCGTGCCACACGCCGAAGCTCGACCGTGTTCGTTGAGAGGTGGAAATGGTAAAAGATGAACATAGTC"),
-        (111,"GGTTCGGCCGAATTCATAGAGCGTGGTAGTCGACGGTATCCCGCCTGGTAGGGGCCCCTTCTACCTAGCGGAAGTTTGTCAGTACTCTATAACACGAGGGCCTCTCACACCCTAGATCGTCCAGCCACTCGAAGATCGCAGCACCCTTACAGAAAGGCATTAATGTTTCTCCTAGCACTTGTGCAATGGTGAAGGAGTGATG","CGTAACACTTCGCGCTACTGGGCTGCAACGTCTTGGGCATACATGCAAGATTATCTAATGCAAGCTTGAGCCCCGCTTGCGGAATTTCCCTAATCGGGGTCCCTTCCTGTTACGATAAGGACGCGTGCACT"),
+        (
+            166,
+            "TCTGGGCACGGATTCGTCAGATTCCATGTCCATATTTGAGGCTCTTGCAGGCAAAATTTGGGCATGTGAACTCCTTATAGTCCCCGTGC",
+            "ATATGGATTGGGGGCATTCAAAGATACGGTTTCCCTTTCTTCAGTTTCGCGCGGCGCACGTCCGGGTGCGAGCCAGTTCGTCTTACTCACATTGTCGACTTCACGAATCGCGCATGATGTGCTTAGCCTGTACTTACGAACGAACTTTCGGTCCAAATACATTCTATCAACACCGAGGTATCCGTGCCACACGCCGAAGCTCGACCGTGTTCGTTGAGAGGTGGAAATGGTAAAAGATGAACATAGTC",
+        ),
+        (
+            111,
+            "GGTTCGGCCGAATTCATAGAGCGTGGTAGTCGACGGTATCCCGCCTGGTAGGGGCCCCTTCTACCTAGCGGAAGTTTGTCAGTACTCTATAACACGAGGGCCTCTCACACCCTAGATCGTCCAGCCACTCGAAGATCGCAGCACCCTTACAGAAAGGCATTAATGTTTCTCCTAGCACTTGTGCAATGGTGAAGGAGTGATG",
+            "CGTAACACTTCGCGCTACTGGGCTGCAACGTCTTGGGCATACATGCAAGATTATCTAATGCAAGCTTGAGCCCCGCTTGCGGAATTTCCCTAATCGGGGTCCCTTCCTGTTACGATAAGGACGCGTGCACT",
+        ),
     ],
 )
 def test_levenshtein(dist, a, b):

From af9b01ef97d934a8601aff46d8341fdaf78b88df Mon Sep 17 00:00:00 2001
From: Raphael Mitsch <r.mitsch@outlook.com>
Date: Fri, 16 Sep 2022 16:54:31 +0200
Subject: [PATCH 101/174] Add dependency check to project step runs (#11226)

* Add dependency check to project step running.

* Fix dependency mismatch warning.

* Remove newline.

* Add types-setuptools to setup.cfg.

* Move types-setuptools to test requirements. Move warnings into _validate_requirements(). Handle file reading in project_run().

* Remove newline formatting for output of package conflicts.

* Show full version conflict message instead of just package name.

* Update spacy/cli/project/run.py

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

* Fix typo.

* Re-add rephrasing of message for conflicting packages. Remove requirements path redundancy.

* Update spacy/cli/project/run.py

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

* Update spacy/cli/project/run.py

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

* Print unified message for requirement conflicts and missing requirements.

* Update spacy/cli/project/run.py

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

* Fix warning message.

* Print conflict/missing messages individually.

* Print conflict/missing messages individually.

* Add check_requirements setting in project.yml to disable requirements check.

* Update website/docs/usage/projects.md

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

* Update website/docs/usage/projects.md

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

* Update description of project.yml structure in projects.md.

* Update website/docs/usage/projects.md

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Prettify projects docs.

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
---
 requirements.txt               |  1 +
 spacy/cli/project/run.py       | 40 +++++++++++++++++++++++++++++++++-
 website/docs/usage/projects.md | 35 ++++++++++++++++++-----------
 3 files changed, 62 insertions(+), 14 deletions(-)

diff --git a/requirements.txt b/requirements.txt
index 3e8501b2f..e45fde787 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -33,6 +33,7 @@ hypothesis>=3.27.0,<7.0.0
 mypy>=0.910,<0.970; platform_machine!='aarch64'
 types-dataclasses>=0.1.3; python_version < "3.7"
 types-mock>=0.1.1
+types-setuptools>=57.0.0
 types-requests
 types-setuptools>=57.0.0
 black>=22.0,<23.0
diff --git a/spacy/cli/project/run.py b/spacy/cli/project/run.py
index d42d95465..ebab7471e 100644
--- a/spacy/cli/project/run.py
+++ b/spacy/cli/project/run.py
@@ -1,5 +1,8 @@
-from typing import Optional, List, Dict, Sequence, Any, Iterable
+from typing import Optional, List, Dict, Sequence, Any, Iterable, Tuple
+import os.path
 from pathlib import Path
+
+import pkg_resources
 from wasabi import msg
 from wasabi.util import locale_escape
 import sys
@@ -71,6 +74,12 @@ def project_run(
     commands = {cmd["name"]: cmd for cmd in config.get("commands", [])}
     workflows = config.get("workflows", {})
     validate_subcommand(list(commands.keys()), list(workflows.keys()), subcommand)
+
+    req_path = project_dir / "requirements.txt"
+    if config.get("check_requirements", True) and os.path.exists(req_path):
+        with req_path.open() as requirements_file:
+            _check_requirements([req.replace("\n", "") for req in requirements_file])
+
     if subcommand in workflows:
         msg.info(f"Running workflow '{subcommand}'")
         for cmd in workflows[subcommand]:
@@ -310,3 +319,32 @@ def get_fileinfo(project_dir: Path, paths: List[str]) -> List[Dict[str, Optional
         md5 = get_checksum(file_path) if file_path.exists() else None
         data.append({"path": path, "md5": md5})
     return data
+
+
+def _check_requirements(requirements: List[str]) -> Tuple[bool, bool]:
+    """Checks whether requirements are installed and free of version conflicts.
+    requirements (List[str]): List of requirements.
+    RETURNS (Tuple[bool, bool]): Whether (1) any packages couldn't be imported, (2) any packages with version conflicts
+        exist.
+    """
+
+    failed_pkgs_msgs: List[str] = []
+    conflicting_pkgs_msgs: List[str] = []
+
+    for req in requirements:
+        try:
+            pkg_resources.require(req)
+        except pkg_resources.DistributionNotFound as dnf:
+            failed_pkgs_msgs.append(dnf.report())
+        except pkg_resources.VersionConflict as vc:
+            conflicting_pkgs_msgs.append(vc.report())
+
+    if len(failed_pkgs_msgs) or len(conflicting_pkgs_msgs):
+        msg.warn(
+            title="Missing requirements or requirement conflicts detected. Make sure your Python environment is set up "
+            "correctly and you installed all requirements specified in your project's requirements.txt: "
+        )
+        for pgk_msg in failed_pkgs_msgs + conflicting_pkgs_msgs:
+            msg.text(pgk_msg)
+
+    return len(failed_pkgs_msgs) > 0, len(conflicting_pkgs_msgs) > 0
diff --git a/website/docs/usage/projects.md b/website/docs/usage/projects.md
index 35150035a..4797bbfe3 100644
--- a/website/docs/usage/projects.md
+++ b/website/docs/usage/projects.md
@@ -148,6 +148,13 @@ skipped. You can also set `--force` to force re-running a command, or `--dry` to
 perform a "dry run" and see what would happen (without actually running the
 script).
 
+Since spaCy v3.4.2, `spacy projects run` checks your installed dependencies to
+verify that your environment is properly set up and aligns with the project's
+`requirements.txt`, if there is one. If missing or conflicting dependencies are
+detected, a corresponding warning is displayed. If you'd like to disable the
+dependency check, set `check_requirements: false` in your project's
+`project.yml`.
+
 ### 4. Run a workflow {#run-workfow}
 
 > #### project.yml
@@ -226,26 +233,28 @@ pipelines.
 ```yaml
 %%GITHUB_PROJECTS/pipelines/tagger_parser_ud/project.yml
 ```
+
 > #### Tip: Overriding variables on the CLI
 >
-> If you want to override one or more variables on the CLI and are not already specifying a
-> project directory, you need to add `.` as a placeholder:
+> If you want to override one or more variables on the CLI and are not already
+> specifying a project directory, you need to add `.` as a placeholder:
 >
 > ```
 > python -m spacy project run test . --vars.foo bar
 > ```
 
-| Section         | Description                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  |
-| --------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
-| `title`         | An optional project title used in `--help` message and [auto-generated docs](#custom-docs).                                                                                                                                                                                                                                                                                                                                                                                                                  |
-| `description`   | An optional project description used in [auto-generated docs](#custom-docs).                                                                                                                                                                                                                                                                                                                                                                                                                                 |
-| `vars`          | A dictionary of variables that can be referenced in paths, URLs and scripts and overriden on the CLI, just like [`config.cfg` variables](/usage/training#config-interpolation). For example, `${vars.name}` will use the value of the variable `name`. Variables need to be defined in the section `vars`, but can be a nested dict, so you're able to reference `${vars.model.name}`.                                                                                                                                                |
-| `env`           | A dictionary of variables, mapped to the names of environment variables that will be read in when running the project. For example, `${env.name}` will use the value of the environment variable defined as `name`.                                                                                                                                                                                                                                                                                          |
-| `directories`   | An optional list of [directories](#project-files) that should be created in the project for assets, training outputs, metrics etc. spaCy will make sure that these directories always exist.                                                                                                                                                                                                                                                                                                                 |
-| `assets`        | A list of assets that can be fetched with the [`project assets`](/api/cli#project-assets) command. `url` defines a URL or local path, `dest` is the destination file relative to the project directory, and an optional `checksum` ensures that an error is raised if the file's checksum doesn't match. Instead of `url`, you can also provide a `git` block with the keys `repo`, `branch` and `path`, to download from a Git repo.                                                                        |
-| `workflows`     | A dictionary of workflow names, mapped to a list of command names, to execute in order. Workflows can be run with the [`project run`](/api/cli#project-run) command.                                                                                                                                                                                                                                                                                                                                         |
-| `commands`      | A list of named commands. A command can define an optional help message (shown in the CLI when the user adds `--help`) and the `script`, a list of commands to run. The `deps` and `outputs` let you define the created file the command depends on and produces, respectively. This lets spaCy determine whether a command needs to be re-run because its dependencies or outputs changed. Commands can be run as part of a workflow, or separately with the [`project run`](/api/cli#project-run) command. |
-| `spacy_version` | Optional spaCy version range like `>=3.0.0,<3.1.0` that the project is compatible with. If it's loaded with an incompatible version, an error is raised when the project is loaded.                                                                                                                                                                                                                                                                                                                          |
+| Section                                             | Description                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  |
+| --------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
+| `title`                                             | An optional project title used in `--help` message and [auto-generated docs](#custom-docs).                                                                                                                                                                                                                                                                                                                                                                                                                  |
+| `description`                                       | An optional project description used in [auto-generated docs](#custom-docs).                                                                                                                                                                                                                                                                                                                                                                                                                                 |
+| `vars`                                              | A dictionary of variables that can be referenced in paths, URLs and scripts and overriden on the CLI, just like [`config.cfg` variables](/usage/training#config-interpolation). For example, `${vars.name}` will use the value of the variable `name`. Variables need to be defined in the section `vars`, but can be a nested dict, so you're able to reference `${vars.model.name}`.                                                                                                                       |
+| `env`                                               | A dictionary of variables, mapped to the names of environment variables that will be read in when running the project. For example, `${env.name}` will use the value of the environment variable defined as `name`.                                                                                                                                                                                                                                                                                          |
+| `directories`                                       | An optional list of [directories](#project-files) that should be created in the project for assets, training outputs, metrics etc. spaCy will make sure that these directories always exist.                                                                                                                                                                                                                                                                                                                 |
+| `assets`                                            | A list of assets that can be fetched with the [`project assets`](/api/cli#project-assets) command. `url` defines a URL or local path, `dest` is the destination file relative to the project directory, and an optional `checksum` ensures that an error is raised if the file's checksum doesn't match. Instead of `url`, you can also provide a `git` block with the keys `repo`, `branch` and `path`, to download from a Git repo.                                                                        |
+| `workflows`                                         | A dictionary of workflow names, mapped to a list of command names, to execute in order. Workflows can be run with the [`project run`](/api/cli#project-run) command.                                                                                                                                                                                                                                                                                                                                         |
+| `commands`                                          | A list of named commands. A command can define an optional help message (shown in the CLI when the user adds `--help`) and the `script`, a list of commands to run. The `deps` and `outputs` let you define the created file the command depends on and produces, respectively. This lets spaCy determine whether a command needs to be re-run because its dependencies or outputs changed. Commands can be run as part of a workflow, or separately with the [`project run`](/api/cli#project-run) command. |
+| `spacy_version`                                     | Optional spaCy version range like `>=3.0.0,<3.1.0` that the project is compatible with. If it's loaded with an incompatible version, an error is raised when the project is loaded.                                                                                                                                                                                                                                                                                                                          |
+| `check_requirements` <Tag variant="new">3.4.2</Tag> | A flag determining whether to verify that the installed dependencies align with the project's `requirements.txt`. Defaults to `true`.                                                                                                                                                                                                                                                                                                                                                                        |
 
 ### Data assets {#data-assets}
 

From f40d2fac29678111ec600eb7def9d58b174f14a2 Mon Sep 17 00:00:00 2001
From: Basile Dura <bdura@users.noreply.github.com>
Date: Fri, 23 Sep 2022 13:18:51 +0200
Subject: [PATCH 102/174] fix: remove duplicate v3.2 (#11530)

---
 website/meta/sidebars.json | 1 -
 1 file changed, 1 deletion(-)

diff --git a/website/meta/sidebars.json b/website/meta/sidebars.json
index 1b743636c..06fce7742 100644
--- a/website/meta/sidebars.json
+++ b/website/meta/sidebars.json
@@ -12,7 +12,6 @@
                     { "text": "New in v3.0", "url": "/usage/v3" },
                     { "text": "New in v3.1", "url": "/usage/v3-1" },
                     { "text": "New in v3.2", "url": "/usage/v3-2" },
-                    { "text": "New in v3.2", "url": "/usage/v3-2" },
                     { "text": "New in v3.3", "url": "/usage/v3-3" },
                     { "text": "New in v3.4", "url": "/usage/v3-4" }
                 ]

From 6f692a06d54d53f702def1a2ca20a649b7a1b644 Mon Sep 17 00:00:00 2001
From: Richard Hudson <richard@explosion.ai>
Date: Mon, 26 Sep 2022 15:58:21 +0200
Subject: [PATCH 103/174] Remove side effects from Doc.__init__() (#11506)

* Remove side effects from Doc.__init__()

* Changes based on review comment

* Readd test

* Change interface of Doc.__init__()

* Simplify test

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

* Update doc.md

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
---
 spacy/tests/doc/test_doc_api.py | 15 +++++++++++++++
 spacy/tokens/doc.pyi            |  2 +-
 spacy/tokens/doc.pyx            | 12 ++++++------
 website/docs/api/doc.md         | 30 +++++++++++++++---------------
 4 files changed, 37 insertions(+), 22 deletions(-)

diff --git a/spacy/tests/doc/test_doc_api.py b/spacy/tests/doc/test_doc_api.py
index a64ab2ba8..38003dea9 100644
--- a/spacy/tests/doc/test_doc_api.py
+++ b/spacy/tests/doc/test_doc_api.py
@@ -82,6 +82,21 @@ def test_issue2396(en_vocab):
     assert (span.get_lca_matrix() == matrix).all()
 
 
+@pytest.mark.issue(11499)
+def test_init_args_unmodified(en_vocab):
+    words = ["A", "sentence"]
+    ents = ["B-TYPE1", ""]
+    sent_starts = [True, False]
+    Doc(
+        vocab=en_vocab,
+        words=words,
+        ents=ents,
+        sent_starts=sent_starts,
+    )
+    assert ents == ["B-TYPE1", ""]
+    assert sent_starts == [True, False]
+
+
 @pytest.mark.parametrize("text", ["-0.23", "+123,456", "±1"])
 @pytest.mark.parametrize("lang_cls", [English, MultiLanguage])
 @pytest.mark.issue(2782)
diff --git a/spacy/tokens/doc.pyi b/spacy/tokens/doc.pyi
index a40fa74aa..f0cdaee87 100644
--- a/spacy/tokens/doc.pyi
+++ b/spacy/tokens/doc.pyi
@@ -72,7 +72,7 @@ class Doc:
         lemmas: Optional[List[str]] = ...,
         heads: Optional[List[int]] = ...,
         deps: Optional[List[str]] = ...,
-        sent_starts: Optional[List[Union[bool, None]]] = ...,
+        sent_starts: Optional[List[Union[bool, int, None]]] = ...,
         ents: Optional[List[str]] = ...,
     ) -> None: ...
     @property
diff --git a/spacy/tokens/doc.pyx b/spacy/tokens/doc.pyx
index 7ba9a3341..d7d2fd8e6 100644
--- a/spacy/tokens/doc.pyx
+++ b/spacy/tokens/doc.pyx
@@ -217,9 +217,9 @@ cdef class Doc:
             head in the doc. Defaults to None.
         deps (Optional[List[str]]): A list of unicode strings, of the same
             length as words, to assign as token.dep. Defaults to None.
-        sent_starts (Optional[List[Union[bool, None]]]): A list of values, of
-            the same length as words, to assign as token.is_sent_start. Will be
-            overridden by heads if heads is provided. Defaults to None.
+        sent_starts (Optional[List[Union[bool, int, None]]]): A list of values, 
+            of the same length as words, to assign as token.is_sent_start. Will 
+            be overridden by heads if heads is provided. Defaults to None.
         ents (Optional[List[str]]): A list of unicode strings, of the same
             length as words, as IOB tags to assign as token.ent_iob and
             token.ent_type. Defaults to None.
@@ -285,6 +285,7 @@ cdef class Doc:
             heads = [0] * len(deps)
         if heads and not deps:
             raise ValueError(Errors.E1017)
+        sent_starts = list(sent_starts) if sent_starts is not None else None
         if sent_starts is not None:
             for i in range(len(sent_starts)):
                 if sent_starts[i] is True:
@@ -300,12 +301,11 @@ cdef class Doc:
         ent_iobs = None
         ent_types = None
         if ents is not None:
+            ents = [ent if ent != "" else None for ent in ents]
             iob_strings = Token.iob_strings()
             # make valid IOB2 out of IOB1 or IOB2
             for i, ent in enumerate(ents):
-                if ent is "":
-                    ents[i] = None
-                elif ent is not None and not isinstance(ent, str):
+                if ent is not None and not isinstance(ent, str):
                     raise ValueError(Errors.E177.format(tag=ent))
                 if i < len(ents) - 1:
                     # OI -> OB
diff --git a/website/docs/api/doc.md b/website/docs/api/doc.md
index f97f4ad83..f97ed4547 100644
--- a/website/docs/api/doc.md
+++ b/website/docs/api/doc.md
@@ -31,21 +31,21 @@ Construct a `Doc` object. The most common way to get a `Doc` object is via the
 > doc = Doc(nlp.vocab, words=words, spaces=spaces)
 > ```
 
-| Name                                     | Description                                                                                                                                                                                        |
-| ---------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `vocab`                                  | A storage container for lexical types. ~~Vocab~~                                                                                                                                                   |
-| `words`                                  | A list of strings or integer hash values to add to the document as words. ~~Optional[List[Union[str,int]]]~~                                                                                       |
-| `spaces`                                 | A list of boolean values indicating whether each word has a subsequent space. Must have the same length as `words`, if specified. Defaults to a sequence of `True`. ~~Optional[List[bool]]~~       |
-| _keyword-only_                           |                                                                                                                                                                                                    |
-| `user\_data`                             | Optional extra data to attach to the Doc. ~~Dict~~                                                                                                                                                 |
-| `tags` <Tag variant="new">3</Tag>        | A list of strings, of the same length as `words`, to assign as `token.tag` for each word. Defaults to `None`. ~~Optional[List[str]]~~                                                              |
-| `pos` <Tag variant="new">3</Tag>         | A list of strings, of the same length as `words`, to assign as `token.pos` for each word. Defaults to `None`. ~~Optional[List[str]]~~                                                              |
-| `morphs` <Tag variant="new">3</Tag>      | A list of strings, of the same length as `words`, to assign as `token.morph` for each word. Defaults to `None`. ~~Optional[List[str]]~~                                                            |
-| `lemmas` <Tag variant="new">3</Tag>      | A list of strings, of the same length as `words`, to assign as `token.lemma` for each word. Defaults to `None`. ~~Optional[List[str]]~~                                                            |
-| `heads` <Tag variant="new">3</Tag>       | A list of values, of the same length as `words`, to assign as the head for each word. Head indices are the absolute position of the head in the `Doc`. Defaults to `None`. ~~Optional[List[int]]~~ |
-| `deps` <Tag variant="new">3</Tag>        | A list of strings, of the same length as `words`, to assign as `token.dep` for each word. Defaults to `None`. ~~Optional[List[str]]~~                                                              |
-| `sent_starts` <Tag variant="new">3</Tag> | A list of values, of the same length as `words`, to assign as `token.is_sent_start`. Will be overridden by heads if `heads` is provided. Defaults to `None`. ~~Optional[List[Optional[bool]]]~~    |
-| `ents` <Tag variant="new">3</Tag>        | A list of strings, of the same length of `words`, to assign the token-based IOB tag. Defaults to `None`. ~~Optional[List[str]]~~                                                                   |
+| Name                                     | Description                                                                                                                                                                                             |
+| ---------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `vocab`                                  | A storage container for lexical types. ~~Vocab~~                                                                                                                                                        |
+| `words`                                  | A list of strings or integer hash values to add to the document as words. ~~Optional[List[Union[str,int]]]~~                                                                                            |
+| `spaces`                                 | A list of boolean values indicating whether each word has a subsequent space. Must have the same length as `words`, if specified. Defaults to a sequence of `True`. ~~Optional[List[bool]]~~            |
+| _keyword-only_                           |                                                                                                                                                                                                         |
+| `user\_data`                             | Optional extra data to attach to the Doc. ~~Dict~~                                                                                                                                                      |
+| `tags` <Tag variant="new">3</Tag>        | A list of strings, of the same length as `words`, to assign as `token.tag` for each word. Defaults to `None`. ~~Optional[List[str]]~~                                                                   |
+| `pos` <Tag variant="new">3</Tag>         | A list of strings, of the same length as `words`, to assign as `token.pos` for each word. Defaults to `None`. ~~Optional[List[str]]~~                                                                   |
+| `morphs` <Tag variant="new">3</Tag>      | A list of strings, of the same length as `words`, to assign as `token.morph` for each word. Defaults to `None`. ~~Optional[List[str]]~~                                                                 |
+| `lemmas` <Tag variant="new">3</Tag>      | A list of strings, of the same length as `words`, to assign as `token.lemma` for each word. Defaults to `None`. ~~Optional[List[str]]~~                                                                 |
+| `heads` <Tag variant="new">3</Tag>       | A list of values, of the same length as `words`, to assign as the head for each word. Head indices are the absolute position of the head in the `Doc`. Defaults to `None`. ~~Optional[List[int]]~~      |
+| `deps` <Tag variant="new">3</Tag>        | A list of strings, of the same length as `words`, to assign as `token.dep` for each word. Defaults to `None`. ~~Optional[List[str]]~~                                                                   |
+| `sent_starts` <Tag variant="new">3</Tag> | A list of values, of the same length as `words`, to assign as `token.is_sent_start`. Will be overridden by heads if `heads` is provided. Defaults to `None`. ~~Optional[List[Union[bool, int, None]]]~~ |
+| `ents` <Tag variant="new">3</Tag>        | A list of strings, of the same length of `words`, to assign the token-based IOB tag. Defaults to `None`. ~~Optional[List[str]]~~                                                                        |
 
 ## Doc.\_\_getitem\_\_ {#getitem tag="method"}
 

From 936a5f0506d5a117aeae000481560e1fc0031036 Mon Sep 17 00:00:00 2001
From: Paul O'Leary McCann <polm@dampfkraft.com>
Date: Tue, 27 Sep 2022 15:25:24 +0900
Subject: [PATCH 104/174] Fix English pipeline names in 3.4 release notes
 (#11542)

---
 website/docs/usage/v3-4.md | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/website/docs/usage/v3-4.md b/website/docs/usage/v3-4.md
index 7cc4570d5..597fc3cc8 100644
--- a/website/docs/usage/v3-4.md
+++ b/website/docs/usage/v3-4.md
@@ -65,10 +65,10 @@ The English CNN pipelines have new word vectors:
 
 | Package                                         | Model Version |  TAG | Parser LAS | NER F |
 | ----------------------------------------------- | ------------- | ---: | ---------: | ----: |
-| [`en_core_news_md`](/models/en#en_core_news_md) | v3.3.0        | 97.3 |       90.1 |  84.6 |
-| [`en_core_news_md`](/models/en#en_core_news_lg) | v3.4.0        | 97.2 |       90.3 |  85.5 |
-| [`en_core_news_lg`](/models/en#en_core_news_md) | v3.3.0        | 97.4 |       90.1 |  85.3 |
-| [`en_core_news_lg`](/models/en#en_core_news_lg) | v3.4.0        | 97.3 |       90.2 |  85.6 |
+| [`en_core_web_md`](/models/en#en_core_web_md) | v3.3.0        | 97.3 |       90.1 |  84.6 |
+| [`en_core_web_md`](/models/en#en_core_web_lg) | v3.4.0        | 97.2 |       90.3 |  85.5 |
+| [`en_core_web_lg`](/models/en#en_core_web_md) | v3.3.0        | 97.4 |       90.1 |  85.3 |
+| [`en_core_web_lg`](/models/en#en_core_web_lg) | v3.4.0        | 97.3 |       90.2 |  85.6 |
 
 ## Notes about upgrading from v3.3 {#upgrading}
 

From 877671e09a0a72ca20ccbbcd65d7073f588cd320 Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Tue, 27 Sep 2022 10:16:51 +0200
Subject: [PATCH 105/174] Preserve missing entity annotation in augmenters
 (#11540)

Preserve both `-` and `O` annotation in augmenters rather than relying
on `Example.to_dict`'s default support for one option outside of labeled
entity spans.

This is intended as a temporary workaround for augmenters for v3.4.x.
The behavior of `Example` and related IOB utils could be improved in the
general case for v3.5.
---
 spacy/tests/training/test_augmenters.py |  7 +++++--
 spacy/training/augment.py               | 14 +++++++++++++-
 spacy/training/iob_utils.py             |  8 ++++++++
 3 files changed, 26 insertions(+), 3 deletions(-)

diff --git a/spacy/tests/training/test_augmenters.py b/spacy/tests/training/test_augmenters.py
index e3639c5da..35860a199 100644
--- a/spacy/tests/training/test_augmenters.py
+++ b/spacy/tests/training/test_augmenters.py
@@ -31,7 +31,7 @@ def doc(nlp):
     words = ["Sarah", "'s", "sister", "flew", "to", "Silicon", "Valley", "via", "London", "."]
     tags = ["NNP", "POS", "NN", "VBD", "IN", "NNP", "NNP", "IN", "NNP", "."]
     pos = ["PROPN", "PART", "NOUN", "VERB", "ADP", "PROPN", "PROPN", "ADP", "PROPN", "PUNCT"]
-    ents = ["B-PERSON", "I-PERSON", "O", "O", "O", "B-LOC", "I-LOC", "O", "B-GPE", "O"]
+    ents = ["B-PERSON", "I-PERSON", "O", "", "O", "B-LOC", "I-LOC", "O", "B-GPE", "O"]
     cats = {"TRAVEL": 1.0, "BAKING": 0.0}
     # fmt: on
     doc = Doc(nlp.vocab, words=words, tags=tags, pos=pos, ents=ents)
@@ -106,6 +106,7 @@ def test_lowercase_augmenter(nlp, doc):
     assert [(e.start, e.end, e.label) for e in eg.reference.ents] == ents
     for ref_ent, orig_ent in zip(eg.reference.ents, doc.ents):
         assert ref_ent.text == orig_ent.text.lower()
+    assert [t.ent_iob for t in doc] == [t.ent_iob for t in eg.reference]
     assert [t.pos_ for t in eg.reference] == [t.pos_ for t in doc]
 
     # check that augmentation works when lowercasing leads to different
@@ -166,7 +167,7 @@ def test_make_whitespace_variant(nlp):
     lemmas = ["they", "fly", "to", "New", "York", "City", ".", "\n", "then", "they", "drive", "to", "Washington", ",", "D.C."]
     heads = [1, 1, 1, 4, 5, 2, 1, 10, 10, 10, 10, 10, 11, 12, 12]
     deps = ["nsubj", "ROOT", "prep", "compound", "compound", "pobj", "punct", "dep", "advmod", "nsubj", "ROOT", "prep", "pobj", "punct", "appos"]
-    ents = ["O", "O", "O", "B-GPE", "I-GPE", "I-GPE", "O", "O", "O", "O", "O", "O", "B-GPE", "O", "B-GPE"]
+    ents = ["O", "", "O", "B-GPE", "I-GPE", "I-GPE", "O", "O", "O", "O", "O", "O", "B-GPE", "O", "B-GPE"]
     # fmt: on
     doc = Doc(
         nlp.vocab,
@@ -215,6 +216,8 @@ def test_make_whitespace_variant(nlp):
             assert mod_ex2.reference[j].head.i == j - 1
         # entities are well-formed
         assert len(doc.ents) == len(mod_ex.reference.ents)
+        # there is one token with missing entity information
+        assert any(t.ent_iob == 0 for t in mod_ex.reference)
         for ent in mod_ex.reference.ents:
             assert not ent[0].is_space
             assert not ent[-1].is_space
diff --git a/spacy/training/augment.py b/spacy/training/augment.py
index 55d780ba4..2fe8c24fb 100644
--- a/spacy/training/augment.py
+++ b/spacy/training/augment.py
@@ -6,7 +6,7 @@ from functools import partial
 
 from ..util import registry
 from .example import Example
-from .iob_utils import split_bilu_label
+from .iob_utils import split_bilu_label, _doc_to_biluo_tags_with_partial
 
 if TYPE_CHECKING:
     from ..language import Language  # noqa: F401
@@ -62,6 +62,9 @@ def combined_augmenter(
     if orth_variants and random.random() < orth_level:
         raw_text = example.text
         orig_dict = example.to_dict()
+        orig_dict["doc_annotation"]["entities"] = _doc_to_biluo_tags_with_partial(
+            example.reference
+        )
         variant_text, variant_token_annot = make_orth_variants(
             nlp,
             raw_text,
@@ -128,6 +131,9 @@ def lower_casing_augmenter(
 
 def make_lowercase_variant(nlp: "Language", example: Example):
     example_dict = example.to_dict()
+    example_dict["doc_annotation"]["entities"] = _doc_to_biluo_tags_with_partial(
+        example.reference
+    )
     doc = nlp.make_doc(example.text.lower())
     example_dict["token_annotation"]["ORTH"] = [t.lower_ for t in example.reference]
     return example.from_dict(doc, example_dict)
@@ -146,6 +152,9 @@ def orth_variants_augmenter(
     else:
         raw_text = example.text
         orig_dict = example.to_dict()
+        orig_dict["doc_annotation"]["entities"] = _doc_to_biluo_tags_with_partial(
+            example.reference
+        )
         variant_text, variant_token_annot = make_orth_variants(
             nlp,
             raw_text,
@@ -248,6 +257,9 @@ def make_whitespace_variant(
     RETURNS (Example): Example with one additional space token.
     """
     example_dict = example.to_dict()
+    example_dict["doc_annotation"]["entities"] = _doc_to_biluo_tags_with_partial(
+        example.reference
+    )
     doc_dict = example_dict.get("doc_annotation", {})
     token_dict = example_dict.get("token_annotation", {})
     # returned unmodified if:
diff --git a/spacy/training/iob_utils.py b/spacy/training/iob_utils.py
index 61f83a1c3..0d4d246b0 100644
--- a/spacy/training/iob_utils.py
+++ b/spacy/training/iob_utils.py
@@ -60,6 +60,14 @@ def doc_to_biluo_tags(doc: Doc, missing: str = "O"):
     )
 
 
+def _doc_to_biluo_tags_with_partial(doc: Doc) -> List[str]:
+    ents = doc_to_biluo_tags(doc, missing="-")
+    for i, token in enumerate(doc):
+        if token.ent_iob == 2:
+            ents[i] = "O"
+    return ents
+
+
 def offsets_to_biluo_tags(
     doc: Doc, entities: Iterable[Tuple[int, int, Union[str, int]]], missing: str = "O"
 ) -> List[str]:

From a44b7d4622108a42ddb95b62b642df6f142a3450 Mon Sep 17 00:00:00 2001
From: Paul O'Leary McCann <polm@dampfkraft.com>
Date: Tue, 27 Sep 2022 18:11:23 +0900
Subject: [PATCH 106/174] Add experimental coref docs (#11291)

* Add experimental coref docs

* Docs cleanup

* Apply suggestions from code review

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Apply changes from code review

* Fix prettier formatting

It seems a period after a number made this think it was a list?

* Update docs on examples for initialize

* Add docs for coref scorers

* Remove 3.4 notes from coref

There won't be a "new" tag until it's in core.

* Add docs for span cleaner

* Fix docs

* Fix docs to match spacy-experimental

These weren't properly updated when the code was moved out of spacy
core.

* More doc fixes

* Formatting

* Update architectures

* Fix links

* Fix another link

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: svlandeg <svlandeg@github.com>
---
 website/docs/api/architectures.md      |  92 ++++++-
 website/docs/api/coref.md              | 353 ++++++++++++++++++++++++
 website/docs/api/pipeline-functions.md |  33 +++
 website/docs/api/scorer.md             |  59 ++++
 website/docs/api/span-resolver.md      | 356 +++++++++++++++++++++++++
 website/meta/sidebars.json             |   2 +
 6 files changed, 889 insertions(+), 6 deletions(-)
 create mode 100644 website/docs/api/coref.md
 create mode 100644 website/docs/api/span-resolver.md

diff --git a/website/docs/api/architectures.md b/website/docs/api/architectures.md
index 2537faff6..4c5447f75 100644
--- a/website/docs/api/architectures.md
+++ b/website/docs/api/architectures.md
@@ -11,6 +11,7 @@ menu:
   - ['Text Classification', 'textcat']
   - ['Span Classification', 'spancat']
   - ['Entity Linking', 'entitylinker']
+  - ['Coreference', 'coref-architectures']
 ---
 
 A **model architecture** is a function that wires up a
@@ -587,8 +588,8 @@ consists of either two or three subnetworks:
   run once for each batch.
 - **lower**: Construct a feature-specific vector for each `(token, feature)`
   pair. This is also run once for each batch. Constructing the state
-  representation is then a matter of summing the component features and
-  applying the non-linearity.
+  representation is then a matter of summing the component features and applying
+  the non-linearity.
 - **upper** (optional): A feed-forward network that predicts scores from the
   state representation. If not present, the output from the lower model is used
   as action scores directly.
@@ -628,8 +629,8 @@ same signature, but the `use_upper` argument was `True` by default.
 > ```
 
 Build a tagger model, using a provided token-to-vector component. The tagger
-model adds a linear layer with softmax activation to predict scores given
-the token vectors.
+model adds a linear layer with softmax activation to predict scores given the
+token vectors.
 
 | Name        | Description                                                                                |
 | ----------- | ------------------------------------------------------------------------------------------ |
@@ -920,5 +921,84 @@ A function that reads an existing `KnowledgeBase` from file.
 A function that takes as input a [`KnowledgeBase`](/api/kb) and a
 [`Span`](/api/span) object denoting a named entity, and returns a list of
 plausible [`Candidate`](/api/kb/#candidate) objects. The default
-`CandidateGenerator` uses the text of a mention to find its potential
-aliases in the `KnowledgeBase`. Note that this function is case-dependent.
+`CandidateGenerator` uses the text of a mention to find its potential aliases in
+the `KnowledgeBase`. Note that this function is case-dependent.
+
+## Coreference {#coref-architectures tag="experimental"}
+
+A [`CoreferenceResolver`](/api/coref) component identifies tokens that refer to
+the same entity. A [`SpanResolver`](/api/span-resolver) component infers spans
+from single tokens. Together these components can be used to reproduce
+traditional coreference models. You can also omit the `SpanResolver` if working
+with only token-level clusters is acceptable.
+
+### spacy-experimental.Coref.v1 {#Coref tag="experimental"}
+
+> #### Example Config
+>
+> ```ini
+>
+> [model]
+> @architectures = "spacy-experimental.Coref.v1"
+> distance_embedding_size = 20
+> dropout = 0.3
+> hidden_size = 1024
+> depth = 2
+> antecedent_limit = 50
+> antecedent_batch_size = 512
+>
+> [model.tok2vec]
+> @architectures = "spacy-transformers.TransformerListener.v1"
+> grad_factor = 1.0
+> upstream = "transformer"
+> pooling = {"@layers":"reduce_mean.v1"}
+> ```
+
+The `Coref` model architecture is a Thinc `Model`.
+
+| Name                      | Description                                                                                                                                                                              |
+| ------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `tok2vec`                 | The [`tok2vec`](#tok2vec) layer of the model. ~~Model~~                                                                                                                                  |
+| `distance_embedding_size` | A representation of the distance between candidates. ~~int~~                                                                                                                             |
+| `dropout`                 | The dropout to use internally. Unlike some Thinc models, this has separate dropout for the internal PyTorch layers. ~~float~~                                                            |
+| `hidden_size`             | Size of the main internal layers. ~~int~~                                                                                                                                                |
+| `depth`                   | Depth of the internal network. ~~int~~                                                                                                                                                   |
+| `antecedent_limit`        | How many candidate antecedents to keep after rough scoring. This has a significant effect on memory usage. Typical values would be 50 to 200, or higher for very long documents. ~~int~~ |
+| `antecedent_batch_size`   | Internal batch size. ~~int~~                                                                                                                                                             |
+| **CREATES**               | The model using the architecture. ~~Model[List[Doc], Floats2d]~~                                                                                                                         |
+
+### spacy-experimental.SpanResolver.v1 {#SpanResolver tag="experimental"}
+
+> #### Example Config
+>
+> ```ini
+>
+> [model]
+> @architectures = "spacy-experimental.SpanResolver.v1"
+> hidden_size = 1024
+> distance_embedding_size = 64
+> conv_channels = 4
+> window_size = 1
+> max_distance = 128
+> prefix = "coref_head_clusters"
+>
+> [model.tok2vec]
+> @architectures = "spacy-transformers.TransformerListener.v1"
+> grad_factor = 1.0
+> upstream = "transformer"
+> pooling = {"@layers":"reduce_mean.v1"}
+> ```
+
+The `SpanResolver` model architecture is a Thinc `Model`. Note that
+`MentionClusters` is `List[List[Tuple[int, int]]]`.
+
+| Name                      | Description                                                                                                          |
+| ------------------------- | -------------------------------------------------------------------------------------------------------------------- |
+| `tok2vec`                 | The [`tok2vec`](#tok2vec) layer of the model. ~~Model~~                                                              |
+| `hidden_size`             | Size of the main internal layers. ~~int~~                                                                            |
+| `distance_embedding_size` | A representation of the distance between two candidates. ~~int~~                                                     |
+| `conv_channels`           | The number of channels in the internal CNN. ~~int~~                                                                  |
+| `window_size`             | The number of neighboring tokens to consider in the internal CNN. `1` means consider one token on each side. ~~int~~ |
+| `max_distance`            | The longest possible length of a predicted span. ~~int~~                                                             |
+| `prefix`                  | The prefix that indicates spans to use for input data. ~~string~~                                                    |
+| **CREATES**               | The model using the architecture. ~~Model[List[Doc], List[MentionClusters]]~~                                        |
diff --git a/website/docs/api/coref.md b/website/docs/api/coref.md
new file mode 100644
index 000000000..8f54422d6
--- /dev/null
+++ b/website/docs/api/coref.md
@@ -0,0 +1,353 @@
+---
+title: CoreferenceResolver
+tag: class,experimental
+source: spacy-experimental/coref/coref_component.py
+teaser: 'Pipeline component for word-level coreference resolution'
+api_base_class: /api/pipe
+api_string_name: coref
+api_trainable: true
+---
+
+> #### Installation
+>
+> ```bash
+> $ pip install -U spacy-experimental
+> ```
+
+<Infobox title="Important note" variant="warning">
+
+This component is not yet integrated into spaCy core, and is available via the
+extension package
+[`spacy-experimental`](https://github.com/explosion/spacy-experimental) starting
+in version 0.6.0. It exposes the component via
+[entry points](/usage/saving-loading/#entry-points), so if you have the package
+installed, using `factory = "experimental_coref"` in your
+[training config](/usage/training#config) or
+`nlp.add_pipe("experimental_coref")` will work out-of-the-box.
+
+</Infobox>
+
+A `CoreferenceResolver` component groups tokens into clusters that refer to the
+same thing. Clusters are represented as SpanGroups that start with a prefix
+(`coref_clusters` by default).
+
+A `CoreferenceResolver` component can be paired with a
+[`SpanResolver`](/api/span-resolver) to expand single tokens to spans.
+
+## Assigned Attributes {#assigned-attributes}
+
+Predictions will be saved to `Doc.spans` as a [`SpanGroup`](/api/spangroup). The
+span key will be a prefix plus a serial number referring to the coreference
+cluster, starting from zero.
+
+The span key prefix defaults to `"coref_clusters"`, but can be passed as a
+parameter.
+
+| Location                                   | Value                                                                                                   |
+| ------------------------------------------ | ------------------------------------------------------------------------------------------------------- |
+| `Doc.spans[prefix + "_" + cluster_number]` | One coreference cluster, represented as single-token spans. Cluster numbers start from 1. ~~SpanGroup~~ |
+
+## Config and implementation {#config}
+
+The default config is defined by the pipeline component factory and describes
+how the component should be configured. You can override its settings via the
+`config` argument on [`nlp.add_pipe`](/api/language#add_pipe) or in your
+[`config.cfg` for training](/usage/training#config). See the
+[model architectures](/api/architectures#coref-architectures) documentation for
+details on the architectures and their arguments and hyperparameters.
+
+> #### Example
+>
+> ```python
+> from spacy_experimental.coref.coref_component import DEFAULT_COREF_MODEL
+> from spacy_experimental.coref.coref_util import DEFAULT_CLUSTER_PREFIX
+> config={
+>     "model": DEFAULT_COREF_MODEL,
+>     "span_cluster_prefix": DEFAULT_CLUSTER_PREFIX,
+> },
+> nlp.add_pipe("experimental_coref", config=config)
+> ```
+
+| Setting               | Description                                                                                                                              |
+| --------------------- | ---------------------------------------------------------------------------------------------------------------------------------------- |
+| `model`               | The [`Model`](https://thinc.ai/docs/api-model) powering the pipeline component. Defaults to [Coref](/api/architectures#Coref). ~~Model~~ |
+| `span_cluster_prefix` | The prefix for the keys for clusters saved to `doc.spans`. Defaults to `coref_clusters`. ~~str~~                                         |
+
+## CoreferenceResolver.\_\_init\_\_ {#init tag="method"}
+
+> #### Example
+>
+> ```python
+> # Construction via add_pipe with default model
+> coref = nlp.add_pipe("experimental_coref")
+>
+> # Construction via add_pipe with custom model
+> config = {"model": {"@architectures": "my_coref.v1"}}
+> coref = nlp.add_pipe("experimental_coref", config=config)
+>
+> # Construction from class
+> from spacy_experimental.coref.coref_component import CoreferenceResolver
+> coref = CoreferenceResolver(nlp.vocab, model)
+> ```
+
+Create a new pipeline instance. In your application, you would normally use a
+shortcut for this and instantiate the component using its string name and
+[`nlp.add_pipe`](/api/language#add_pipe).
+
+| Name                  | Description                                                                                         |
+| --------------------- | --------------------------------------------------------------------------------------------------- |
+| `vocab`               | The shared vocabulary. ~~Vocab~~                                                                    |
+| `model`               | The [`Model`](https://thinc.ai/docs/api-model) powering the pipeline component. ~~Model~~           |
+| `name`                | String name of the component instance. Used to add entries to the `losses` during training. ~~str~~ |
+| _keyword-only_        |                                                                                                     |
+| `span_cluster_prefix` | The prefix for the key for saving clusters of spans. ~~bool~~                                       |
+
+## CoreferenceResolver.\_\_call\_\_ {#call tag="method"}
+
+Apply the pipe to one document. The document is modified in place and returned.
+This usually happens under the hood when the `nlp` object is called on a text
+and all pipeline components are applied to the `Doc` in order. Both
+[`__call__`](/api/coref#call) and [`pipe`](/api/coref#pipe) delegate to the
+[`predict`](/api/coref#predict) and
+[`set_annotations`](/api/coref#set_annotations) methods.
+
+> #### Example
+>
+> ```python
+> doc = nlp("This is a sentence.")
+> coref = nlp.add_pipe("experimental_coref")
+> # This usually happens under the hood
+> processed = coref(doc)
+> ```
+
+| Name        | Description                      |
+| ----------- | -------------------------------- |
+| `doc`       | The document to process. ~~Doc~~ |
+| **RETURNS** | The processed document. ~~Doc~~  |
+
+## CoreferenceResolver.pipe {#pipe tag="method"}
+
+Apply the pipe to a stream of documents. This usually happens under the hood
+when the `nlp` object is called on a text and all pipeline components are
+applied to the `Doc` in order. Both [`__call__`](/api/coref#call) and
+[`pipe`](/api/coref#pipe) delegate to the [`predict`](/api/coref#predict) and
+[`set_annotations`](/api/coref#set_annotations) methods.
+
+> #### Example
+>
+> ```python
+> coref = nlp.add_pipe("experimental_coref")
+> for doc in coref.pipe(docs, batch_size=50):
+>     pass
+> ```
+
+| Name           | Description                                                   |
+| -------------- | ------------------------------------------------------------- |
+| `stream`       | A stream of documents. ~~Iterable[Doc]~~                      |
+| _keyword-only_ |                                                               |
+| `batch_size`   | The number of documents to buffer. Defaults to `128`. ~~int~~ |
+| **YIELDS**     | The processed documents in order. ~~Doc~~                     |
+
+## CoreferenceResolver.initialize {#initialize tag="method"}
+
+Initialize the component for training. `get_examples` should be a function that
+returns an iterable of [`Example`](/api/example) objects. **At least one example
+should be supplied.** The data examples are used to **initialize the model** of
+the component and can either be the full training data or a representative
+sample. Initialization includes validating the network,
+[inferring missing shapes](https://thinc.ai/docs/usage-models#validation) and
+setting up the label scheme based on the data. This method is typically called
+by [`Language.initialize`](/api/language#initialize).
+
+> #### Example
+>
+> ```python
+> coref = nlp.add_pipe("experimental_coref")
+> coref.initialize(lambda: examples, nlp=nlp)
+> ```
+
+| Name           | Description                                                                                                                                                                |
+| -------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `get_examples` | Function that returns gold-standard annotations in the form of [`Example`](/api/example) objects. Must contain at least one `Example`. ~~Callable[[], Iterable[Example]]~~ |
+| _keyword-only_ |                                                                                                                                                                            |
+| `nlp`          | The current `nlp` object. Defaults to `None`. ~~Optional[Language]~~                                                                                                       |
+
+## CoreferenceResolver.predict {#predict tag="method"}
+
+Apply the component's model to a batch of [`Doc`](/api/doc) objects, without
+modifying them. Clusters are returned as a list of `MentionClusters`, one for
+each input `Doc`. A `MentionClusters` instance is just a list of lists of pairs
+of `int`s, where each item corresponds to a cluster, and the `int`s correspond
+to token indices.
+
+> #### Example
+>
+> ```python
+> coref = nlp.add_pipe("experimental_coref")
+> clusters = coref.predict([doc1, doc2])
+> ```
+
+| Name        | Description                                                                  |
+| ----------- | ---------------------------------------------------------------------------- |
+| `docs`      | The documents to predict. ~~Iterable[Doc]~~                                  |
+| **RETURNS** | The predicted coreference clusters for the `docs`. ~~List[MentionClusters]~~ |
+
+## CoreferenceResolver.set_annotations {#set_annotations tag="method"}
+
+Modify a batch of documents, saving coreference clusters in `Doc.spans`.
+
+> #### Example
+>
+> ```python
+> coref = nlp.add_pipe("experimental_coref")
+> clusters = coref.predict([doc1, doc2])
+> coref.set_annotations([doc1, doc2], clusters)
+> ```
+
+| Name       | Description                                                                  |
+| ---------- | ---------------------------------------------------------------------------- |
+| `docs`     | The documents to modify. ~~Iterable[Doc]~~                                   |
+| `clusters` | The predicted coreference clusters for the `docs`. ~~List[MentionClusters]~~ |
+
+## CoreferenceResolver.update {#update tag="method"}
+
+Learn from a batch of [`Example`](/api/example) objects. Delegates to
+[`predict`](/api/coref#predict).
+
+> #### Example
+>
+> ```python
+> coref = nlp.add_pipe("experimental_coref")
+> optimizer = nlp.initialize()
+> losses = coref.update(examples, sgd=optimizer)
+> ```
+
+| Name           | Description                                                                                                              |
+| -------------- | ------------------------------------------------------------------------------------------------------------------------ |
+| `examples`     | A batch of [`Example`](/api/example) objects to learn from. ~~Iterable[Example]~~                                        |
+| _keyword-only_ |                                                                                                                          |
+| `drop`         | The dropout rate. ~~float~~                                                                                              |
+| `sgd`          | An optimizer. Will be created via [`create_optimizer`](#create_optimizer) if not set. ~~Optional[Optimizer]~~            |
+| `losses`       | Optional record of the loss during training. Updated using the component name as the key. ~~Optional[Dict[str, float]]~~ |
+| **RETURNS**    | The updated `losses` dictionary. ~~Dict[str, float]~~                                                                    |
+
+## CoreferenceResolver.create_optimizer {#create_optimizer tag="method"}
+
+Create an optimizer for the pipeline component.
+
+> #### Example
+>
+> ```python
+> coref = nlp.add_pipe("experimental_coref")
+> optimizer = coref.create_optimizer()
+> ```
+
+| Name        | Description                  |
+| ----------- | ---------------------------- |
+| **RETURNS** | The optimizer. ~~Optimizer~~ |
+
+## CoreferenceResolver.use_params {#use_params tag="method, contextmanager"}
+
+Modify the pipe's model, to use the given parameter values. At the end of the
+context, the original parameters are restored.
+
+> #### Example
+>
+> ```python
+> coref = nlp.add_pipe("experimental_coref")
+> with coref.use_params(optimizer.averages):
+>     coref.to_disk("/best_model")
+> ```
+
+| Name     | Description                                        |
+| -------- | -------------------------------------------------- |
+| `params` | The parameter values to use in the model. ~~dict~~ |
+
+## CoreferenceResolver.to_disk {#to_disk tag="method"}
+
+Serialize the pipe to disk.
+
+> #### Example
+>
+> ```python
+> coref = nlp.add_pipe("experimental_coref")
+> coref.to_disk("/path/to/coref")
+> ```
+
+| Name           | Description                                                                                                                                |
+| -------------- | ------------------------------------------------------------------------------------------------------------------------------------------ |
+| `path`         | A path to a directory, which will be created if it doesn't exist. Paths may be either strings or `Path`-like objects. ~~Union[str, Path]~~ |
+| _keyword-only_ |                                                                                                                                            |
+| `exclude`      | String names of [serialization fields](#serialization-fields) to exclude. ~~Iterable[str]~~                                                |
+
+## CoreferenceResolver.from_disk {#from_disk tag="method"}
+
+Load the pipe from disk. Modifies the object in place and returns it.
+
+> #### Example
+>
+> ```python
+> coref = nlp.add_pipe("experimental_coref")
+> coref.from_disk("/path/to/coref")
+> ```
+
+| Name           | Description                                                                                     |
+| -------------- | ----------------------------------------------------------------------------------------------- |
+| `path`         | A path to a directory. Paths may be either strings or `Path`-like objects. ~~Union[str, Path]~~ |
+| _keyword-only_ |                                                                                                 |
+| `exclude`      | String names of [serialization fields](#serialization-fields) to exclude. ~~Iterable[str]~~     |
+| **RETURNS**    | The modified `CoreferenceResolver` object. ~~CoreferenceResolver~~                              |
+
+## CoreferenceResolver.to_bytes {#to_bytes tag="method"}
+
+> #### Example
+>
+> ```python
+> coref = nlp.add_pipe("experimental_coref")
+> coref_bytes = coref.to_bytes()
+> ```
+
+Serialize the pipe to a bytestring, including the `KnowledgeBase`.
+
+| Name           | Description                                                                                 |
+| -------------- | ------------------------------------------------------------------------------------------- |
+| _keyword-only_ |                                                                                             |
+| `exclude`      | String names of [serialization fields](#serialization-fields) to exclude. ~~Iterable[str]~~ |
+| **RETURNS**    | The serialized form of the `CoreferenceResolver` object. ~~bytes~~                          |
+
+## CoreferenceResolver.from_bytes {#from_bytes tag="method"}
+
+Load the pipe from a bytestring. Modifies the object in place and returns it.
+
+> #### Example
+>
+> ```python
+> coref_bytes = coref.to_bytes()
+> coref = nlp.add_pipe("experimental_coref")
+> coref.from_bytes(coref_bytes)
+> ```
+
+| Name           | Description                                                                                 |
+| -------------- | ------------------------------------------------------------------------------------------- |
+| `bytes_data`   | The data to load from. ~~bytes~~                                                            |
+| _keyword-only_ |                                                                                             |
+| `exclude`      | String names of [serialization fields](#serialization-fields) to exclude. ~~Iterable[str]~~ |
+| **RETURNS**    | The `CoreferenceResolver` object. ~~CoreferenceResolver~~                                   |
+
+## Serialization fields {#serialization-fields}
+
+During serialization, spaCy will export several data fields used to restore
+different aspects of the object. If needed, you can exclude them from
+serialization by passing in the string names via the `exclude` argument.
+
+> #### Example
+>
+> ```python
+> data = coref.to_disk("/path", exclude=["vocab"])
+> ```
+
+| Name    | Description                                                    |
+| ------- | -------------------------------------------------------------- |
+| `vocab` | The shared [`Vocab`](/api/vocab).                              |
+| `cfg`   | The config file. You usually don't want to exclude this.       |
+| `model` | The binary model data. You usually don't want to exclude this. |
diff --git a/website/docs/api/pipeline-functions.md b/website/docs/api/pipeline-functions.md
index 1b7017ca7..070292782 100644
--- a/website/docs/api/pipeline-functions.md
+++ b/website/docs/api/pipeline-functions.md
@@ -153,3 +153,36 @@ whole pipeline has run.
 | `attrs`     | A dict of the `Doc` attributes and the values to set them to. Defaults to `{"tensor": None, "_.trf_data": None}` to clean up after `tok2vec` and `transformer` components. ~~dict~~ |
 | `silent`    | If `False`, show warnings if attributes aren't found or can't be set. Defaults to `True`. ~~bool~~                                                                                  |
 | **RETURNS** | The modified `Doc` with the modified attributes. ~~Doc~~                                                                                                                            |
+
+## span_cleaner {#span_cleaner tag="function,experimental"}
+
+Remove `SpanGroup`s from `doc.spans` based on a key prefix. This is used to
+clean up after the [`CoreferenceResolver`](/api/coref) when it's paired with a
+[`SpanResolver`](/api/span-resolver).
+
+<Infobox title="Important note" variant="warning">
+
+This pipeline function is not yet integrated into spaCy core, and is available
+via the extension package
+[`spacy-experimental`](https://github.com/explosion/spacy-experimental) starting
+in version 0.6.0. It exposes the component via
+[entry points](/usage/saving-loading/#entry-points), so if you have the package
+installed, using `factory = "span_cleaner"` in your
+[training config](/usage/training#config) or `nlp.add_pipe("span_cleaner")` will
+work out-of-the-box.
+
+</Infobox>
+
+> #### Example
+>
+> ```python
+> config = {"prefix": "coref_head_clusters"}
+> nlp.add_pipe("span_cleaner", config=config)
+> doc = nlp("text")
+> assert "coref_head_clusters_1" not in doc.spans
+> ```
+
+| Setting     | Description                                                                                                               |
+| ----------- | ------------------------------------------------------------------------------------------------------------------------- |
+| `prefix`    | A prefix to check `SpanGroup` keys for. Any matching groups will be removed. Defaults to `"coref_head_clusters"`. ~~str~~ |
+| **RETURNS** | The modified `Doc` with any matching spans removed. ~~Doc~~                                                               |
diff --git a/website/docs/api/scorer.md b/website/docs/api/scorer.md
index 8dbe3b276..ca3462aa9 100644
--- a/website/docs/api/scorer.md
+++ b/website/docs/api/scorer.md
@@ -270,3 +270,62 @@ Compute micro-PRF and per-entity PRF scores.
 | Name       | Description                                                                                                         |
 | ---------- | ------------------------------------------------------------------------------------------------------------------- |
 | `examples` | The `Example` objects holding both the predictions and the correct gold-standard annotations. ~~Iterable[Example]~~ |
+
+## score_coref_clusters {#score_coref_clusters tag="experimental"}
+
+Returns LEA ([Moosavi and Strube, 2016](https://aclanthology.org/P16-1060/)) PRF
+scores for coreference clusters.
+
+<Infobox title="Important note" variant="warning">
+
+Note this scoring function is not yet included in spaCy core - for details, see
+the [CoreferenceResolver](/api/coref) docs.
+
+</Infobox>
+
+> #### Example
+>
+> ```python
+> scores = score_coref_clusters(
+>     examples,
+>     span_cluster_prefix="coref_clusters",
+> )
+> print(scores["coref_f"])
+> ```
+
+| Name                  | Description                                                                                                         |
+| --------------------- | ------------------------------------------------------------------------------------------------------------------- |
+| `examples`            | The `Example` objects holding both the predictions and the correct gold-standard annotations. ~~Iterable[Example]~~ |
+| _keyword-only_        |                                                                                                                     |
+| `span_cluster_prefix` | The prefix used for spans representing coreference clusters. ~~str~~                                                |
+| **RETURNS**           | A dictionary containing the scores. ~~Dict[str, Optional[float]]~~                                                  |
+
+## score_span_predictions {#score_span_predictions tag="experimental"}
+
+Return accuracy for reconstructions of spans from single tokens. Only exactly
+correct predictions are counted as correct, there is no partial credit for near
+answers. Used by the [SpanResolver](/api/span-resolver).
+
+<Infobox title="Important note" variant="warning">
+
+Note this scoring function is not yet included in spaCy core - for details, see
+the [SpanResolver](/api/span-resolver) docs.
+
+</Infobox>
+
+> #### Example
+>
+> ```python
+> scores = score_span_predictions(
+>     examples,
+>     output_prefix="coref_clusters",
+> )
+> print(scores["span_coref_clusters_accuracy"])
+> ```
+
+| Name            | Description                                                                                                         |
+| --------------- | ------------------------------------------------------------------------------------------------------------------- |
+| `examples`      | The `Example` objects holding both the predictions and the correct gold-standard annotations. ~~Iterable[Example]~~ |
+| _keyword-only_  |                                                                                                                     |
+| `output_prefix` | The prefix used for spans representing the final predicted spans. ~~str~~                                           |
+| **RETURNS**     | A dictionary containing the scores. ~~Dict[str, Optional[float]]~~                                                  |
diff --git a/website/docs/api/span-resolver.md b/website/docs/api/span-resolver.md
new file mode 100644
index 000000000..3e992cd03
--- /dev/null
+++ b/website/docs/api/span-resolver.md
@@ -0,0 +1,356 @@
+---
+title: SpanResolver
+tag: class,experimental
+source: spacy-experimental/coref/span_resolver_component.py
+teaser: 'Pipeline component for resolving tokens into spans'
+api_base_class: /api/pipe
+api_string_name: span_resolver
+api_trainable: true
+---
+
+> #### Installation
+>
+> ```bash
+> $ pip install -U spacy-experimental
+> ```
+
+<Infobox title="Important note" variant="warning">
+
+This component not yet integrated into spaCy core, and is available via the
+extension package
+[`spacy-experimental`](https://github.com/explosion/spacy-experimental) starting
+in version 0.6.0. It exposes the component via
+[entry points](/usage/saving-loading/#entry-points), so if you have the package
+installed, using `factory = "experimental_span_resolver"` in your
+[training config](/usage/training#config) or
+`nlp.add_pipe("experimental_span_resolver")` will work out-of-the-box.
+
+</Infobox>
+
+A `SpanResolver` component takes in tokens (represented as `Span` objects of
+length 1) and resolves them into `Span` objects of arbitrary length. The initial
+use case is as a post-processing step on word-level
+[coreference resolution](/api/coref). The input and output keys used to store
+`Span` objects are configurable.
+
+## Assigned Attributes {#assigned-attributes}
+
+Predictions will be saved to `Doc.spans` as [`SpanGroup`s](/api/spangroup).
+
+Input token spans will be read in using an input prefix, by default
+`"coref_head_clusters"`, and output spans will be saved using an output prefix
+(default `"coref_clusters"`) plus a serial number starting from one. The
+prefixes are configurable.
+
+| Location                                          | Value                                                                     |
+| ------------------------------------------------- | ------------------------------------------------------------------------- |
+| `Doc.spans[output_prefix + "_" + cluster_number]` | One group of predicted spans. Cluster number starts from 1. ~~SpanGroup~~ |
+
+## Config and implementation {#config}
+
+The default config is defined by the pipeline component factory and describes
+how the component should be configured. You can override its settings via the
+`config` argument on [`nlp.add_pipe`](/api/language#add_pipe) or in your
+[`config.cfg` for training](/usage/training#config). See the
+[model architectures](/api/architectures#coref-architectures) documentation for
+details on the architectures and their arguments and hyperparameters.
+
+> #### Example
+>
+> ```python
+> from spacy_experimental.coref.span_resolver_component import DEFAULT_SPAN_RESOLVER_MODEL
+> from spacy_experimental.coref.coref_util import DEFAULT_CLUSTER_PREFIX, DEFAULT_CLUSTER_HEAD_PREFIX
+> config={
+>     "model": DEFAULT_SPAN_RESOLVER_MODEL,
+>     "input_prefix": DEFAULT_CLUSTER_HEAD_PREFIX,
+>     "output_prefix": DEFAULT_CLUSTER_PREFIX,
+> },
+> nlp.add_pipe("experimental_span_resolver", config=config)
+> ```
+
+| Setting         | Description                                                                                                                                            |
+| --------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------ |
+| `model`         | The [`Model`](https://thinc.ai/docs/api-model) powering the pipeline component. Defaults to [SpanResolver](/api/architectures#SpanResolver). ~~Model~~ |
+| `input_prefix`  | The prefix to use for input `SpanGroup`s. Defaults to `coref_head_clusters`. ~~str~~                                                                   |
+| `output_prefix` | The prefix for predicted `SpanGroup`s. Defaults to `coref_clusters`. ~~str~~                                                                           |
+
+## SpanResolver.\_\_init\_\_ {#init tag="method"}
+
+> #### Example
+>
+> ```python
+> # Construction via add_pipe with default model
+> span_resolver = nlp.add_pipe("experimental_span_resolver")
+>
+> # Construction via add_pipe with custom model
+> config = {"model": {"@architectures": "my_span_resolver.v1"}}
+> span_resolver = nlp.add_pipe("experimental_span_resolver", config=config)
+>
+> # Construction from class
+> from spacy_experimental.coref.span_resolver_component import SpanResolver
+> span_resolver = SpanResolver(nlp.vocab, model)
+> ```
+
+Create a new pipeline instance. In your application, you would normally use a
+shortcut for this and instantiate the component using its string name and
+[`nlp.add_pipe`](/api/language#add_pipe).
+
+| Name            | Description                                                                                         |
+| --------------- | --------------------------------------------------------------------------------------------------- |
+| `vocab`         | The shared vocabulary. ~~Vocab~~                                                                    |
+| `model`         | The [`Model`](https://thinc.ai/docs/api-model) powering the pipeline component. ~~Model~~           |
+| `name`          | String name of the component instance. Used to add entries to the `losses` during training. ~~str~~ |
+| _keyword-only_  |                                                                                                     |
+| `input_prefix`  | The prefix to use for input `SpanGroup`s. Defaults to `coref_head_clusters`. ~~str~~                |
+| `output_prefix` | The prefix for predicted `SpanGroup`s. Defaults to `coref_clusters`. ~~str~~                        |
+
+## SpanResolver.\_\_call\_\_ {#call tag="method"}
+
+Apply the pipe to one document. The document is modified in place and returned.
+This usually happens under the hood when the `nlp` object is called on a text
+and all pipeline components are applied to the `Doc` in order. Both
+[`__call__`](#call) and [`pipe`](#pipe) delegate to the [`predict`](#predict)
+and [`set_annotations`](#set_annotations) methods.
+
+> #### Example
+>
+> ```python
+> doc = nlp("This is a sentence.")
+> span_resolver = nlp.add_pipe("experimental_span_resolver")
+> # This usually happens under the hood
+> processed = span_resolver(doc)
+> ```
+
+| Name        | Description                      |
+| ----------- | -------------------------------- |
+| `doc`       | The document to process. ~~Doc~~ |
+| **RETURNS** | The processed document. ~~Doc~~  |
+
+## SpanResolver.pipe {#pipe tag="method"}
+
+Apply the pipe to a stream of documents. This usually happens under the hood
+when the `nlp` object is called on a text and all pipeline components are
+applied to the `Doc` in order. Both [`__call__`](/api/span-resolver#call) and
+[`pipe`](/api/span-resolver#pipe) delegate to the
+[`predict`](/api/span-resolver#predict) and
+[`set_annotations`](/api/span-resolver#set_annotations) methods.
+
+> #### Example
+>
+> ```python
+> span_resolver = nlp.add_pipe("experimental_span_resolver")
+> for doc in span_resolver.pipe(docs, batch_size=50):
+>     pass
+> ```
+
+| Name           | Description                                                   |
+| -------------- | ------------------------------------------------------------- |
+| `stream`       | A stream of documents. ~~Iterable[Doc]~~                      |
+| _keyword-only_ |                                                               |
+| `batch_size`   | The number of documents to buffer. Defaults to `128`. ~~int~~ |
+| **YIELDS**     | The processed documents in order. ~~Doc~~                     |
+
+## SpanResolver.initialize {#initialize tag="method"}
+
+Initialize the component for training. `get_examples` should be a function that
+returns an iterable of [`Example`](/api/example) objects. **At least one example
+should be supplied.** The data examples are used to **initialize the model** of
+the component and can either be the full training data or a representative
+sample. Initialization includes validating the network,
+[inferring missing shapes](https://thinc.ai/docs/usage-models#validation) and
+setting up the label scheme based on the data. This method is typically called
+by [`Language.initialize`](/api/language#initialize).
+
+> #### Example
+>
+> ```python
+> span_resolver = nlp.add_pipe("experimental_span_resolver")
+> span_resolver.initialize(lambda: examples, nlp=nlp)
+> ```
+
+| Name           | Description                                                                                                                                                                |
+| -------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `get_examples` | Function that returns gold-standard annotations in the form of [`Example`](/api/example) objects. Must contain at least one `Example`. ~~Callable[[], Iterable[Example]]~~ |
+| _keyword-only_ |                                                                                                                                                                            |
+| `nlp`          | The current `nlp` object. Defaults to `None`. ~~Optional[Language]~~                                                                                                       |
+
+## SpanResolver.predict {#predict tag="method"}
+
+Apply the component's model to a batch of [`Doc`](/api/doc) objects, without
+modifying them. Predictions are returned as a list of `MentionClusters`, one for
+each input `Doc`. A `MentionClusters` instance is just a list of lists of pairs
+of `int`s, where each item corresponds to an input `SpanGroup`, and the `int`s
+correspond to token indices.
+
+> #### Example
+>
+> ```python
+> span_resolver = nlp.add_pipe("experimental_span_resolver")
+> spans = span_resolver.predict([doc1, doc2])
+> ```
+
+| Name        | Description                                                   |
+| ----------- | ------------------------------------------------------------- |
+| `docs`      | The documents to predict. ~~Iterable[Doc]~~                   |
+| **RETURNS** | The predicted spans for the `Doc`s. ~~List[MentionClusters]~~ |
+
+## SpanResolver.set_annotations {#set_annotations tag="method"}
+
+Modify a batch of documents, saving predictions using the output prefix in
+`Doc.spans`.
+
+> #### Example
+>
+> ```python
+> span_resolver = nlp.add_pipe("experimental_span_resolver")
+> spans = span_resolver.predict([doc1, doc2])
+> span_resolver.set_annotations([doc1, doc2], spans)
+> ```
+
+| Name    | Description                                                   |
+| ------- | ------------------------------------------------------------- |
+| `docs`  | The documents to modify. ~~Iterable[Doc]~~                    |
+| `spans` | The predicted spans for the `docs`. ~~List[MentionClusters]~~ |
+
+## SpanResolver.update {#update tag="method"}
+
+Learn from a batch of [`Example`](/api/example) objects. Delegates to
+[`predict`](/api/span-resolver#predict).
+
+> #### Example
+>
+> ```python
+> span_resolver = nlp.add_pipe("experimental_span_resolver")
+> optimizer = nlp.initialize()
+> losses = span_resolver.update(examples, sgd=optimizer)
+> ```
+
+| Name           | Description                                                                                                              |
+| -------------- | ------------------------------------------------------------------------------------------------------------------------ |
+| `examples`     | A batch of [`Example`](/api/example) objects to learn from. ~~Iterable[Example]~~                                        |
+| _keyword-only_ |                                                                                                                          |
+| `drop`         | The dropout rate. ~~float~~                                                                                              |
+| `sgd`          | An optimizer. Will be created via [`create_optimizer`](#create_optimizer) if not set. ~~Optional[Optimizer]~~            |
+| `losses`       | Optional record of the loss during training. Updated using the component name as the key. ~~Optional[Dict[str, float]]~~ |
+| **RETURNS**    | The updated `losses` dictionary. ~~Dict[str, float]~~                                                                    |
+
+## SpanResolver.create_optimizer {#create_optimizer tag="method"}
+
+Create an optimizer for the pipeline component.
+
+> #### Example
+>
+> ```python
+> span_resolver = nlp.add_pipe("experimental_span_resolver")
+> optimizer = span_resolver.create_optimizer()
+> ```
+
+| Name        | Description                  |
+| ----------- | ---------------------------- |
+| **RETURNS** | The optimizer. ~~Optimizer~~ |
+
+## SpanResolver.use_params {#use_params tag="method, contextmanager"}
+
+Modify the pipe's model, to use the given parameter values. At the end of the
+context, the original parameters are restored.
+
+> #### Example
+>
+> ```python
+> span_resolver = nlp.add_pipe("experimental_span_resolver")
+> with span_resolver.use_params(optimizer.averages):
+>     span_resolver.to_disk("/best_model")
+> ```
+
+| Name     | Description                                        |
+| -------- | -------------------------------------------------- |
+| `params` | The parameter values to use in the model. ~~dict~~ |
+
+## SpanResolver.to_disk {#to_disk tag="method"}
+
+Serialize the pipe to disk.
+
+> #### Example
+>
+> ```python
+> span_resolver = nlp.add_pipe("experimental_span_resolver")
+> span_resolver.to_disk("/path/to/span_resolver")
+> ```
+
+| Name           | Description                                                                                                                                |
+| -------------- | ------------------------------------------------------------------------------------------------------------------------------------------ |
+| `path`         | A path to a directory, which will be created if it doesn't exist. Paths may be either strings or `Path`-like objects. ~~Union[str, Path]~~ |
+| _keyword-only_ |                                                                                                                                            |
+| `exclude`      | String names of [serialization fields](#serialization-fields) to exclude. ~~Iterable[str]~~                                                |
+
+## SpanResolver.from_disk {#from_disk tag="method"}
+
+Load the pipe from disk. Modifies the object in place and returns it.
+
+> #### Example
+>
+> ```python
+> span_resolver = nlp.add_pipe("experimental_span_resolver")
+> span_resolver.from_disk("/path/to/span_resolver")
+> ```
+
+| Name           | Description                                                                                     |
+| -------------- | ----------------------------------------------------------------------------------------------- |
+| `path`         | A path to a directory. Paths may be either strings or `Path`-like objects. ~~Union[str, Path]~~ |
+| _keyword-only_ |                                                                                                 |
+| `exclude`      | String names of [serialization fields](#serialization-fields) to exclude. ~~Iterable[str]~~     |
+| **RETURNS**    | The modified `SpanResolver` object. ~~SpanResolver~~                                            |
+
+## SpanResolver.to_bytes {#to_bytes tag="method"}
+
+> #### Example
+>
+> ```python
+> span_resolver = nlp.add_pipe("experimental_span_resolver")
+> span_resolver_bytes = span_resolver.to_bytes()
+> ```
+
+Serialize the pipe to a bytestring.
+
+| Name           | Description                                                                                 |
+| -------------- | ------------------------------------------------------------------------------------------- |
+| _keyword-only_ |                                                                                             |
+| `exclude`      | String names of [serialization fields](#serialization-fields) to exclude. ~~Iterable[str]~~ |
+| **RETURNS**    | The serialized form of the `SpanResolver` object. ~~bytes~~                                 |
+
+## SpanResolver.from_bytes {#from_bytes tag="method"}
+
+Load the pipe from a bytestring. Modifies the object in place and returns it.
+
+> #### Example
+>
+> ```python
+> span_resolver_bytes = span_resolver.to_bytes()
+> span_resolver = nlp.add_pipe("experimental_span_resolver")
+> span_resolver.from_bytes(span_resolver_bytes)
+> ```
+
+| Name           | Description                                                                                 |
+| -------------- | ------------------------------------------------------------------------------------------- |
+| `bytes_data`   | The data to load from. ~~bytes~~                                                            |
+| _keyword-only_ |                                                                                             |
+| `exclude`      | String names of [serialization fields](#serialization-fields) to exclude. ~~Iterable[str]~~ |
+| **RETURNS**    | The `SpanResolver` object. ~~SpanResolver~~                                                 |
+
+## Serialization fields {#serialization-fields}
+
+During serialization, spaCy will export several data fields used to restore
+different aspects of the object. If needed, you can exclude them from
+serialization by passing in the string names via the `exclude` argument.
+
+> #### Example
+>
+> ```python
+> data = span_resolver.to_disk("/path", exclude=["vocab"])
+> ```
+
+| Name    | Description                                                    |
+| ------- | -------------------------------------------------------------- |
+| `vocab` | The shared [`Vocab`](/api/vocab).                              |
+| `cfg`   | The config file. You usually don't want to exclude this.       |
+| `model` | The binary model data. You usually don't want to exclude this. |
diff --git a/website/meta/sidebars.json b/website/meta/sidebars.json
index 06fce7742..2d8745d77 100644
--- a/website/meta/sidebars.json
+++ b/website/meta/sidebars.json
@@ -94,6 +94,7 @@
                 "label": "Pipeline",
                 "items": [
                     { "text": "AttributeRuler", "url": "/api/attributeruler" },
+                    { "text": "CoreferenceResolver", "url": "/api/coref" },
                     { "text": "DependencyParser", "url": "/api/dependencyparser" },
                     { "text": "EditTreeLemmatizer", "url": "/api/edittreelemmatizer" },
                     { "text": "EntityLinker", "url": "/api/entitylinker" },
@@ -104,6 +105,7 @@
                     { "text": "SentenceRecognizer", "url": "/api/sentencerecognizer" },
                     { "text": "Sentencizer", "url": "/api/sentencizer" },
                     { "text": "SpanCategorizer", "url": "/api/spancategorizer" },
+                    { "text": "SpanResolver", "url": "/api/span-resolver" },
                     { "text": "SpanRuler", "url": "/api/spanruler" },
                     { "text": "Tagger", "url": "/api/tagger" },
                     { "text": "TextCategorizer", "url": "/api/textcategorizer" },

From 3e8bc1272f95c89e0aa9e5a19f51e286a7934ffa Mon Sep 17 00:00:00 2001
From: Jacobo Myerston <43222279+jmyerston@users.noreply.github.com>
Date: Tue, 27 Sep 2022 02:38:56 -0700
Subject: [PATCH 107/174] add punctuation to grc (#11426)

* add punctuation to grc

Add support for special editorial punctuation that is common in ancient Greek texts.  Ancient Greek texts, as found in digital and print form, have been largely edited by scholars. Restorations and improvements are normally marked with special characters that need to be handled properly by the tokenizer.

* add unit tests

* simplify regex

* move generic quotes to char classes

* rename unit test

* fix regex

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

Co-authored-by: svlandeg <svlandeg@github.com>
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
---
 spacy/lang/char_classes.py             |  2 +-
 spacy/lang/grc/__init__.py             |  4 +++
 spacy/lang/grc/punctuation.py          | 46 ++++++++++++++++++++++++++
 spacy/tests/lang/grc/test_tokenizer.py | 18 ++++++++++
 4 files changed, 69 insertions(+), 1 deletion(-)
 create mode 100644 spacy/lang/grc/punctuation.py
 create mode 100644 spacy/tests/lang/grc/test_tokenizer.py

diff --git a/spacy/lang/char_classes.py b/spacy/lang/char_classes.py
index 1d204c46c..37c58c85f 100644
--- a/spacy/lang/char_classes.py
+++ b/spacy/lang/char_classes.py
@@ -280,7 +280,7 @@ _currency = (
 _punct = (
     r"… …… , : ; \! \? ¿ ؟ ¡ \( \) \[ \] \{ \} < > _ # \* & 。 ？ ！ ， 、 ； ： ～ · । ، ۔ ؛ ٪"
 )
-_quotes = r'\' " ” “ ` ‘ ´ ’ ‚ , „ » « 「 」 『 』 （ ） 〔 〕 【 】 《 》 〈 〉'
+_quotes = r'\' " ” “ ` ‘ ´ ’ ‚ , „ » « 「 」 『 』 （ ） 〔 〕 【 】 《 》 〈 〉 〈 〉  ⟦ ⟧'
 _hyphens = "- – — -- --- —— ~"
 
 # Various symbols like dingbats, but also emoji
diff --git a/spacy/lang/grc/__init__.py b/spacy/lang/grc/__init__.py
index e83f0c5a5..019b3802e 100644
--- a/spacy/lang/grc/__init__.py
+++ b/spacy/lang/grc/__init__.py
@@ -1,11 +1,15 @@
 from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
 from .stop_words import STOP_WORDS
 from .lex_attrs import LEX_ATTRS
+from .punctuation import TOKENIZER_PREFIXES, TOKENIZER_SUFFIXES, TOKENIZER_INFIXES
 from ...language import Language, BaseDefaults
 
 
 class AncientGreekDefaults(BaseDefaults):
     tokenizer_exceptions = TOKENIZER_EXCEPTIONS
+    prefixes = TOKENIZER_PREFIXES
+    suffixes = TOKENIZER_SUFFIXES
+    infixes = TOKENIZER_INFIXES
     lex_attr_getters = LEX_ATTRS
     stop_words = STOP_WORDS
 
diff --git a/spacy/lang/grc/punctuation.py b/spacy/lang/grc/punctuation.py
new file mode 100644
index 000000000..8f3589e9a
--- /dev/null
+++ b/spacy/lang/grc/punctuation.py
@@ -0,0 +1,46 @@
+from ..char_classes import LIST_PUNCT, LIST_ELLIPSES, LIST_QUOTES, LIST_CURRENCY
+from ..char_classes import LIST_ICONS, ALPHA_LOWER, ALPHA_UPPER, ALPHA, HYPHENS
+from ..char_classes import CONCAT_QUOTES
+
+_prefixes = (
+    [
+        "†",
+        "⸏",
+    ]
+    + LIST_PUNCT
+    + LIST_ELLIPSES
+    + LIST_QUOTES
+    + LIST_CURRENCY
+    + LIST_ICONS
+)
+
+_suffixes = (
+    LIST_PUNCT
+    + LIST_ELLIPSES
+    + LIST_QUOTES
+    + LIST_ICONS
+    + [
+        "†",
+        "⸎",
+        r"(?<=[\u1F00-\u1FFF\u0370-\u03FF])[\-\.⸏]",
+    ]
+)
+
+_infixes = (
+    LIST_ELLIPSES
+    + LIST_ICONS
+    + [
+        r"(?<=[0-9])[+\-\*^](?=[0-9-])",
+        r"(?<=[{al}{q}])\.(?=[{au}{q}])".format(
+            al=ALPHA_LOWER, au=ALPHA_UPPER, q=CONCAT_QUOTES
+        ),
+        r"(?<=[{a}]),(?=[{a}])".format(a=ALPHA),
+        r"(?<=[{a}0-9])(?:{h})(?=[{a}])".format(a=ALPHA, h=HYPHENS),
+        r"(?<=[{a}0-9])[:<>=/](?=[{a}])".format(a=ALPHA),
+        r"(?<=[\u1F00-\u1FFF\u0370-\u03FF])—",
+    ]
+)
+
+TOKENIZER_PREFIXES = _prefixes
+TOKENIZER_SUFFIXES = _suffixes
+TOKENIZER_INFIXES = _infixes
diff --git a/spacy/tests/lang/grc/test_tokenizer.py b/spacy/tests/lang/grc/test_tokenizer.py
new file mode 100644
index 000000000..3df5b546b
--- /dev/null
+++ b/spacy/tests/lang/grc/test_tokenizer.py
@@ -0,0 +1,18 @@
+import pytest
+
+
+# fmt: off
+GRC_TOKEN_EXCEPTION_TESTS = [
+    ("τὸ 〈τῆς〉 φιλοσοφίας ἔργον ἔνιοί φασιν ἀπὸ ⟦βαρβάρων⟧ ἄρξαι.", ["τὸ", "〈", "τῆς", "〉", "φιλοσοφίας", "ἔργον", "ἔνιοί", "φασιν", "ἀπὸ", "⟦", "βαρβάρων", "⟧", "ἄρξαι", "."]),
+    ("τὴν δὲ τῶν Αἰγυπτίων φιλοσοφίαν εἶναι τοιαύτην περί τε †θεῶν† καὶ ὑπὲρ δικαιοσύνης.", ["τὴν", "δὲ", "τῶν", "Αἰγυπτίων", "φιλοσοφίαν", "εἶναι", "τοιαύτην", "περί", "τε", "†", "θεῶν", "†", "καὶ", "ὑπὲρ", "δικαιοσύνης", "."]),
+    ("⸏πόσις δ' Ἐρεχθεύς ἐστί μοι σεσωσμένος⸏", ["⸏", "πόσις", "δ'", "Ἐρεχθεύς", "ἐστί", "μοι", "σεσωσμένος", "⸏"]),
+    ("⸏ὔπνον ἴδωμεν⸎", ["⸏", "ὔπνον", "ἴδωμεν", "⸎"]),
+]
+# fmt: on
+
+
+@pytest.mark.parametrize("text,expected_tokens", GRC_TOKEN_EXCEPTION_TESTS)
+def test_grc_tokenizer(grc_tokenizer, text, expected_tokens):
+    tokens = grc_tokenizer(text)
+    token_list = [token.text for token in tokens if not token.is_space]
+    assert expected_tokens == token_list

From 9557b0fb01612f5b32823dfc52cae71af37f0bd8 Mon Sep 17 00:00:00 2001
From: Taniguchi Yasufumi <yasufumi.taniguchi@gmail.com>
Date: Tue, 27 Sep 2022 21:11:50 +0900
Subject: [PATCH 108/174] Add spacy-partial-tagger to spaCy Universe (#11538)

---
 website/meta/universe.json | 14 ++++++++++++++
 1 file changed, 14 insertions(+)

diff --git a/website/meta/universe.json b/website/meta/universe.json
index 9145855c6..9ec0d6c0e 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -3984,7 +3984,21 @@
             },
             "category": ["pipeline"],
             "tags": ["interpretation", "ja"]
+        },
+        {
+            "id": "spacy-partial-tagger",
+            "title": "spaCy - Partial Tagger",
+            "slogan": "Sequence Tagger for Partially Annotated Dataset in spaCy",
+            "description": "This is a library to build a CRF tagger with a partially annotated dataset in spaCy. You can build your own tagger only from dictionary.",
+            "github": "doccano/spacy-partial-tagger",
+            "pip": "spacy-partial-tagger",
+            "category": ["pipeline", "training"],
+            "author": "Yasufumi Taniguchi",
+            "author_links": {
+                "github": "yasufumy"
+            }
         }
+
     ],
 
     "categories": [

From aea16719be04d4d6ab889cd20fe0e323b2c7ffee Mon Sep 17 00:00:00 2001
From: Raphael Mitsch <r.mitsch@outlook.com>
Date: Tue, 27 Sep 2022 14:22:36 +0200
Subject: [PATCH 109/174] Simplify and clarify enable/disable behavior of
 spacy.load() (#11459)

* Change enable/disable behavior so that arguments take precedence over config options. Extend error message on conflict. Add warning message in case of overwriting config option with arguments.

* Fix tests in test_serialize_pipeline.py to reflect changes to handling of enable/disable.

* Fix type issue.

* Move comment.

* Move comment.

* Issue UserWarning instead of printing wasabi message. Adjust test.

* Added pytest.warns(UserWarning) for expected warning to fix tests.

* Update warning message.

* Move type handling out of fetch_pipes_status().

* Add global variable for default value. Use id() to determine whether used values are default value.

* Fix default value for disable.

* Rename DEFAULT_PIPE_STATUS to _DEFAULT_EMPTY_PIPES.
---
 spacy/__init__.py                             |  6 +-
 spacy/errors.py                               |  7 ++-
 spacy/language.py                             | 59 ++++++++++++-------
 spacy/tests/pipeline/test_pipe_methods.py     | 33 +++++++++--
 .../serialize/test_serialize_pipeline.py      |  7 ++-
 spacy/util.py                                 | 23 ++++----
 6 files changed, 92 insertions(+), 43 deletions(-)

diff --git a/spacy/__init__.py b/spacy/__init__.py
index d60f46b96..c3568bc5c 100644
--- a/spacy/__init__.py
+++ b/spacy/__init__.py
@@ -31,9 +31,9 @@ def load(
     name: Union[str, Path],
     *,
     vocab: Union[Vocab, bool] = True,
-    disable: Union[str, Iterable[str]] = util.SimpleFrozenList(),
-    enable: Union[str, Iterable[str]] = util.SimpleFrozenList(),
-    exclude: Union[str, Iterable[str]] = util.SimpleFrozenList(),
+    disable: Union[str, Iterable[str]] = util._DEFAULT_EMPTY_PIPES,
+    enable: Union[str, Iterable[str]] = util._DEFAULT_EMPTY_PIPES,
+    exclude: Union[str, Iterable[str]] = util._DEFAULT_EMPTY_PIPES,
     config: Union[Dict[str, Any], Config] = util.SimpleFrozenDict(),
 ) -> Language:
     """Load a spaCy model from an installed package or a local path.
diff --git a/spacy/errors.py b/spacy/errors.py
index f55b378e9..c035f684d 100644
--- a/spacy/errors.py
+++ b/spacy/errors.py
@@ -212,6 +212,8 @@ class Warnings(metaclass=ErrorsWithCodes):
     W121 = ("Attempting to trace non-existent method '{method}' in pipe '{pipe}'")
     W122 = ("Couldn't trace method '{method}' in pipe '{pipe}'. This can happen if the pipe class "
             "is a Cython extension type.")
+    W123 = ("Argument {arg} with value {arg_value} is used instead of {config_value} as specified in the config. Be "
+            "aware that this might affect other components in your pipeline.")
 
 
 class Errors(metaclass=ErrorsWithCodes):
@@ -937,8 +939,9 @@ class Errors(metaclass=ErrorsWithCodes):
     E1040 = ("Doc.from_json requires all tokens to have the same attributes. "
              "Some tokens do not contain annotation for: {partial_attrs}")
     E1041 = ("Expected a string, Doc, or bytes as input, but got: {type}")
-    E1042 = ("Function was called with `{arg1}`={arg1_values} and "
-             "`{arg2}`={arg2_values} but these arguments are conflicting.")
+    E1042 = ("`enable={enable}` and `disable={disable}` are inconsistent with each other.\nIf you only passed "
+             "one of `enable` or `disable`, the other argument is specified in your pipeline's configuration.\nIn that "
+             "case pass an empty list for the previously not specified argument to avoid this error.")
     E1043 = ("Expected None or a value in range [{range_start}, {range_end}] for entity linker threshold, but got "
              "{value}.")
 
diff --git a/spacy/language.py b/spacy/language.py
index 34a06e576..d391f15ab 100644
--- a/spacy/language.py
+++ b/spacy/language.py
@@ -1,4 +1,4 @@
-from typing import Iterator, Optional, Any, Dict, Callable, Iterable, Collection
+from typing import Iterator, Optional, Any, Dict, Callable, Iterable
 from typing import Union, Tuple, List, Set, Pattern, Sequence
 from typing import NoReturn, TYPE_CHECKING, TypeVar, cast, overload
 
@@ -10,6 +10,7 @@ from contextlib import contextmanager
 from copy import deepcopy
 from pathlib import Path
 import warnings
+
 from thinc.api import get_current_ops, Config, CupyOps, Optimizer
 import srsly
 import multiprocessing as mp
@@ -24,7 +25,7 @@ from .pipe_analysis import validate_attrs, analyze_pipes, print_pipe_analysis
 from .training import Example, validate_examples
 from .training.initialize import init_vocab, init_tok2vec
 from .scorer import Scorer
-from .util import registry, SimpleFrozenList, _pipe, raise_error
+from .util import registry, SimpleFrozenList, _pipe, raise_error, _DEFAULT_EMPTY_PIPES
 from .util import SimpleFrozenDict, combine_score_weights, CONFIG_SECTION_ORDER
 from .util import warn_if_jupyter_cupy
 from .lang.tokenizer_exceptions import URL_MATCH, BASE_EXCEPTIONS
@@ -1698,9 +1699,9 @@ class Language:
         config: Union[Dict[str, Any], Config] = {},
         *,
         vocab: Union[Vocab, bool] = True,
-        disable: Union[str, Iterable[str]] = SimpleFrozenList(),
-        enable: Union[str, Iterable[str]] = SimpleFrozenList(),
-        exclude: Union[str, Iterable[str]] = SimpleFrozenList(),
+        disable: Union[str, Iterable[str]] = _DEFAULT_EMPTY_PIPES,
+        enable: Union[str, Iterable[str]] = _DEFAULT_EMPTY_PIPES,
+        exclude: Union[str, Iterable[str]] = _DEFAULT_EMPTY_PIPES,
         meta: Dict[str, Any] = SimpleFrozenDict(),
         auto_fill: bool = True,
         validate: bool = True,
@@ -1727,12 +1728,6 @@ class Language:
 
         DOCS: https://spacy.io/api/language#from_config
         """
-        if isinstance(disable, str):
-            disable = [disable]
-        if isinstance(enable, str):
-            enable = [enable]
-        if isinstance(exclude, str):
-            exclude = [exclude]
         if auto_fill:
             config = Config(
                 cls.default_config, section_order=CONFIG_SECTION_ORDER
@@ -1877,9 +1872,38 @@ class Language:
             nlp.vocab.from_bytes(vocab_b)
 
         # Resolve disabled/enabled settings.
+        if isinstance(disable, str):
+            disable = [disable]
+        if isinstance(enable, str):
+            enable = [enable]
+        if isinstance(exclude, str):
+            exclude = [exclude]
+
+        def fetch_pipes_status(value: Iterable[str], key: str) -> Iterable[str]:
+            """Fetch value for `enable` or `disable` w.r.t. the specified config and passed arguments passed to
+            .load(). If both arguments and config specified values for this field, the passed arguments take precedence
+            and a warning is printed.
+            value (Iterable[str]): Passed value for `enable` or `disable`.
+            key (str): Key for field in config (either "enabled" or "disabled").
+            RETURN (Iterable[str]):
+            """
+            # We assume that no argument was passed if the value is the specified default value.
+            if id(value) == id(_DEFAULT_EMPTY_PIPES):
+                return config["nlp"].get(key, [])
+            else:
+                if len(config["nlp"].get(key, [])):
+                    warnings.warn(
+                        Warnings.W123.format(
+                            arg=key[:-1],
+                            arg_value=value,
+                            config_value=config["nlp"][key],
+                        )
+                    )
+                return value
+
         disabled_pipes = cls._resolve_component_status(
-            [*config["nlp"]["disabled"], *disable],
-            [*config["nlp"].get("enabled", []), *enable],
+            fetch_pipes_status(disable, "disabled"),
+            fetch_pipes_status(enable, "enabled"),
             config["nlp"]["pipeline"],
         )
         nlp._disabled = set(p for p in disabled_pipes if p not in exclude)
@@ -2064,14 +2088,7 @@ class Language:
                 pipe_name for pipe_name in pipe_names if pipe_name not in enable
             ]
             if disable and disable != to_disable:
-                raise ValueError(
-                    Errors.E1042.format(
-                        arg1="enable",
-                        arg2="disable",
-                        arg1_values=enable,
-                        arg2_values=disable,
-                    )
-                )
+                raise ValueError(Errors.E1042.format(enable=enable, disable=disable))
 
         return tuple(to_disable)
 
diff --git a/spacy/tests/pipeline/test_pipe_methods.py b/spacy/tests/pipeline/test_pipe_methods.py
index b946061f6..14a7a36e5 100644
--- a/spacy/tests/pipeline/test_pipe_methods.py
+++ b/spacy/tests/pipeline/test_pipe_methods.py
@@ -605,10 +605,35 @@ def test_update_with_annotates():
             assert results[component] == ""
 
 
-def test_load_disable_enable() -> None:
-    """
-    Tests spacy.load() with dis-/enabling components.
-    """
+@pytest.mark.issue(11443)
+def test_enable_disable_conflict_with_config():
+    """Test conflict between enable/disable w.r.t. `nlp.disabled` set in the config."""
+    nlp = English()
+    nlp.add_pipe("tagger")
+    nlp.add_pipe("senter")
+    nlp.add_pipe("sentencizer")
+
+    with make_tempdir() as tmp_dir:
+        nlp.to_disk(tmp_dir)
+        # Expected to fail, as config and arguments conflict.
+        with pytest.raises(ValueError):
+            spacy.load(
+                tmp_dir, enable=["tagger"], config={"nlp": {"disabled": ["senter"]}}
+            )
+        # Expected to succeed without warning due to the lack of a conflicting config option.
+        spacy.load(tmp_dir, enable=["tagger"])
+        # Expected to succeed with a warning, as disable=[] should override the config setting.
+        with pytest.warns(UserWarning):
+            spacy.load(
+                tmp_dir,
+                enable=["tagger"],
+                disable=[],
+                config={"nlp": {"disabled": ["senter"]}},
+            )
+
+
+def test_load_disable_enable():
+    """Tests spacy.load() with dis-/enabling components."""
 
     base_nlp = English()
     for pipe in ("sentencizer", "tagger", "parser"):
diff --git a/spacy/tests/serialize/test_serialize_pipeline.py b/spacy/tests/serialize/test_serialize_pipeline.py
index 9fcf18e2d..b948bb76c 100644
--- a/spacy/tests/serialize/test_serialize_pipeline.py
+++ b/spacy/tests/serialize/test_serialize_pipeline.py
@@ -404,10 +404,11 @@ def test_serialize_pipeline_disable_enable():
     assert nlp3.component_names == ["ner", "tagger"]
     with make_tempdir() as d:
         nlp3.to_disk(d)
-        nlp4 = spacy.load(d, disable=["ner"])
-    assert nlp4.pipe_names == []
+        with pytest.warns(UserWarning):
+            nlp4 = spacy.load(d, disable=["ner"])
+    assert nlp4.pipe_names == ["tagger"]
     assert nlp4.component_names == ["ner", "tagger"]
-    assert nlp4.disabled == ["ner", "tagger"]
+    assert nlp4.disabled == ["ner"]
     with make_tempdir() as d:
         nlp.to_disk(d)
         nlp5 = spacy.load(d, exclude=["tagger"])
diff --git a/spacy/util.py b/spacy/util.py
index 4e1a62d05..3034808ba 100644
--- a/spacy/util.py
+++ b/spacy/util.py
@@ -67,7 +67,6 @@ LEXEME_NORM_LANGS = ["cs", "da", "de", "el", "en", "id", "lb", "mk", "pt", "ru",
 CONFIG_SECTION_ORDER = ["paths", "variables", "system", "nlp", "components", "corpora", "training", "pretraining", "initialize"]
 # fmt: on
 
-
 logger = logging.getLogger("spacy")
 logger_stream_handler = logging.StreamHandler()
 logger_stream_handler.setFormatter(
@@ -394,13 +393,17 @@ def get_module_path(module: ModuleType) -> Path:
     return file_path.parent
 
 
+# Default value for passed enable/disable values.
+_DEFAULT_EMPTY_PIPES = SimpleFrozenList()
+
+
 def load_model(
     name: Union[str, Path],
     *,
     vocab: Union["Vocab", bool] = True,
-    disable: Union[str, Iterable[str]] = SimpleFrozenList(),
-    enable: Union[str, Iterable[str]] = SimpleFrozenList(),
-    exclude: Union[str, Iterable[str]] = SimpleFrozenList(),
+    disable: Union[str, Iterable[str]] = _DEFAULT_EMPTY_PIPES,
+    enable: Union[str, Iterable[str]] = _DEFAULT_EMPTY_PIPES,
+    exclude: Union[str, Iterable[str]] = _DEFAULT_EMPTY_PIPES,
     config: Union[Dict[str, Any], Config] = SimpleFrozenDict(),
 ) -> "Language":
     """Load a model from a package or data path.
@@ -470,9 +473,9 @@ def load_model_from_path(
     *,
     meta: Optional[Dict[str, Any]] = None,
     vocab: Union["Vocab", bool] = True,
-    disable: Union[str, Iterable[str]] = SimpleFrozenList(),
-    enable: Union[str, Iterable[str]] = SimpleFrozenList(),
-    exclude: Union[str, Iterable[str]] = SimpleFrozenList(),
+    disable: Union[str, Iterable[str]] = _DEFAULT_EMPTY_PIPES,
+    enable: Union[str, Iterable[str]] = _DEFAULT_EMPTY_PIPES,
+    exclude: Union[str, Iterable[str]] = _DEFAULT_EMPTY_PIPES,
     config: Union[Dict[str, Any], Config] = SimpleFrozenDict(),
 ) -> "Language":
     """Load a model from a data directory path. Creates Language class with
@@ -516,9 +519,9 @@ def load_model_from_config(
     *,
     meta: Dict[str, Any] = SimpleFrozenDict(),
     vocab: Union["Vocab", bool] = True,
-    disable: Union[str, Iterable[str]] = SimpleFrozenList(),
-    enable: Union[str, Iterable[str]] = SimpleFrozenList(),
-    exclude: Union[str, Iterable[str]] = SimpleFrozenList(),
+    disable: Union[str, Iterable[str]] = _DEFAULT_EMPTY_PIPES,
+    enable: Union[str, Iterable[str]] = _DEFAULT_EMPTY_PIPES,
+    exclude: Union[str, Iterable[str]] = _DEFAULT_EMPTY_PIPES,
     auto_fill: bool = False,
     validate: bool = True,
 ) -> "Language":

From e794d4ae39b65aed341fa588ed4d473644aec672 Mon Sep 17 00:00:00 2001
From: Peter Baumgartner <5107405+pmbaumgartner@users.noreply.github.com>
Date: Wed, 28 Sep 2022 11:16:05 -0400
Subject: [PATCH 110/174] `debug data` Spancat Table Improvements (#11504)

* update

* fix format function

* pull out _format_number

* format with black
---
 spacy/cli/_util.py      |  9 +++++++++
 spacy/cli/debug_data.py | 29 ++++++++++++++++++++++++-----
 2 files changed, 33 insertions(+), 5 deletions(-)

diff --git a/spacy/cli/_util.py b/spacy/cli/_util.py
index ae43b991b..897964a88 100644
--- a/spacy/cli/_util.py
+++ b/spacy/cli/_util.py
@@ -573,3 +573,12 @@ def setup_gpu(use_gpu: int, silent=None) -> None:
         local_msg.info("Using CPU")
         if gpu_is_available():
             local_msg.info("To switch to GPU 0, use the option: --gpu-id 0")
+
+
+def _format_number(number: Union[int, float], ndigits: int = 2) -> str:
+    """Formats a number (float or int) rounding to `ndigits`, without truncating trailing 0s,
+    as happens with `round(number, ndigits)`"""
+    if isinstance(number, float):
+        return f"{number:.{ndigits}f}"
+    else:
+        return str(number)
diff --git a/spacy/cli/debug_data.py b/spacy/cli/debug_data.py
index bd05471b1..963d5b926 100644
--- a/spacy/cli/debug_data.py
+++ b/spacy/cli/debug_data.py
@@ -9,7 +9,7 @@ import typer
 import math
 
 from ._util import app, Arg, Opt, show_validation_error, parse_config_overrides
-from ._util import import_code, debug_cli
+from ._util import import_code, debug_cli, _format_number
 from ..training import Example, remove_bilu_prefix
 from ..training.initialize import get_sourced_components
 from ..schemas import ConfigSchemaTraining
@@ -989,7 +989,8 @@ def _get_kl_divergence(p: Counter, q: Counter) -> float:
 def _format_span_row(span_data: List[Dict], labels: List[str]) -> List[Any]:
     """Compile into one list for easier reporting"""
     d = {
-        label: [label] + list(round(d[label], 2) for d in span_data) for label in labels
+        label: [label] + list(_format_number(d[label]) for d in span_data)
+        for label in labels
     }
     return list(d.values())
 
@@ -1004,6 +1005,10 @@ def _get_span_characteristics(
         label: _gmean(l)
         for label, l in compiled_gold["spans_length"][spans_key].items()
     }
+    spans_per_type = {
+        label: len(spans)
+        for label, spans in compiled_gold["spans_per_type"][spans_key].items()
+    }
     min_lengths = [min(l) for l in compiled_gold["spans_length"][spans_key].values()]
     max_lengths = [max(l) for l in compiled_gold["spans_length"][spans_key].values()]
 
@@ -1031,6 +1036,7 @@ def _get_span_characteristics(
     return {
         "sd": span_distinctiveness,
         "bd": sb_distinctiveness,
+        "spans_per_type": spans_per_type,
         "lengths": span_length,
         "min_length": min(min_lengths),
         "max_length": max(max_lengths),
@@ -1045,12 +1051,15 @@ def _get_span_characteristics(
 
 def _print_span_characteristics(span_characteristics: Dict[str, Any]):
     """Print all span characteristics into a table"""
-    headers = ("Span Type", "Length", "SD", "BD")
+    headers = ("Span Type", "Length", "SD", "BD", "N")
+    # Wasabi has this at 30 by default, but we might have some long labels
+    max_col = max(30, max(len(label) for label in span_characteristics["labels"]))
     # Prepare table data with all span characteristics
     table_data = [
         span_characteristics["lengths"],
         span_characteristics["sd"],
         span_characteristics["bd"],
+        span_characteristics["spans_per_type"],
     ]
     table = _format_span_row(
         span_data=table_data, labels=span_characteristics["labels"]
@@ -1061,8 +1070,18 @@ def _print_span_characteristics(span_characteristics: Dict[str, Any]):
         span_characteristics["avg_sd"],
         span_characteristics["avg_bd"],
     ]
-    footer = ["Wgt. Average"] + [str(round(f, 2)) for f in footer_data]
-    msg.table(table, footer=footer, header=headers, divider=True)
+
+    footer = (
+        ["Wgt. Average"] + ["{:.2f}".format(round(f, 2)) for f in footer_data] + ["-"]
+    )
+    msg.table(
+        table,
+        footer=footer,
+        header=headers,
+        divider=True,
+        aligns=["l"] + ["r"] * (len(footer_data) + 1),
+        max_col=max_col,
+    )
 
 
 def _get_spans_length_freq_dist(

From 6d7630c5d372cda53b88a18b10bb893ce478d294 Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Thu, 29 Sep 2022 10:44:06 +0200
Subject: [PATCH 111/174] Allow overriding spacy_version in spacy package meta
 (#11552)

---
 spacy/cli/package.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/spacy/cli/package.py b/spacy/cli/package.py
index b8c8397b6..324c5d1bb 100644
--- a/spacy/cli/package.py
+++ b/spacy/cli/package.py
@@ -299,8 +299,8 @@ def get_meta(
     }
     nlp = util.load_model_from_path(Path(model_path))
     meta.update(nlp.meta)
-    meta.update(existing_meta)
     meta["spacy_version"] = util.get_minor_version_range(about.__version__)
+    meta.update(existing_meta)
     meta["vectors"] = {
         "width": nlp.vocab.vectors_length,
         "vectors": len(nlp.vocab.vectors),

From ba63f57f81441d049da52c5d398e5b226019a1a6 Mon Sep 17 00:00:00 2001
From: Paul O'Leary McCann <polm@dampfkraft.com>
Date: Thu, 29 Sep 2022 18:50:29 +0900
Subject: [PATCH 112/174] Update docs to reflect Doc input to Language (#11555)

---
 website/docs/api/language.md | 10 ++++++++--
 1 file changed, 8 insertions(+), 2 deletions(-)

diff --git a/website/docs/api/language.md b/website/docs/api/language.md
index ed763e36a..767a7450a 100644
--- a/website/docs/api/language.md
+++ b/website/docs/api/language.md
@@ -164,6 +164,9 @@ examples, see the
 Apply the pipeline to some text. The text can span multiple sentences, and can
 contain arbitrary whitespace. Alignment into the original string is preserved.
 
+Instead of text, a `Doc` can be passed as input, in which case tokenization is
+skipped, but the rest of the pipeline is run.
+
 > #### Example
 >
 > ```python
@@ -173,7 +176,7 @@ contain arbitrary whitespace. Alignment into the original string is preserved.
 
 | Name            | Description                                                                                                                                    |
 | --------------- | ---------------------------------------------------------------------------------------------------------------------------------------------- |
-| `text`          | The text to be processed. ~~str~~                                                                                                              |
+| `text`          | The text to be processed, or a Doc. ~~Union[str, Doc]~~                                                                                        |
 | _keyword-only_  |                                                                                                                                                |
 | `disable`       | Names of pipeline components to [disable](/usage/processing-pipelines#disabling). ~~List[str]~~                                                |
 | `component_cfg` | Optional dictionary of keyword arguments for components, keyed by component names. Defaults to `None`. ~~Optional[Dict[str, Dict[str, Any]]]~~ |
@@ -184,6 +187,9 @@ contain arbitrary whitespace. Alignment into the original string is preserved.
 Process texts as a stream, and yield `Doc` objects in order. This is usually
 more efficient than processing texts one-by-one.
 
+Instead of text, a `Doc` object can be passed as input. In this case
+tokenization is skipped but the rest of the pipeline is run.
+
 > #### Example
 >
 > ```python
@@ -194,7 +200,7 @@ more efficient than processing texts one-by-one.
 
 | Name                                       | Description                                                                                                                                                         |
 | ------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `texts`                                    | A sequence of strings. ~~Iterable[str]~~                                                                                                                            |
+| `texts`                                    | A sequence of strings (or `Doc` objects). ~~Iterable[Union[str, Doc]]~~                                                                                             |
 | _keyword-only_                             |                                                                                                                                                                     |
 | `as_tuples`                                | If set to `True`, inputs should be a sequence of `(text, context)` tuples. Output will then be a sequence of `(doc, context)` tuples. Defaults to `False`. ~~bool~~ |
 | `batch_size`                               | The number of texts to buffer. ~~Optional[int]~~                                                                                                                    |

From bcda8bc1e720e999243d23ce620181fcad7e8e46 Mon Sep 17 00:00:00 2001
From: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Date: Thu, 29 Sep 2022 14:24:40 +0200
Subject: [PATCH 113/174] update mypy to latest version (#11546)

* update mypy and disable it for python 3.6

* ignoring mypy's type redefinition error
---
 .github/azure-steps.yml       | 2 +-
 requirements.txt              | 2 +-
 spacy/pipeline/entityruler.py | 5 ++---
 3 files changed, 4 insertions(+), 5 deletions(-)

diff --git a/.github/azure-steps.yml b/.github/azure-steps.yml
index c7722391f..9d57219ca 100644
--- a/.github/azure-steps.yml
+++ b/.github/azure-steps.yml
@@ -27,7 +27,7 @@ steps:
 
   - script: python -m mypy spacy
     displayName: 'Run mypy'
-    condition: ne(variables['python_version'], '3.10')
+    condition: ne(variables['python_version'], '3.6')
 
   - task: DeleteFiles@1
     inputs:
diff --git a/requirements.txt b/requirements.txt
index e45fde787..446560c06 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -30,7 +30,7 @@ pytest-timeout>=1.3.0,<2.0.0
 mock>=2.0.0,<3.0.0
 flake8>=3.8.0,<3.10.0
 hypothesis>=3.27.0,<7.0.0
-mypy>=0.910,<0.970; platform_machine!='aarch64'
+mypy>=0.980,<0.990; platform_machine != "aarch64" and python_version >= "3.7"
 types-dataclasses>=0.1.3; python_version < "3.7"
 types-mock>=0.1.1
 types-setuptools>=57.0.0
diff --git a/spacy/pipeline/entityruler.py b/spacy/pipeline/entityruler.py
index 3cb1ca676..8154a077d 100644
--- a/spacy/pipeline/entityruler.py
+++ b/spacy/pipeline/entityruler.py
@@ -1,6 +1,5 @@
-import warnings
 from typing import Optional, Union, List, Dict, Tuple, Iterable, Any, Callable, Sequence
-from typing import cast
+import warnings
 from collections import defaultdict
 from pathlib import Path
 import srsly
@@ -317,7 +316,7 @@ class EntityRuler(Pipe):
                     phrase_pattern["id"] = ent_id
                 phrase_patterns.append(phrase_pattern)
             for entry in token_patterns + phrase_patterns:  # type: ignore[operator]
-                label = entry["label"]
+                label = entry["label"]  # type: ignore
                 if "id" in entry:
                     ent_label = label
                     label = self._create_label(label, entry["id"])

From ff9002b726cfdae083a9a0206e1ef615f19a6088 Mon Sep 17 00:00:00 2001
From: Gabriele Picco <piccogabriele@gmail.com>
Date: Thu, 29 Sep 2022 16:34:44 +0100
Subject: [PATCH 114/174] Add Zshot Spacy plugin (#11557)

* Add Zshot Spacy plugin

Add Zshot (Zero and Few shot named entity & relationships recognition) Spacy plugin

* Update website/meta/universe.json

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

* Update website/meta/universe.json

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
---
 website/meta/universe.json | 57 ++++++++++++++++++++++++++++++++++++++
 1 file changed, 57 insertions(+)

diff --git a/website/meta/universe.json b/website/meta/universe.json
index 9ec0d6c0e..a6a1a0fc7 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -1,5 +1,62 @@
 {
     "resources": [
+        {
+            "id": "Zshot",
+            "title": "Zshot",
+            "slogan": "Zero and Few shot named entity & relationships recognition",
+            "github": "ibm/zshot",
+            "pip": "zshot",
+            "code_example": [
+                "import spacy",
+                "from zshot import PipelineConfig, displacy",
+                "from zshot.linker import LinkerRegen",
+                "from zshot.mentions_extractor import MentionsExtractorSpacy",
+                "from zshot.utils.data_models import Entity",
+                "",
+                "nlp = spacy.load('en_core_web_sm')",
+                "# zero shot definition of entities",
+                "nlp_config = PipelineConfig(",
+                "    mentions_extractor=MentionsExtractorSpacy(),",
+                "    linker=LinkerRegen(),",
+                "    entities=[",
+                "        Entity(name='Paris',",
+                "               description='Paris is located in northern central France, in a north-bending arc of the river Seine'),",
+                "        Entity(name='IBM',",
+                "               description='International Business Machines Corporation (IBM) is an American multinational technology corporation headquartered in Armonk, New York'),",
+                "        Entity(name='New York', description='New York is a city in U.S. state'),",
+                "        Entity(name='Florida', description='southeasternmost U.S. state'),",
+                "        Entity(name='American',",
+                "              description='American, something of, from, or related to the United States of America, commonly known as the United States or America'),",
+                "        Entity(name='Chemical formula',",
+                "               description='In chemistry, a chemical formula is a way of presenting information about the chemical proportions of atoms that constitute a particular chemical compound or molecul'),",
+                "        Entity(name='Acetamide',",
+                "               description='Acetamide (systematic name: ethanamide) is an organic compound with the formula CH3CONH2. It is the simplest amide derived from acetic acid. It finds some use as a plasticizer and as an industrial solvent.'),",
+                "        Entity(name='Armonk',",
+                "               description='Armonk is a hamlet and census-designated place (CDP) in the town of North Castle, located in Westchester County, New York, United States.'),",
+                "        Entity(name='Acetic Acid',",
+                "               description='Acetic acid, systematically named ethanoic acid, is an acidic, colourless liquid and organic compound with the chemical formula CH3COOH'),",
+                "        Entity(name='Industrial solvent',",
+                "               description='Acetamide (systematic name: ethanamide) is an organic compound with the formula CH3CONH2. It is the simplest amide derived from acetic acid. It finds some use as a plasticizer and as an industrial solvent.'),",
+                "    ]",
+                ")",
+                "nlp.add_pipe('zshot', config=nlp_config, last=True)",
+                "",
+                "text = 'International Business Machines Corporation (IBM) is an American multinational technology corporation' \\",
+                "        ' headquartered in Armonk, New York, with operations in over 171 countries.'",
+                "",
+                "doc = nlp(text)",
+                "displacy.serve(doc, style='ent')"
+            ],
+            "thumb": "https://ibm.github.io/zshot/img/graph.png",
+            "url": "https://ibm.github.io/zshot/",
+            "author": "IBM Research",
+            "author_links": {
+                "github": "ibm",
+                "twitter": "IBMResearch",
+                "website": "https://research.ibm.com/labs/ireland/"
+            },
+            "category": ["scientific", "models", "research"]
+        },
         {
             "id": "concepcy",
             "title": "concepCy",

From 087cc74c6abdd43e04e4313cdcf292edf6187f4b Mon Sep 17 00:00:00 2001
From: Paul O'Leary McCann <polm@dampfkraft.com>
Date: Mon, 3 Oct 2022 18:53:21 +0900
Subject: [PATCH 115/174] Remove mention of 1.7 from issue template (#11570)

It's rare to have anyone using v1 anymore, so this message is no longer
helpful.
---
 .github/ISSUE_TEMPLATE/01_bugs.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/ISSUE_TEMPLATE/01_bugs.md b/.github/ISSUE_TEMPLATE/01_bugs.md
index 255a5241e..f0d0ba912 100644
--- a/.github/ISSUE_TEMPLATE/01_bugs.md
+++ b/.github/ISSUE_TEMPLATE/01_bugs.md
@@ -10,7 +10,7 @@ about: Use this template if you came across a bug or unexpected behaviour differ
 <!-- Include a code example or the steps that led to the problem. Please try to be as specific as possible. -->
 
 ## Your Environment
-<!-- Include details of your environment. If you're using spaCy 1.7+, you can also type `python -m spacy info --markdown` and copy-paste the result here.-->
+<!-- Include details of your environment. You can also type `python -m spacy info --markdown` and copy-paste the result here.-->
 * Operating System:
 * Python Version Used:
 * spaCy Version Used:

From 70e21dfcad28b044903ba33b2b8831d925151b76 Mon Sep 17 00:00:00 2001
From: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Date: Mon, 3 Oct 2022 13:04:03 +0200
Subject: [PATCH 116/174] PR to test importlib-metadata (#11569)

* empty commit

* restrict importlib-metadata to lower than 5.0.0

* restrict importlib-metadata also for validate CI step

* set fixed version for CI

* try flake8 5.0.4 in CI validation step

* from importlib-metadata from requirements again
---
 azure-pipelines.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/azure-pipelines.yml b/azure-pipelines.yml
index f475b7fdd..2f5201614 100644
--- a/azure-pipelines.yml
+++ b/azure-pipelines.yml
@@ -31,7 +31,7 @@ jobs:
         inputs:
           versionSpec: "3.7"
       - script: |
-          pip install flake8==3.9.2
+          pip install flake8==5.0.4
           python -m flake8 spacy --count --select=E901,E999,F821,F822,F823,W605 --show-source --statistics
         displayName: "flake8"
 

From b187076a2dd0f034c1a8918c9b332711688b5dc2 Mon Sep 17 00:00:00 2001
From: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Date: Mon, 3 Oct 2022 17:01:04 +0200
Subject: [PATCH 117/174] fix docs (#11573)

---
 website/docs/api/kb_in_memory.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/website/docs/api/kb_in_memory.md b/website/docs/api/kb_in_memory.md
index c9ce624f0..9e3279e6a 100644
--- a/website/docs/api/kb_in_memory.md
+++ b/website/docs/api/kb_in_memory.md
@@ -21,9 +21,9 @@ Create the knowledge base.
 > #### Example
 >
 > ```python
-> from spacy.kb import KnowledgeBase
+> from spacy.kb import InMemoryLookupKB
 > vocab = nlp.vocab
-> kb = KnowledgeBase(vocab=vocab, entity_vector_length=64)
+> kb = InMemoryLookupKB(vocab=vocab, entity_vector_length=64)
 > ```
 
 | Name                   | Description                                      |

From 8cd77dd54cfc89c2f67ca2412490ef9b49a98518 Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Tue, 4 Oct 2022 11:23:04 +0200
Subject: [PATCH 118/174] Sync flake8 version across requirements (#11580)

---
 .pre-commit-config.yaml | 2 +-
 requirements.txt        | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index b959262e3..df59697b1 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -6,7 +6,7 @@ repos:
       language_version: python3.7
       additional_dependencies: ['click==8.0.4']
 -   repo: https://gitlab.com/pycqa/flake8
-    rev: 3.9.2
+    rev: 5.0.4
     hooks:
     - id: flake8
       args:
diff --git a/requirements.txt b/requirements.txt
index 446560c06..14847ff21 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -28,7 +28,7 @@ cython>=0.25,<3.0
 pytest>=5.2.0,!=7.1.0
 pytest-timeout>=1.3.0,<2.0.0
 mock>=2.0.0,<3.0.0
-flake8>=3.8.0,<3.10.0
+flake8>=3.8.0,<6.0.0
 hypothesis>=3.27.0,<7.0.0
 mypy>=0.980,<0.990; platform_machine != "aarch64" and python_version >= "3.7"
 types-dataclasses>=0.1.3; python_version < "3.7"

From ef74f8f5e447dec10ab69d2a7e94f0e09165db75 Mon Sep 17 00:00:00 2001
From: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Date: Tue, 11 Oct 2022 14:15:22 +0200
Subject: [PATCH 119/174] Fix mypy error in edittree lemmatizer (#11612)

* cleanup imports

* try limiting Thinc to previous release

* remove Model specification

* fix code and revert Thinc constraint
---
 spacy/pipeline/edit_tree_lemmatizer.py | 5 ++---
 1 file changed, 2 insertions(+), 3 deletions(-)

diff --git a/spacy/pipeline/edit_tree_lemmatizer.py b/spacy/pipeline/edit_tree_lemmatizer.py
index b7d615f6d..7f6367c75 100644
--- a/spacy/pipeline/edit_tree_lemmatizer.py
+++ b/spacy/pipeline/edit_tree_lemmatizer.py
@@ -1,7 +1,6 @@
 from typing import cast, Any, Callable, Dict, Iterable, List, Optional
-from typing import Sequence, Tuple, Union
+from typing import Tuple
 from collections import Counter
-from copy import deepcopy
 from itertools import islice
 import numpy as np
 
@@ -150,7 +149,7 @@ class EditTreeLemmatizer(TrainablePipe):
             # Handle cases where there are no tokens in any docs.
             n_labels = len(self.cfg["labels"])
             guesses: List[Ints2d] = [
-                self.model.ops.alloc((0, n_labels), dtype="i") for doc in docs
+                self.model.ops.alloc2i(0, n_labels, dtype="i") for _ in docs
             ]
             assert len(guesses) == n_docs
             return guesses

From 29649589fc889a58c8b631d569d4ae378a10aa2b Mon Sep 17 00:00:00 2001
From: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Date: Tue, 11 Oct 2022 15:25:05 +0200
Subject: [PATCH 120/174] remove dtype (#11615)

---
 spacy/pipeline/edit_tree_lemmatizer.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/spacy/pipeline/edit_tree_lemmatizer.py b/spacy/pipeline/edit_tree_lemmatizer.py
index 7f6367c75..76b0e0bc9 100644
--- a/spacy/pipeline/edit_tree_lemmatizer.py
+++ b/spacy/pipeline/edit_tree_lemmatizer.py
@@ -149,7 +149,7 @@ class EditTreeLemmatizer(TrainablePipe):
             # Handle cases where there are no tokens in any docs.
             n_labels = len(self.cfg["labels"])
             guesses: List[Ints2d] = [
-                self.model.ops.alloc2i(0, n_labels, dtype="i") for _ in docs
+                self.model.ops.alloc2i(0, n_labels) for _ in docs
             ]
             assert len(guesses) == n_docs
             return guesses

From 2e52479eec987367117d27fb4f049df2efb2518d Mon Sep 17 00:00:00 2001
From: Paul O'Leary McCann <polm@dampfkraft.com>
Date: Tue, 11 Oct 2022 23:45:05 +0900
Subject: [PATCH 121/174] Fix example code for spacy-wordnet (#11593)

* Fix example code for spacy-wordnet

It looks like in the most recent version, 0.1.0, it's no longer possible
to pass the lang parameter to the component separately. Doing so will
raise an error.

* Apply suggestions from code review

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Cleanup

* More cleanup

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
---
 website/meta/universe.json | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/website/meta/universe.json b/website/meta/universe.json
index a6a1a0fc7..637e9d6ce 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -2460,20 +2460,20 @@
                 "import spacy",
                 "from spacy_wordnet.wordnet_annotator import WordnetAnnotator ",
                 "",
-                "# Load an spacy model (supported models are \"es\" and \"en\") ",
-                "nlp = spacy.load('en')",
-                "# Spacy 3.x",
-                "nlp.add_pipe(\"spacy_wordnet\", after='tagger', config={'lang': nlp.lang})",
-                "# Spacy 2.x",
+                "# Load a spaCy model (supported languages are \"es\" and \"en\") ",
+                "nlp = spacy.load('en_core_web_sm')",
+                "# spaCy 3.x",
+                "nlp.add_pipe(\"spacy_wordnet\", after='tagger')",
+                "# spaCy 2.x",
                 "# nlp.add_pipe(WordnetAnnotator(nlp.lang), after='tagger')",
                 "token = nlp('prices')[0]",
                 "",
-                "# wordnet object link spacy token with nltk wordnet interface by giving acces to",
+                "# WordNet object links spaCy token with NLTK WordNet interface by giving access to",
                 "# synsets and lemmas ",
                 "token._.wordnet.synsets()",
                 "token._.wordnet.lemmas()",
                 "",
-                "# And automatically tags with wordnet domains",
+                "# And automatically add info about WordNet domains",
                 "token._.wordnet.wordnet_domains()"
             ],
             "author": "recognai",

From fe06e037bcd733708401bce082863994b1fc48bd Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Wed, 12 Oct 2022 12:18:39 +0200
Subject: [PATCH 122/174] Fix init for pymorphy2_lookup lemmatizer mode
 (#11631)

---
 spacy/lang/ru/lemmatizer.py            |  2 +-
 spacy/lang/uk/lemmatizer.py            |  2 +-
 spacy/tests/conftest.py                | 17 +++++++++++++++++
 spacy/tests/lang/ru/test_lemmatizer.py | 14 ++++++++++++++
 spacy/tests/lang/uk/test_lemmatizer.py |  8 ++++++++
 5 files changed, 41 insertions(+), 2 deletions(-)

diff --git a/spacy/lang/ru/lemmatizer.py b/spacy/lang/ru/lemmatizer.py
index 85180b1e4..5bf685d44 100644
--- a/spacy/lang/ru/lemmatizer.py
+++ b/spacy/lang/ru/lemmatizer.py
@@ -23,7 +23,7 @@ class RussianLemmatizer(Lemmatizer):
         overwrite: bool = False,
         scorer: Optional[Callable] = lemmatizer_score,
     ) -> None:
-        if mode == "pymorphy2":
+        if mode in {"pymorphy2", "pymorphy2_lookup"}:
             try:
                 from pymorphy2 import MorphAnalyzer
             except ImportError:
diff --git a/spacy/lang/uk/lemmatizer.py b/spacy/lang/uk/lemmatizer.py
index a8bc56057..d4f8cc9e5 100644
--- a/spacy/lang/uk/lemmatizer.py
+++ b/spacy/lang/uk/lemmatizer.py
@@ -18,7 +18,7 @@ class UkrainianLemmatizer(RussianLemmatizer):
         overwrite: bool = False,
         scorer: Optional[Callable] = lemmatizer_score,
     ) -> None:
-        if mode == "pymorphy2":
+        if mode in {"pymorphy2", "pymorphy2_lookup"}:
             try:
                 from pymorphy2 import MorphAnalyzer
             except ImportError:
diff --git a/spacy/tests/conftest.py b/spacy/tests/conftest.py
index 742bfcc6a..394ef00d3 100644
--- a/spacy/tests/conftest.py
+++ b/spacy/tests/conftest.py
@@ -343,6 +343,14 @@ def ru_lemmatizer():
     return get_lang_class("ru")().add_pipe("lemmatizer")
 
 
+@pytest.fixture
+def ru_lookup_lemmatizer():
+    pytest.importorskip("pymorphy2")
+    return get_lang_class("ru")().add_pipe(
+        "lemmatizer", config={"mode": "pymorphy2_lookup"}
+    )
+
+
 @pytest.fixture(scope="session")
 def sa_tokenizer():
     return get_lang_class("sa")().tokenizer
@@ -422,6 +430,15 @@ def uk_lemmatizer():
     return get_lang_class("uk")().add_pipe("lemmatizer")
 
 
+@pytest.fixture
+def uk_lookup_lemmatizer():
+    pytest.importorskip("pymorphy2")
+    pytest.importorskip("pymorphy2_dicts_uk")
+    return get_lang_class("uk")().add_pipe(
+        "lemmatizer", config={"mode": "pymorphy2_lookup"}
+    )
+
+
 @pytest.fixture(scope="session")
 def ur_tokenizer():
     return get_lang_class("ur")().tokenizer
diff --git a/spacy/tests/lang/ru/test_lemmatizer.py b/spacy/tests/lang/ru/test_lemmatizer.py
index 9ca7f441b..e82fd4f8c 100644
--- a/spacy/tests/lang/ru/test_lemmatizer.py
+++ b/spacy/tests/lang/ru/test_lemmatizer.py
@@ -78,3 +78,17 @@ def test_ru_lemmatizer_punct(ru_lemmatizer):
     assert ru_lemmatizer.pymorphy2_lemmatize(doc[0]) == ['"']
     doc = Doc(ru_lemmatizer.vocab, words=["»"], pos=["PUNCT"])
     assert ru_lemmatizer.pymorphy2_lemmatize(doc[0]) == ['"']
+
+
+def test_ru_doc_lookup_lemmatization(ru_lookup_lemmatizer):
+    words = ["мама", "мыла", "раму"]
+    pos = ["NOUN", "VERB", "NOUN"]
+    morphs = [
+        "Animacy=Anim|Case=Nom|Gender=Fem|Number=Sing",
+        "Aspect=Imp|Gender=Fem|Mood=Ind|Number=Sing|Tense=Past|VerbForm=Fin|Voice=Act",
+        "Animacy=Anim|Case=Acc|Gender=Fem|Number=Sing",
+    ]
+    doc = Doc(ru_lookup_lemmatizer.vocab, words=words, pos=pos, morphs=morphs)
+    doc = ru_lookup_lemmatizer(doc)
+    lemmas = [token.lemma_ for token in doc]
+    assert lemmas == ["мама", "мыла", "раму"]
diff --git a/spacy/tests/lang/uk/test_lemmatizer.py b/spacy/tests/lang/uk/test_lemmatizer.py
index 57dd4198a..788744aa1 100644
--- a/spacy/tests/lang/uk/test_lemmatizer.py
+++ b/spacy/tests/lang/uk/test_lemmatizer.py
@@ -9,3 +9,11 @@ def test_uk_lemmatizer(uk_lemmatizer):
     """Check that the default uk lemmatizer runs."""
     doc = Doc(uk_lemmatizer.vocab, words=["a", "b", "c"])
     uk_lemmatizer(doc)
+    assert [token.lemma for token in doc]
+
+
+def test_uk_lookup_lemmatizer(uk_lookup_lemmatizer):
+    """Check that the lookup uk lemmatizer runs."""
+    doc = Doc(uk_lookup_lemmatizer.vocab, words=["a", "b", "c"])
+    uk_lookup_lemmatizer(doc)
+    assert [token.lemma for token in doc]

From 4d869fcc111151bcefa08ee1a2b7b49dc5ecd677 Mon Sep 17 00:00:00 2001
From: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Date: Wed, 12 Oct 2022 15:17:40 +0200
Subject: [PATCH 123/174] Small fixes to docstrings (#11610)

* add missing scorer arg to docstring

* fix class names in textcat_multilabel

* add missing scorer to docstrings
---
 spacy/pipeline/spancat.py            | 3 +++
 spacy/pipeline/textcat_multilabel.py | 6 ++++--
 2 files changed, 7 insertions(+), 2 deletions(-)

diff --git a/spacy/pipeline/spancat.py b/spacy/pipeline/spancat.py
index 1b7a9eecb..ca9f1dab0 100644
--- a/spacy/pipeline/spancat.py
+++ b/spacy/pipeline/spancat.py
@@ -133,6 +133,9 @@ def make_spancat(
     spans_key (str): Key of the doc.spans dict to save the spans under. During
         initialization and training, the component will look for spans on the
         reference document under the same key.
+    scorer (Optional[Callable]): The scoring method. Defaults to
+        Scorer.score_spans for the Doc.spans[spans_key] with overlapping
+        spans allowed.
     threshold (float): Minimum probability to consider a prediction positive.
         Spans with a positive prediction will be saved on the Doc. Defaults to
         0.5.
diff --git a/spacy/pipeline/textcat_multilabel.py b/spacy/pipeline/textcat_multilabel.py
index e33a885f8..119ae3310 100644
--- a/spacy/pipeline/textcat_multilabel.py
+++ b/spacy/pipeline/textcat_multilabel.py
@@ -96,8 +96,8 @@ def make_multilabel_textcat(
     model: Model[List[Doc], List[Floats2d]],
     threshold: float,
     scorer: Optional[Callable],
-) -> "TextCategorizer":
-    """Create a TextCategorizer component. The text categorizer predicts categories
+) -> "MultiLabel_TextCategorizer":
+    """Create a MultiLabel_TextCategorizer component. The text categorizer predicts categories
     over a whole document. It can learn one or more labels, and the labels are considered
     to be non-mutually exclusive, which means that there can be zero or more labels
     per doc).
@@ -105,6 +105,7 @@ def make_multilabel_textcat(
     model (Model[List[Doc], List[Floats2d]]): A model instance that predicts
         scores for each category.
     threshold (float): Cutoff to consider a prediction "positive".
+    scorer (Optional[Callable]): The scoring method.
     """
     return MultiLabel_TextCategorizer(
         nlp.vocab, model, name, threshold=threshold, scorer=scorer
@@ -147,6 +148,7 @@ class MultiLabel_TextCategorizer(TextCategorizer):
         name (str): The component instance name, used to add entries to the
             losses during training.
         threshold (float): Cutoff to consider a prediction "positive".
+        scorer (Optional[Callable]): The scoring method.
 
         DOCS: https://spacy.io/api/textcategorizer#init
         """

From 6b5a3e72198aa9735587b0712e3eb2c24234b463 Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Fri, 14 Oct 2022 08:16:49 +0200
Subject: [PATCH 124/174] Extend to pydantic v1.10 (#11635)

* Update types in `spacy.schemas` for updated pydantic+mypy
---
 requirements.txt |  2 +-
 setup.cfg        |  2 +-
 spacy/schemas.py | 18 +++++++++---------
 3 files changed, 11 insertions(+), 11 deletions(-)

diff --git a/requirements.txt b/requirements.txt
index 14847ff21..9d6bbb2c4 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -15,7 +15,7 @@ pathy>=0.3.5
 numpy>=1.15.0
 requests>=2.13.0,<3.0.0
 tqdm>=4.38.0,<5.0.0
-pydantic>=1.7.4,!=1.8,!=1.8.1,<1.10.0
+pydantic>=1.7.4,!=1.8,!=1.8.1,<1.11.0
 jinja2
 langcodes>=3.2.0,<4.0.0
 # Official Python utilities
diff --git a/setup.cfg b/setup.cfg
index 2dc5e7042..c2653feba 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -56,7 +56,7 @@ install_requires =
     tqdm>=4.38.0,<5.0.0
     numpy>=1.15.0
     requests>=2.13.0,<3.0.0
-    pydantic>=1.7.4,!=1.8,!=1.8.1,<1.10.0
+    pydantic>=1.7.4,!=1.8,!=1.8.1,<1.11.0
     jinja2
     # Official Python utilities
     setuptools
diff --git a/spacy/schemas.py b/spacy/schemas.py
index 048082134..ab71b2016 100644
--- a/spacy/schemas.py
+++ b/spacy/schemas.py
@@ -181,12 +181,12 @@ class TokenPatternNumber(BaseModel):
     IS_SUBSET: Optional[List[StrictInt]] = Field(None, alias="is_subset")
     IS_SUPERSET: Optional[List[StrictInt]] = Field(None, alias="is_superset")
     INTERSECTS: Optional[List[StrictInt]] = Field(None, alias="intersects")
-    EQ: Union[StrictInt, StrictFloat] = Field(None, alias="==")
-    NEQ: Union[StrictInt, StrictFloat] = Field(None, alias="!=")
-    GEQ: Union[StrictInt, StrictFloat] = Field(None, alias=">=")
-    LEQ: Union[StrictInt, StrictFloat] = Field(None, alias="<=")
-    GT: Union[StrictInt, StrictFloat] = Field(None, alias=">")
-    LT: Union[StrictInt, StrictFloat] = Field(None, alias="<")
+    EQ: Optional[Union[StrictInt, StrictFloat]] = Field(None, alias="==")
+    NEQ: Optional[Union[StrictInt, StrictFloat]] = Field(None, alias="!=")
+    GEQ: Optional[Union[StrictInt, StrictFloat]] = Field(None, alias=">=")
+    LEQ: Optional[Union[StrictInt, StrictFloat]] = Field(None, alias="<=")
+    GT: Optional[Union[StrictInt, StrictFloat]] = Field(None, alias=">")
+    LT: Optional[Union[StrictInt, StrictFloat]] = Field(None, alias="<")
 
     class Config:
         extra = "forbid"
@@ -430,7 +430,7 @@ class ProjectConfigAssetURL(BaseModel):
     # fmt: off
     dest: StrictStr = Field(..., title="Destination of downloaded asset")
     url: Optional[StrictStr] = Field(None, title="URL of asset")
-    checksum: str = Field(None, title="MD5 hash of file", regex=r"([a-fA-F\d]{32})")
+    checksum: Optional[str] = Field(None, title="MD5 hash of file", regex=r"([a-fA-F\d]{32})")
     description: StrictStr = Field("", title="Description of asset")
     # fmt: on
 
@@ -438,7 +438,7 @@ class ProjectConfigAssetURL(BaseModel):
 class ProjectConfigAssetGit(BaseModel):
     # fmt: off
     git: ProjectConfigAssetGitItem = Field(..., title="Git repo information")
-    checksum: str = Field(None, title="MD5 hash of file", regex=r"([a-fA-F\d]{32})")
+    checksum: Optional[str] = Field(None, title="MD5 hash of file", regex=r"([a-fA-F\d]{32})")
     description: Optional[StrictStr] = Field(None, title="Description of asset")
     # fmt: on
 
@@ -508,7 +508,7 @@ class DocJSONSchema(BaseModel):
         None, title="Indices of sentences' start and end indices"
     )
     text: StrictStr = Field(..., title="Document text")
-    spans: Dict[StrictStr, List[Dict[StrictStr, Union[StrictStr, StrictInt]]]] = Field(
+    spans: Optional[Dict[StrictStr, List[Dict[StrictStr, Union[StrictStr, StrictInt]]]]] = Field(
         None, title="Span information - end/start indices, label, KB ID"
     )
     tokens: List[Dict[StrictStr, Union[StrictStr, StrictInt]]] = Field(

From ceb62352bfcad49b3ad63e3e65ef12dabab645b3 Mon Sep 17 00:00:00 2001
From: "github-actions[bot]"
 <41898282+github-actions[bot]@users.noreply.github.com>
Date: Fri, 14 Oct 2022 18:04:55 +0900
Subject: [PATCH 125/174] Auto-format code with black (#11649)

Co-authored-by: explosion-bot <explosion-bot@users.noreply.github.com>
---
 spacy/pipeline/edit_tree_lemmatizer.py | 4 +---
 spacy/schemas.py                       | 6 +++---
 2 files changed, 4 insertions(+), 6 deletions(-)

diff --git a/spacy/pipeline/edit_tree_lemmatizer.py b/spacy/pipeline/edit_tree_lemmatizer.py
index 76b0e0bc9..12f9b73a3 100644
--- a/spacy/pipeline/edit_tree_lemmatizer.py
+++ b/spacy/pipeline/edit_tree_lemmatizer.py
@@ -148,9 +148,7 @@ class EditTreeLemmatizer(TrainablePipe):
         if not any(len(doc) for doc in docs):
             # Handle cases where there are no tokens in any docs.
             n_labels = len(self.cfg["labels"])
-            guesses: List[Ints2d] = [
-                self.model.ops.alloc2i(0, n_labels) for _ in docs
-            ]
+            guesses: List[Ints2d] = [self.model.ops.alloc2i(0, n_labels) for _ in docs]
             assert len(guesses) == n_docs
             return guesses
         scores = self.model.predict(docs)
diff --git a/spacy/schemas.py b/spacy/schemas.py
index ab71b2016..a67d96d9d 100644
--- a/spacy/schemas.py
+++ b/spacy/schemas.py
@@ -508,9 +508,9 @@ class DocJSONSchema(BaseModel):
         None, title="Indices of sentences' start and end indices"
     )
     text: StrictStr = Field(..., title="Document text")
-    spans: Optional[Dict[StrictStr, List[Dict[StrictStr, Union[StrictStr, StrictInt]]]]] = Field(
-        None, title="Span information - end/start indices, label, KB ID"
-    )
+    spans: Optional[
+        Dict[StrictStr, List[Dict[StrictStr, Union[StrictStr, StrictInt]]]]
+    ] = Field(None, title="Span information - end/start indices, label, KB ID")
     tokens: List[Dict[StrictStr, Union[StrictStr, StrictInt]]] = Field(
         ..., title="Token information - ID, start, annotations"
     )

From 2ce6aadda2d455cf2f2a1aef494b2bafe3e07119 Mon Sep 17 00:00:00 2001
From: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Date: Mon, 17 Oct 2022 12:10:03 +0200
Subject: [PATCH 126/174] update default configs to recent versions (#11618)

---
 spacy/pipeline/spancat.py            | 6 +++---
 spacy/pipeline/textcat_multilabel.py | 4 ++--
 2 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/spacy/pipeline/spancat.py b/spacy/pipeline/spancat.py
index 1b7a9eecb..5ede622c2 100644
--- a/spacy/pipeline/spancat.py
+++ b/spacy/pipeline/spancat.py
@@ -26,17 +26,17 @@ scorer = {"@layers": "spacy.LinearLogistic.v1"}
 hidden_size = 128
 
 [model.tok2vec]
-@architectures = "spacy.Tok2Vec.v1"
+@architectures = "spacy.Tok2Vec.v2"
 
 [model.tok2vec.embed]
-@architectures = "spacy.MultiHashEmbed.v1"
+@architectures = "spacy.MultiHashEmbed.v2"
 width = 96
 rows = [5000, 2000, 1000, 1000]
 attrs = ["ORTH", "PREFIX", "SUFFIX", "SHAPE"]
 include_static_vectors = false
 
 [model.tok2vec.encode]
-@architectures = "spacy.MaxoutWindowEncoder.v1"
+@architectures = "spacy.MaxoutWindowEncoder.v2"
 width = ${model.tok2vec.embed.width}
 window_size = 1
 maxout_pieces = 3
diff --git a/spacy/pipeline/textcat_multilabel.py b/spacy/pipeline/textcat_multilabel.py
index e33a885f8..10aef46aa 100644
--- a/spacy/pipeline/textcat_multilabel.py
+++ b/spacy/pipeline/textcat_multilabel.py
@@ -19,7 +19,7 @@ multi_label_default_config = """
 @architectures = "spacy.TextCatEnsemble.v2"
 
 [model.tok2vec]
-@architectures = "spacy.Tok2Vec.v1"
+@architectures = "spacy.Tok2Vec.v2"
 
 [model.tok2vec.embed]
 @architectures = "spacy.MultiHashEmbed.v2"
@@ -29,7 +29,7 @@ attrs = ["ORTH", "LOWER", "PREFIX", "SUFFIX", "SHAPE", "ID"]
 include_static_vectors = false
 
 [model.tok2vec.encode]
-@architectures = "spacy.MaxoutWindowEncoder.v1"
+@architectures = "spacy.MaxoutWindowEncoder.v2"
 width = ${model.tok2vec.embed.width}
 window_size = 1
 maxout_pieces = 3

From 858565a5671de61334443d6a2348164bc39216e1 Mon Sep 17 00:00:00 2001
From: Paul O'Leary McCann <polm@dampfkraft.com>
Date: Tue, 18 Oct 2022 15:11:39 +0900
Subject: [PATCH 127/174] Fix issues with DVC commands (#11592)

* Fix flag handling in dvc

Prior to this commit, if a flag (--verbose or --quiet) was passed to
DVC, it would be added to the end of the generated dvc command line.
This would result in the command being interpreted as part of the actual
command to run, rather than an argument to dvc. This would result in
command lines like:

    spacy project run preprocess --verbose

That would fail with an error that there's no such directory as
`--verbose`.

This change puts the flags at the front of the dvc command so that they
are interpreted correctly. It removes the `run_dvc_commands` function,
which had been reduced to just a for loop and wasn't used elsewhere.

A separate problem is that there's no way to specify the quiet behaviour
to dvc from the command line, though it's unclear if that's a bug.

* Add dvc quiet flag to docs

* Handle case in DVC where no commands are appropriate

If only have commands with no deps or outputs (admittedly unlikely), you
get a weird error about the dvc file not existing. This gives explicit
output instead.

* Add support for quiet flag

* Fix command execution

Commands are strings now because they're joined further up.
---
 spacy/cli/project/dvc.py | 57 +++++++++++++++++++++-------------------
 website/docs/api/cli.md  |  3 ++-
 2 files changed, 32 insertions(+), 28 deletions(-)

diff --git a/spacy/cli/project/dvc.py b/spacy/cli/project/dvc.py
index 83dc5efbf..a15353855 100644
--- a/spacy/cli/project/dvc.py
+++ b/spacy/cli/project/dvc.py
@@ -25,6 +25,7 @@ def project_update_dvc_cli(
     project_dir: Path = Arg(Path.cwd(), help="Location of project directory. Defaults to current working directory.", exists=True, file_okay=False),
     workflow: Optional[str] = Arg(None, help=f"Name of workflow defined in {PROJECT_FILE}. Defaults to first workflow if not set."),
     verbose: bool = Opt(False, "--verbose", "-V", help="Print more info"),
+    quiet: bool = Opt(False, "--quiet", "-q", help="Print less info"),
     force: bool = Opt(False, "--force", "-F", help="Force update DVC config"),
     # fmt: on
 ):
@@ -36,7 +37,7 @@ def project_update_dvc_cli(
 
     DOCS: https://spacy.io/api/cli#project-dvc
     """
-    project_update_dvc(project_dir, workflow, verbose=verbose, force=force)
+    project_update_dvc(project_dir, workflow, verbose=verbose, quiet=quiet, force=force)
 
 
 def project_update_dvc(
@@ -44,6 +45,7 @@ def project_update_dvc(
     workflow: Optional[str] = None,
     *,
     verbose: bool = False,
+    quiet: bool = False,
     force: bool = False,
 ) -> None:
     """Update the auto-generated Data Version Control (DVC) config file. A DVC
@@ -54,11 +56,12 @@ def project_update_dvc(
     workflow (Optional[str]): Optional name of workflow defined in project.yml.
         If not set, the first workflow will be used.
     verbose (bool): Print more info.
+    quiet (bool): Print less info.
     force (bool): Force update DVC config.
     """
     config = load_project_config(project_dir)
     updated = update_dvc_config(
-        project_dir, config, workflow, verbose=verbose, force=force
+        project_dir, config, workflow, verbose=verbose, quiet=quiet, force=force
     )
     help_msg = "To execute the workflow with DVC, run: dvc repro"
     if updated:
@@ -72,7 +75,7 @@ def update_dvc_config(
     config: Dict[str, Any],
     workflow: Optional[str] = None,
     verbose: bool = False,
-    silent: bool = False,
+    quiet: bool = False,
     force: bool = False,
 ) -> bool:
     """Re-run the DVC commands in dry mode and update dvc.yaml file in the
@@ -83,7 +86,7 @@ def update_dvc_config(
     path (Path): The path to the project directory.
     config (Dict[str, Any]): The loaded project.yml.
     verbose (bool): Whether to print additional info (via DVC).
-    silent (bool): Don't output anything (via DVC).
+    quiet (bool): Don't output anything (via DVC).
     force (bool): Force update, even if hashes match.
     RETURNS (bool): Whether the DVC config file was updated.
     """
@@ -105,6 +108,14 @@ def update_dvc_config(
         dvc_config_path.unlink()
     dvc_commands = []
     config_commands = {cmd["name"]: cmd for cmd in config.get("commands", [])}
+
+    # some flags that apply to every command
+    flags = []
+    if verbose:
+        flags.append("--verbose")
+    if quiet:
+        flags.append("--quiet")
+
     for name in workflows[workflow]:
         command = config_commands[name]
         deps = command.get("deps", [])
@@ -118,14 +129,26 @@ def update_dvc_config(
         deps_cmd = [c for cl in [["-d", p] for p in deps] for c in cl]
         outputs_cmd = [c for cl in [["-o", p] for p in outputs] for c in cl]
         outputs_nc_cmd = [c for cl in [["-O", p] for p in outputs_no_cache] for c in cl]
-        dvc_cmd = ["run", "-n", name, "-w", str(path), "--no-exec"]
+
+        dvc_cmd = ["run", *flags, "-n", name, "-w", str(path), "--no-exec"]
         if command.get("no_skip"):
             dvc_cmd.append("--always-changed")
         full_cmd = [*dvc_cmd, *deps_cmd, *outputs_cmd, *outputs_nc_cmd, *project_cmd]
         dvc_commands.append(join_command(full_cmd))
+
+    if not dvc_commands:
+        # If we don't check for this, then there will be an error when reading the
+        # config, since DVC wouldn't create it.
+        msg.fail(
+            "No usable commands for DVC found. This can happen if none of your "
+            "commands have dependencies or outputs.",
+            exits=1,
+        )
+
     with working_dir(path):
-        dvc_flags = {"--verbose": verbose, "--quiet": silent}
-        run_dvc_commands(dvc_commands, flags=dvc_flags)
+        for c in dvc_commands:
+            dvc_command = "dvc " + c
+            run_command(dvc_command)
     with dvc_config_path.open("r+", encoding="utf8") as f:
         content = f.read()
         f.seek(0, 0)
@@ -133,26 +156,6 @@ def update_dvc_config(
     return True
 
 
-def run_dvc_commands(
-    commands: Iterable[str] = SimpleFrozenList(), flags: Dict[str, bool] = {}
-) -> None:
-    """Run a sequence of DVC commands in a subprocess, in order.
-
-    commands (List[str]): The string commands without the leading "dvc".
-    flags (Dict[str, bool]): Conditional flags to be added to command. Makes it
-        easier to pass flags like --quiet that depend on a variable or
-        command-line setting while avoiding lots of nested conditionals.
-    """
-    for c in commands:
-        command = split_command(c)
-        dvc_command = ["dvc", *command]
-        # Add the flags if they are set to True
-        for flag, is_active in flags.items():
-            if is_active:
-                dvc_command.append(flag)
-        run_command(dvc_command)
-
-
 def check_workflows(workflows: List[str], workflow: Optional[str] = None) -> None:
     """Validate workflows provided in project.yml and check that a given
     workflow can be used to generate a DVC config.
diff --git a/website/docs/api/cli.md b/website/docs/api/cli.md
index e5cd3089b..fc2c46022 100644
--- a/website/docs/api/cli.md
+++ b/website/docs/api/cli.md
@@ -1482,7 +1482,7 @@ You'll also need to add the assets you want to track with
 </Infobox>
 
 ```cli
-$ python -m spacy project dvc [project_dir] [workflow] [--force] [--verbose]
+$ python -m spacy project dvc [project_dir] [workflow] [--force] [--verbose] [--quiet]
 ```
 
 > #### Example
@@ -1499,6 +1499,7 @@ $ python -m spacy project dvc [project_dir] [workflow] [--force] [--verbose]
 | `workflow`        | Name of workflow defined in `project.yml`. Defaults to first workflow if not set. ~~Optional[str] \(option)~~ |
 | `--force`, `-F`   | Force-updating config file. ~~bool (flag)~~                                                                   |
 | `--verbose`, `-V` | Print more output generated by DVC. ~~bool (flag)~~                                                           |
+| `--quiet`, `-q`   | Print no output generated by DVC. ~~bool (flag)~~                                                             |
 | `--help`, `-h`    | Show help message and available arguments. ~~bool (flag)~~                                                    |
 | **CREATES**       | A `dvc.yaml` file in the project directory, based on the steps defined in the given workflow.                 |
 

From a1eacaa8db055322d4a066a08b730243a2f5b969 Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Tue, 18 Oct 2022 14:36:06 +0200
Subject: [PATCH 128/174] Add python 3.11.0rc2 to CI (#11667)

---
 .github/azure-steps.yml | 1 +
 azure-pipelines.yml     | 9 +++++++++
 2 files changed, 10 insertions(+)

diff --git a/.github/azure-steps.yml b/.github/azure-steps.yml
index 9d57219ca..cc0247b3a 100644
--- a/.github/azure-steps.yml
+++ b/.github/azure-steps.yml
@@ -10,6 +10,7 @@ steps:
     inputs:
       versionSpec: ${{ parameters.python_version }}
       architecture: ${{ parameters.architecture }}
+      allowUnstable: true
 
   - bash: |
       echo "##vso[task.setvariable variable=python_version]${{ parameters.python_version }}"
diff --git a/azure-pipelines.yml b/azure-pipelines.yml
index 2f5201614..357cce835 100644
--- a/azure-pipelines.yml
+++ b/azure-pipelines.yml
@@ -85,6 +85,15 @@ jobs:
         Python310Mac:
           imageName: "macos-latest"
           python.version: "3.10"
+        Python311Linux:
+          imageName: 'ubuntu-latest'
+          python.version: '3.11.0-rc.2'
+        Python311Windows:
+          imageName: 'windows-latest'
+          python.version: '3.11.0-rc.2'
+        Python311Mac:
+          imageName: 'macos-latest'
+          python.version: '3.11.0-rc.2'
       maxParallel: 4
     pool:
       vmImage: $(imageName)

From d66ccb8eb08cd515904045de84351546065fb3ed Mon Sep 17 00:00:00 2001
From: Edward <43848523+thomashacker@users.noreply.github.com>
Date: Wed, 19 Oct 2022 15:52:47 +0200
Subject: [PATCH 129/174] Fix multiple entries per custom extension in doc json
 (#11551)

* Fix multiple extensions and character offset

* Rename token_start/end to start/end

* Refactor Doc.from_json based on review

* Iterate over user_data items

* Only add non-empty underscore entries

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
---
 spacy/schemas.py                            |  4 +-
 spacy/tests/doc/test_json_doc_conversion.py | 25 +++++++----
 spacy/tokens/doc.pyx                        | 48 ++++++++++-----------
 3 files changed, 42 insertions(+), 35 deletions(-)

diff --git a/spacy/schemas.py b/spacy/schemas.py
index a67d96d9d..c824d76b9 100644
--- a/spacy/schemas.py
+++ b/spacy/schemas.py
@@ -519,9 +519,9 @@ class DocJSONSchema(BaseModel):
         title="Any custom data stored in the document's _ attribute",
         alias="_",
     )
-    underscore_token: Optional[Dict[StrictStr, Dict[StrictStr, Any]]] = Field(
+    underscore_token: Optional[Dict[StrictStr, List[Dict[StrictStr, Any]]]] = Field(
         None, title="Any custom data stored in the token's _ attribute"
     )
-    underscore_span: Optional[Dict[StrictStr, Dict[StrictStr, Any]]] = Field(
+    underscore_span: Optional[Dict[StrictStr, List[Dict[StrictStr, Any]]]] = Field(
         None, title="Any custom data stored in the span's _ attribute"
     )
diff --git a/spacy/tests/doc/test_json_doc_conversion.py b/spacy/tests/doc/test_json_doc_conversion.py
index 0d7c061c9..19698cfb2 100644
--- a/spacy/tests/doc/test_json_doc_conversion.py
+++ b/spacy/tests/doc/test_json_doc_conversion.py
@@ -128,7 +128,9 @@ def test_doc_to_json_with_token_span_attributes(doc):
     doc._.json_test1 = "hello world"
     doc._.json_test2 = [1, 2, 3]
     doc[0:1]._.span_test = "span_attribute"
+    doc[0:2]._.span_test = "span_attribute_2"
     doc[0]._.token_test = 117
+    doc[1]._.token_test = 118
     doc.spans["span_group"] = [doc[0:1]]
     json_doc = doc.to_json(
         underscore=["json_test1", "json_test2", "token_test", "span_test"]
@@ -139,8 +141,10 @@ def test_doc_to_json_with_token_span_attributes(doc):
     assert json_doc["_"]["json_test2"] == [1, 2, 3]
     assert "underscore_token" in json_doc
     assert "underscore_span" in json_doc
-    assert json_doc["underscore_token"]["token_test"]["value"] == 117
-    assert json_doc["underscore_span"]["span_test"]["value"] == "span_attribute"
+    assert json_doc["underscore_token"]["token_test"][0]["value"] == 117
+    assert json_doc["underscore_token"]["token_test"][1]["value"] == 118
+    assert json_doc["underscore_span"]["span_test"][0]["value"] == "span_attribute"
+    assert json_doc["underscore_span"]["span_test"][1]["value"] == "span_attribute_2"
     assert len(schemas.validate(schemas.DocJSONSchema, json_doc)) == 0
     assert srsly.json_loads(srsly.json_dumps(json_doc)) == json_doc
 
@@ -161,8 +165,8 @@ def test_doc_to_json_with_custom_user_data(doc):
     assert json_doc["_"]["json_test"] == "hello world"
     assert "underscore_token" in json_doc
     assert "underscore_span" in json_doc
-    assert json_doc["underscore_token"]["token_test"]["value"] == 117
-    assert json_doc["underscore_span"]["span_test"]["value"] == "span_attribute"
+    assert json_doc["underscore_token"]["token_test"][0]["value"] == 117
+    assert json_doc["underscore_span"]["span_test"][0]["value"] == "span_attribute"
     assert len(schemas.validate(schemas.DocJSONSchema, json_doc)) == 0
     assert srsly.json_loads(srsly.json_dumps(json_doc)) == json_doc
 
@@ -181,8 +185,8 @@ def test_doc_to_json_with_token_span_same_identifier(doc):
     assert json_doc["_"]["my_ext"] == "hello world"
     assert "underscore_token" in json_doc
     assert "underscore_span" in json_doc
-    assert json_doc["underscore_token"]["my_ext"]["value"] == 117
-    assert json_doc["underscore_span"]["my_ext"]["value"] == "span_attribute"
+    assert json_doc["underscore_token"]["my_ext"][0]["value"] == 117
+    assert json_doc["underscore_span"]["my_ext"][0]["value"] == "span_attribute"
     assert len(schemas.validate(schemas.DocJSONSchema, json_doc)) == 0
     assert srsly.json_loads(srsly.json_dumps(json_doc)) == json_doc
 
@@ -195,10 +199,9 @@ def test_doc_to_json_with_token_attributes_missing(doc):
     doc[0]._.token_test = 117
     json_doc = doc.to_json(underscore=["span_test"])
 
-    assert "underscore_token" in json_doc
     assert "underscore_span" in json_doc
-    assert json_doc["underscore_span"]["span_test"]["value"] == "span_attribute"
-    assert "token_test" not in json_doc["underscore_token"]
+    assert json_doc["underscore_span"]["span_test"][0]["value"] == "span_attribute"
+    assert "underscore_token" not in json_doc
     assert len(schemas.validate(schemas.DocJSONSchema, json_doc)) == 0
 
 
@@ -283,7 +286,9 @@ def test_json_to_doc_with_token_span_attributes(doc):
     doc._.json_test1 = "hello world"
     doc._.json_test2 = [1, 2, 3]
     doc[0:1]._.span_test = "span_attribute"
+    doc[0:2]._.span_test = "span_attribute_2"
     doc[0]._.token_test = 117
+    doc[1]._.token_test = 118
 
     json_doc = doc.to_json(
         underscore=["json_test1", "json_test2", "token_test", "span_test"]
@@ -295,7 +300,9 @@ def test_json_to_doc_with_token_span_attributes(doc):
     assert new_doc._.json_test1 == "hello world"
     assert new_doc._.json_test2 == [1, 2, 3]
     assert new_doc[0]._.token_test == 117
+    assert new_doc[1]._.token_test == 118
     assert new_doc[0:1]._.span_test == "span_attribute"
+    assert new_doc[0:2]._.span_test == "span_attribute_2"
     assert new_doc.user_data == doc.user_data
     assert new_doc.to_bytes(exclude=["user_data"]) == doc.to_bytes(
         exclude=["user_data"]
diff --git a/spacy/tokens/doc.pyx b/spacy/tokens/doc.pyx
index d7d2fd8e6..295f91c28 100644
--- a/spacy/tokens/doc.pyx
+++ b/spacy/tokens/doc.pyx
@@ -1608,24 +1608,20 @@ cdef class Doc:
                 Doc.set_extension(attr)
             self._.set(attr, doc_json["_"][attr])
 
-        if doc_json.get("underscore_token", {}):
-            for token_attr in doc_json["underscore_token"]:
-                token_start = doc_json["underscore_token"][token_attr]["token_start"]
-                value = doc_json["underscore_token"][token_attr]["value"]
-
-                if not Token.has_extension(token_attr):
-                    Token.set_extension(token_attr)
-                self[token_start]._.set(token_attr, value)
+        for token_attr in doc_json.get("underscore_token", {}):
+            if not Token.has_extension(token_attr):
+                Token.set_extension(token_attr)
+            for token_data in doc_json["underscore_token"][token_attr]:
+                start = token_by_char(self.c, self.length, token_data["start"])
+                value = token_data["value"]
+                self[start]._.set(token_attr, value)
                 
-        if doc_json.get("underscore_span", {}):
-            for span_attr in doc_json["underscore_span"]:
-                token_start = doc_json["underscore_span"][span_attr]["token_start"]
-                token_end = doc_json["underscore_span"][span_attr]["token_end"]
-                value = doc_json["underscore_span"][span_attr]["value"]
-
-                if not Span.has_extension(span_attr):
-                    Span.set_extension(span_attr)
-                self[token_start:token_end]._.set(span_attr, value)
+        for span_attr in doc_json.get("underscore_span", {}):
+            if not Span.has_extension(span_attr):
+                Span.set_extension(span_attr)
+            for span_data in doc_json["underscore_span"][span_attr]:
+                value = span_data["value"]
+                self.char_span(span_data["start"], span_data["end"])._.set(span_attr, value)
         return self
 
     def to_json(self, underscore=None):
@@ -1673,30 +1669,34 @@ cdef class Doc:
         if underscore:
             user_keys = set()
             if self.user_data:
-                data["_"] = {}
-                data["underscore_token"] = {}
-                data["underscore_span"] = {}
-                for data_key in self.user_data:
+                for data_key, value in self.user_data.copy().items():
                     if type(data_key) == tuple and len(data_key) >= 4 and data_key[0] == "._.":
                         attr = data_key[1]
                         start = data_key[2]
                         end = data_key[3]
                         if attr in underscore:
                             user_keys.add(attr)
-                            value = self.user_data[data_key]
                             if not srsly.is_json_serializable(value):
                                 raise ValueError(Errors.E107.format(attr=attr, value=repr(value)))
                             # Check if doc attribute
                             if start is None:
+                                if "_" not in data:
+                                    data["_"] = {}
                                 data["_"][attr] = value
                             # Check if token attribute
                             elif end is None:
+                                if "underscore_token" not in data:
+                                    data["underscore_token"] = {}
                                 if attr not in data["underscore_token"]:
-                                    data["underscore_token"][attr] = {"token_start": start, "value": value}
+                                    data["underscore_token"][attr] = []
+                                data["underscore_token"][attr].append({"start": start, "value": value})
                             # Else span attribute
                             else:
+                                if "underscore_span" not in data:
+                                    data["underscore_span"] = {}
                                 if attr not in data["underscore_span"]:
-                                    data["underscore_span"][attr] = {"token_start": start, "token_end": end, "value": value}
+                                    data["underscore_span"][attr] = []
+                                data["underscore_span"][attr].append({"start": start, "end": end, "value": value})
 
             for attr in underscore:
                 if attr not in user_keys:

From 3d0e895363921d4acb7f89a5b708472681e6fc1b Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Wed, 19 Oct 2022 17:33:55 +0200
Subject: [PATCH 130/174] Set version to v3.4.2 (#11672)

---
 spacy/about.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/spacy/about.py b/spacy/about.py
index 843c15aba..ce86e6294 100644
--- a/spacy/about.py
+++ b/spacy/about.py
@@ -1,6 +1,6 @@
 # fmt: off
 __title__ = "spacy"
-__version__ = "3.4.1"
+__version__ = "3.4.2"
 __download_url__ = "https://github.com/explosion/spacy-models/releases/download"
 __compatibility__ = "https://raw.githubusercontent.com/explosion/spacy-models/master/compatibility.json"
 __projects__ = "https://github.com/explosion/projects"

From bf83f6872a55e307da289fb901db3c16dd35e8d1 Mon Sep 17 00:00:00 2001
From: Paul O'Leary McCann <polm@dampfkraft.com>
Date: Thu, 20 Oct 2022 20:35:03 +0900
Subject: [PATCH 131/174] Add detailed example of env dict usage (#11677)

* Add detailed example of env dict usage

* Mark code blocks as yaml
---
 website/docs/usage/projects.md | 21 +++++++++++++++++++++
 1 file changed, 21 insertions(+)

diff --git a/website/docs/usage/projects.md b/website/docs/usage/projects.md
index 4797bbfe3..90b612358 100644
--- a/website/docs/usage/projects.md
+++ b/website/docs/usage/projects.md
@@ -243,6 +243,27 @@ pipelines.
 > python -m spacy project run test . --vars.foo bar
 > ```
 
+> #### Tip: Environment Variables
+>
+> Commands in a project file are not executed in a shell, so they don't have
+> direct access to environment variables. But you can insert environment
+> variables using the `env` dictionary to make values available for
+> interpolation, just like values in `vars`. Here's an example `env` dict that
+> makes `$PATH` available as `ENV_PATH`:
+>
+> ```yaml
+> env:
+>   ENV_PATH: PATH
+> ```
+>
+> This can be used in a project command like so:
+>
+> ```yaml
+>   - name: "echo-path"
+>     script:
+>       - "echo ${env.ENV_PATH}"
+> ```
+
 | Section                                             | Description                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  |
 | --------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
 | `title`                                             | An optional project title used in `--help` message and [auto-generated docs](#custom-docs).                                                                                                                                                                                                                                                                                                                                                                                                                  |

From b69d249a223fa4e633e11babc0830f3b68df57e2 Mon Sep 17 00:00:00 2001
From: Cellan Hall <60790416+Ce11an@users.noreply.github.com>
Date: Thu, 20 Oct 2022 12:38:29 +0100
Subject: [PATCH 132/174] Adding `spacy-cleaner` to the spaCy universe (#11674)

* added spacy-cleaner to the spaCy universe

* Move data to righ section of universe.json

* Cleanup

- fix typo ("replacers")
- spaCy doesn't need to be marked as code
- lemma of "Hello" is lower case

Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com>
---
 website/meta/universe.json | 41 ++++++++++++++++++++++++++++++++++++++
 1 file changed, 41 insertions(+)

diff --git a/website/meta/universe.json b/website/meta/universe.json
index 637e9d6ce..d7c99956b 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -1,5 +1,46 @@
 {
     "resources": [
+        {
+            "id": "spacy-cleaner",
+            "title": "spacy-cleaner",
+            "slogan": "Easily clean text with spaCy!",
+            "description": "**spacy-cleaner** utilises spaCy `Language` models to replace, remove, and \n  mutate spaCy tokens. Cleaning actions available are:\n\n* Remove/replace stopwords.\n* Remove/replace punctuation.\n* Remove/replace numbers.\n* Remove/replace emails.\n* Remove/replace URLs.\n* Perform lemmatisation.\n\nSee our [docs](https://ce11an.github.io/spacy-cleaner/) for more information.",
+            "github": "Ce11an/spacy-cleaner",
+            "pip": "spacy-cleaner",
+            "code_example": [
+                "import spacy",
+                "import spacy_cleaner",
+                "from spacy_cleaner.processing import removers, replacers, mutators",
+                "",
+                "model = spacy.load(\"en_core_web_sm\")",
+                "pipeline = spacy_cleaner.Pipeline(",
+                "    model,",
+                "    removers.remove_stopword_token,",
+                "    replacers.replace_punctuation_token,",
+                "    mutators.mutate_lemma_token,",
+                ")",
+                "",
+                "texts = [\"Hello, my name is Cellan! I love to swim!\"]",
+                "",
+                "pipeline.clean(texts)",
+                "# ['hello _IS_PUNCT_ Cellan _IS_PUNCT_ love swim _IS_PUNCT_']"
+            ],
+            "code_language": "python",
+            "url": "https://ce11an.github.io/spacy-cleaner/",
+            "image": "https://raw.githubusercontent.com/Ce11an/spacy-cleaner/main/docs/assets/images/spacemen.png",
+            "author": "Cellan Hall",
+            "author_links": {
+                "twitter": "Ce11an",
+                "github": "Ce11an",
+                "website": "https://www.linkedin.com/in/cellan-hall/"
+            },
+            "category": [
+                "extension"
+            ],
+            "tags": [
+                "text-processing"
+            ]
+        },
         {
             "id": "Zshot",
             "title": "Zshot",

From 84d9cb6b387572293c8bcf26b0e71b508104b165 Mon Sep 17 00:00:00 2001
From: "github-actions[bot]"
 <41898282+github-actions[bot]@users.noreply.github.com>
Date: Fri, 21 Oct 2022 11:54:17 +0200
Subject: [PATCH 133/174] Auto-format code with black (#11687)

Co-authored-by: explosion-bot <explosion-bot@users.noreply.github.com>
---
 spacy/tests/pipeline/test_tok2vec.py | 22 ++++++++++++++++------
 1 file changed, 16 insertions(+), 6 deletions(-)

diff --git a/spacy/tests/pipeline/test_tok2vec.py b/spacy/tests/pipeline/test_tok2vec.py
index 659274db9..e423d9a19 100644
--- a/spacy/tests/pipeline/test_tok2vec.py
+++ b/spacy/tests/pipeline/test_tok2vec.py
@@ -231,7 +231,7 @@ def test_tok2vec_listener_callback():
 
 
 def test_tok2vec_listener_overfitting():
-    """ Test that a pipeline with a listener properly overfits, even if 'tok2vec' is in the annotating components """
+    """Test that a pipeline with a listener properly overfits, even if 'tok2vec' is in the annotating components"""
     orig_config = Config().from_str(cfg_string)
     nlp = util.load_model_from_config(orig_config, auto_fill=True, validate=True)
     train_examples = []
@@ -264,7 +264,7 @@ def test_tok2vec_listener_overfitting():
 
 
 def test_tok2vec_frozen_not_annotating():
-    """ Test that a pipeline with a frozen tok2vec raises an error when the tok2vec is not annotating """
+    """Test that a pipeline with a frozen tok2vec raises an error when the tok2vec is not annotating"""
     orig_config = Config().from_str(cfg_string)
     nlp = util.load_model_from_config(orig_config, auto_fill=True, validate=True)
     train_examples = []
@@ -274,12 +274,16 @@ def test_tok2vec_frozen_not_annotating():
 
     for i in range(2):
         losses = {}
-        with pytest.raises(ValueError, match=r"the tok2vec embedding layer is not updated"):
-            nlp.update(train_examples, sgd=optimizer, losses=losses, exclude=["tok2vec"])
+        with pytest.raises(
+            ValueError, match=r"the tok2vec embedding layer is not updated"
+        ):
+            nlp.update(
+                train_examples, sgd=optimizer, losses=losses, exclude=["tok2vec"]
+            )
 
 
 def test_tok2vec_frozen_overfitting():
-    """ Test that a pipeline with a frozen & annotating tok2vec can still overfit """
+    """Test that a pipeline with a frozen & annotating tok2vec can still overfit"""
     orig_config = Config().from_str(cfg_string)
     nlp = util.load_model_from_config(orig_config, auto_fill=True, validate=True)
     train_examples = []
@@ -289,7 +293,13 @@ def test_tok2vec_frozen_overfitting():
 
     for i in range(100):
         losses = {}
-        nlp.update(train_examples, sgd=optimizer, losses=losses, exclude=["tok2vec"], annotates=["tok2vec"])
+        nlp.update(
+            train_examples,
+            sgd=optimizer,
+            losses=losses,
+            exclude=["tok2vec"],
+            annotates=["tok2vec"],
+        )
     assert losses["tagger"] < 0.0001
 
     # test the trained model

From 88d35450dcedd89fa739640d8a8d3e62f3643b4a Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Tue, 25 Oct 2022 14:53:18 +0200
Subject: [PATCH 134/174] Rename test helper method with non-test_ name
 (#11701)

---
 spacy/tests/test_models.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/spacy/tests/test_models.py b/spacy/tests/test_models.py
index 2306cabb7..d91ed1201 100644
--- a/spacy/tests/test_models.py
+++ b/spacy/tests/test_models.py
@@ -23,7 +23,7 @@ def get_textcat_bow_kwargs():
 
 
 def get_textcat_cnn_kwargs():
-    return {"tok2vec": test_tok2vec(), "exclusive_classes": False, "nO": 13}
+    return {"tok2vec": make_test_tok2vec(), "exclusive_classes": False, "nO": 13}
 
 
 def get_all_params(model):
@@ -65,7 +65,7 @@ def get_tok2vec_kwargs():
     }
 
 
-def test_tok2vec():
+def make_test_tok2vec():
     return build_Tok2Vec_model(**get_tok2vec_kwargs())
 
 

From 8740e4341f03fe2720f50c64e2f94a339d6bd4be Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Tue, 25 Oct 2022 14:54:54 +0200
Subject: [PATCH 135/174] Update languages and version in README and website
 (#11694)

---
 README.md                   |  6 +++---
 website/meta/languages.json | 28 ++++++++++++++++++++++++++--
 2 files changed, 29 insertions(+), 5 deletions(-)

diff --git a/README.md b/README.md
index d9ef83e01..abfc3da67 100644
--- a/README.md
+++ b/README.md
@@ -8,7 +8,7 @@ be used in real products.
 
 spaCy comes with
 [pretrained pipelines](https://spacy.io/models) and
-currently supports tokenization and training for **60+ languages**. It features
+currently supports tokenization and training for **70+ languages**. It features
 state-of-the-art speed and **neural network models** for tagging,
 parsing, **named entity recognition**, **text classification** and more,
 multi-task learning with pretrained **transformers** like BERT, as well as a
@@ -16,7 +16,7 @@ production-ready [**training system**](https://spacy.io/usage/training) and easy
 model packaging, deployment and workflow management. spaCy is commercial
 open-source software, released under the MIT license.
 
-💫 **Version 3.4.0 out now!**
+💫 **Version 3.4 out now!**
 [Check out the release notes here.](https://github.com/explosion/spaCy/releases)
 
 [![Azure Pipelines](https://img.shields.io/azure-devops/build/explosion-ai/public/8/master.svg?logo=azure-pipelines&style=flat-square&label=build)](https://dev.azure.com/explosion-ai/public/_build?definitionId=8)
@@ -79,7 +79,7 @@ more people can benefit from it.
 
 ## Features
 
-- Support for **60+ languages**
+- Support for **70+ languages**
 - **Trained pipelines** for different languages and tasks
 - Multi-task learning with pretrained **transformers** like BERT
 - Support for pretrained **word vectors** and embeddings
diff --git a/website/meta/languages.json b/website/meta/languages.json
index 0028b4a5f..bd1535c90 100644
--- a/website/meta/languages.json
+++ b/website/meta/languages.json
@@ -4,12 +4,22 @@
             "code": "af",
             "name": "Afrikaans"
         },
+        {
+            "code": "am",
+            "name": "Amharic",
+            "has_examples": true
+        },
         {
             "code": "ar",
             "name": "Arabic",
             "example": "هذه جملة",
             "has_examples": true
         },
+        {
+            "code": "az",
+            "name": "Azerbaijani",
+            "has_examples": true
+        },
         {
             "code": "bg",
             "name": "Bulgarian",
@@ -65,7 +75,7 @@
         {
             "code": "dsb",
             "name": "Lower Sorbian",
-	    "has_examples": true
+            "has_examples": true
         },
         {
             "code": "el",
@@ -142,6 +152,11 @@
             "code": "ga",
             "name": "Irish"
         },
+        {
+            "code": "grc",
+            "name": "Ancient Greek",
+            "has_examples": true
+        },
         {
             "code": "gu",
             "name": "Gujarati",
@@ -172,7 +187,7 @@
         {
             "code": "hsb",
             "name": "Upper Sorbian",
-	    "has_examples": true
+            "has_examples": true
         },
         {
             "code": "hu",
@@ -260,6 +275,10 @@
             "example": "Адамга эң кыйыны — күн сайын адам болуу",
             "has_examples": true
         },
+        {
+            "code": "la",
+            "name": "Latin"
+        },
         {
             "code": "lb",
             "name": "Luxembourgish",
@@ -448,6 +467,11 @@
             "example": "นี่คือประโยค",
             "has_examples": true
         },
+        {
+            "code": "ti",
+            "name": "Tigrinya",
+            "has_examples": true
+        },
         {
             "code": "tl",
             "name": "Tagalog"

From 0a9859ba01c8a51842218e1817dff7ff784951df Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Tue, 25 Oct 2022 19:38:23 +0200
Subject: [PATCH 136/174] Reduce python 3.10 in CI to one OS (#11703)

---
 azure-pipelines.yml | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/azure-pipelines.yml b/azure-pipelines.yml
index 357cce835..eea07cb7a 100644
--- a/azure-pipelines.yml
+++ b/azure-pipelines.yml
@@ -76,15 +76,15 @@ jobs:
         #        Python39Mac:
         #          imageName: "macos-latest"
         #          python.version: "3.9"
-        Python310Linux:
-          imageName: "ubuntu-latest"
-          python.version: "3.10"
+        #        Python310Linux:
+        #          imageName: "ubuntu-latest"
+        #          python.version: "3.10"
         Python310Windows:
           imageName: "windows-latest"
           python.version: "3.10"
-        Python310Mac:
-          imageName: "macos-latest"
-          python.version: "3.10"
+        #        Python310Mac:
+        #          imageName: "macos-latest"
+        #          python.version: "3.10"
         Python311Linux:
           imageName: 'ubuntu-latest'
           python.version: '3.11.0-rc.2'

From a9139907a943f0cc91dac0338aa43caa38939778 Mon Sep 17 00:00:00 2001
From: Ryn Daniels <397565+ryndaniels@users.noreply.github.com>
Date: Wed, 26 Oct 2022 09:15:13 +0300
Subject: [PATCH 137/174] update github actions to deal with deprecations
 (#11702)

---
 .github/workflows/autoblack.yml | 9 +++++----
 1 file changed, 5 insertions(+), 4 deletions(-)

diff --git a/.github/workflows/autoblack.yml b/.github/workflows/autoblack.yml
index 8d0282650..3ad4cf408 100644
--- a/.github/workflows/autoblack.yml
+++ b/.github/workflows/autoblack.yml
@@ -12,10 +12,10 @@ jobs:
     if: github.repository_owner == 'explosion'
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v3
         with:
             ref: ${{ github.head_ref }}
-      - uses: actions/setup-python@v2
+      - uses: actions/setup-python@v3
       - run: pip install black
       - name: Auto-format code if needed
         run: black spacy
@@ -23,10 +23,11 @@ jobs:
       # code and makes GitHub think the action failed
       - name: Check for modified files
         id: git-check
-        run: echo ::set-output name=modified::$(if git diff-index --quiet HEAD --; then echo "false"; else echo "true"; fi)
+        run: echo modified=$(if git diff-index --quiet HEAD --; then echo "false"; else echo "true"; fi) >> $GITHUB_OUTPUT
+
       - name: Create Pull Request
         if: steps.git-check.outputs.modified == 'true'
-        uses: peter-evans/create-pull-request@v3
+        uses: peter-evans/create-pull-request@v4
         with:
             title: Auto-format code with black
             labels: meta

From 865691d169c3be413007f0d7324e03a7aac3b3cb Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Wed, 26 Oct 2022 08:43:00 +0200
Subject: [PATCH 138/174] Adjust default attrs for textcat configs (#11698)

---
 spacy/pipeline/textcat.py            | 4 ++--
 spacy/pipeline/textcat_multilabel.py | 4 ++--
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/spacy/pipeline/textcat.py b/spacy/pipeline/textcat.py
index c45f819fc..59549ad99 100644
--- a/spacy/pipeline/textcat.py
+++ b/spacy/pipeline/textcat.py
@@ -24,8 +24,8 @@ single_label_default_config = """
 [model.tok2vec.embed]
 @architectures = "spacy.MultiHashEmbed.v2"
 width = 64
-rows = [2000, 2000, 1000, 1000, 1000, 1000]
-attrs = ["ORTH", "LOWER", "PREFIX", "SUFFIX", "SHAPE", "ID"]
+rows = [2000, 2000, 500, 1000, 500]
+attrs = ["NORM", "LOWER", "PREFIX", "SUFFIX", "SHAPE"]
 include_static_vectors = false
 
 [model.tok2vec.encode]
diff --git a/spacy/pipeline/textcat_multilabel.py b/spacy/pipeline/textcat_multilabel.py
index 493c440c3..eb83d9cb7 100644
--- a/spacy/pipeline/textcat_multilabel.py
+++ b/spacy/pipeline/textcat_multilabel.py
@@ -24,8 +24,8 @@ multi_label_default_config = """
 [model.tok2vec.embed]
 @architectures = "spacy.MultiHashEmbed.v2"
 width = 64
-rows = [2000, 2000, 1000, 1000, 1000, 1000]
-attrs = ["ORTH", "LOWER", "PREFIX", "SUFFIX", "SHAPE", "ID"]
+rows = [2000, 2000, 500, 1000, 500]
+attrs = ["NORM", "LOWER", "PREFIX", "SUFFIX", "SHAPE"]
 include_static_vectors = false
 
 [model.tok2vec.encode]

From 6b78135b9e158e5bc02e39c1a73ef28bb360a44f Mon Sep 17 00:00:00 2001
From: Paul O'Leary McCann <polm@dampfkraft.com>
Date: Thu, 27 Oct 2022 22:08:24 +0900
Subject: [PATCH 139/174] Add warning to install widget for M1 GPUs (#11666)

* Add warning to install widget for M1 GPUs

* Use Thinc tracking issue instead

* Update website/src/widgets/quickstart-install.js

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

* Underline URL in warning

* Update website/src/widgets/quickstart-install.js

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

* Don't install cupy on m1 gpus

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
---
 website/src/styles/quickstart.module.sass |  3 +++
 website/src/widgets/quickstart-install.js | 11 ++++++++++-
 2 files changed, 13 insertions(+), 1 deletion(-)

diff --git a/website/src/styles/quickstart.module.sass b/website/src/styles/quickstart.module.sass
index 8ad106a78..d0f9db551 100644
--- a/website/src/styles/quickstart.module.sass
+++ b/website/src/styles/quickstart.module.sass
@@ -149,6 +149,9 @@
     & > span
         display: block
 
+    a
+        text-decoration: underline
+
 .small
     font-size: var(--font-size-code)
     line-height: 1.65
diff --git a/website/src/widgets/quickstart-install.js b/website/src/widgets/quickstart-install.js
index 0d2186acb..28dd14ecc 100644
--- a/website/src/widgets/quickstart-install.js
+++ b/website/src/widgets/quickstart-install.js
@@ -159,6 +159,9 @@ const QuickstartInstall = ({ id, title }) => {
                         setters={setters}
                         showDropdown={showDropdown}
                     >
+                        <QS os="mac" hardware="gpu" platform="arm">
+                            # Note M1 GPU support is experimental, see <a href="https://github.com/explosion/thinc/issues/792">Thinc issue #792</a>
+                        </QS>
                         <QS package="pip" config="venv">
                             python -m venv .env
                         </QS>
@@ -198,7 +201,13 @@ const QuickstartInstall = ({ id, title }) => {
                             {nightly ? ' --pre' : ''}
                         </QS>
                         <QS package="conda">conda install -c conda-forge spacy</QS>
-                        <QS package="conda" hardware="gpu">
+                        <QS package="conda" hardware="gpu" os="windows">
+                            conda install -c conda-forge cupy
+                        </QS>
+                        <QS package="conda" hardware="gpu" os="linux">
+                            conda install -c conda-forge cupy
+                        </QS>
+                        <QS package="conda" hardware="gpu" os="mac" platform="x86">
                             conda install -c conda-forge cupy
                         </QS>
                         <QS package="conda" config="train">

From d61e742960ef230b423dfa157449b291a03bd119 Mon Sep 17 00:00:00 2001
From: Paul O'Leary McCann <polm@dampfkraft.com>
Date: Fri, 28 Oct 2022 17:25:34 +0900
Subject: [PATCH 140/174] Handle Docs with no entities in EntityLinker (#11640)

* Handle docs with no entities

If a whole batch contains no entities it won't make it to the model, but
it's possible for individual Docs to have no entities. Before this
commit, those Docs would cause an error when attempting to concatenate
arrays because the dimensions didn't match.

It turns out the process of preparing the Ragged at the end of the span
maker forward was a little different from list2ragged, which just uses
the flatten function directly. Letting list2ragged do the conversion
avoids the dimension issue.

This did not come up before because in NEL demo projects it's typical
for data with no entities to be discarded before it reaches the NEL
component.

This includes a simple direct test that shows the issue and checks it's
resolved. It doesn't check if there are any downstream changes, so a
more complete test could be added. A full run was tested by adding an
example with no entities to the Emerson sample project.

* Add a blank instance to default training data in tests

Rather than adding a specific test, since not failing on instances with
no entities is basic functionality, it makes sense to add it to the
default set.

* Fix without modifying architecture

If the architecture is modified this would have to be a new version, but
this change isn't big enough to merit that.
---
 spacy/ml/models/entity_linker.py           |  7 +++----
 spacy/tests/pipeline/test_entity_linker.py | 22 +++++++++++++++++++++-
 2 files changed, 24 insertions(+), 5 deletions(-)

diff --git a/spacy/ml/models/entity_linker.py b/spacy/ml/models/entity_linker.py
index 4d18d216a..299b6bb52 100644
--- a/spacy/ml/models/entity_linker.py
+++ b/spacy/ml/models/entity_linker.py
@@ -71,11 +71,10 @@ def span_maker_forward(model, docs: List[Doc], is_train) -> Tuple[Ragged, Callab
             cands.append((start_token, end_token))
 
         candidates.append(ops.asarray2i(cands))
-    candlens = ops.asarray1i([len(cands) for cands in candidates])
-    candidates = ops.xp.concatenate(candidates)
-    outputs = Ragged(candidates, candlens)
+    lengths = model.ops.asarray1i([len(cands) for cands in candidates])
+    out = Ragged(model.ops.flatten(candidates), lengths)
     # because this is just rearranging docs, the backprop does nothing
-    return outputs, lambda x: []
+    return out, lambda x: []
 
 
 @registry.misc("spacy.KBFromFile.v1")
diff --git a/spacy/tests/pipeline/test_entity_linker.py b/spacy/tests/pipeline/test_entity_linker.py
index 4d683acc5..99f164f15 100644
--- a/spacy/tests/pipeline/test_entity_linker.py
+++ b/spacy/tests/pipeline/test_entity_linker.py
@@ -9,6 +9,7 @@ from spacy.compat import pickle
 from spacy.kb import Candidate, InMemoryLookupKB, get_candidates, KnowledgeBase
 from spacy.lang.en import English
 from spacy.ml import load_kb
+from spacy.ml.models.entity_linker import build_span_maker
 from spacy.pipeline import EntityLinker
 from spacy.pipeline.legacy import EntityLinker_v1
 from spacy.pipeline.tok2vec import DEFAULT_TOK2VEC_MODEL
@@ -715,7 +716,11 @@ TRAIN_DATA = [
     ("Russ Cochran was a member of University of Kentucky's golf team.",
         {"links": {(0, 12): {"Q7381115": 0.0, "Q2146908": 1.0}},
          "entities": [(0, 12, "PERSON"), (43, 51, "LOC")],
-         "sent_starts": [1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]})
+         "sent_starts": [1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]}),
+    # having a blank instance shouldn't break things
+    ("The weather is nice today.",
+        {"links": {}, "entities": [],
+         "sent_starts": [1, -1, 0, 0, 0, 0]})
 ]
 GOLD_entities = ["Q2146908", "Q7381115", "Q7381115", "Q2146908"]
 # fmt: on
@@ -1196,3 +1201,18 @@ def test_threshold(meet_threshold: bool, config: Dict[str, Any]):
 
     assert len(doc.ents) == 1
     assert doc.ents[0].kb_id_ == entity_id if meet_threshold else EntityLinker.NIL
+
+
+def test_span_maker_forward_with_empty():
+    """The forward pass of the span maker may have a doc with no entities."""
+    nlp = English()
+    doc1 = nlp("a b c")
+    ent = doc1[0:1]
+    ent.label_ = "X"
+    doc1.ents = [ent]
+    # no entities
+    doc2 = nlp("x y z")
+
+    # just to get a model
+    span_maker = build_span_maker()
+    span_maker([doc1, doc2], False)

From d25f09468c4eca20eb464d78d35e439474ed2dbc Mon Sep 17 00:00:00 2001
From: Aaron Zipp <15341396+aaronzipp@users.noreply.github.com>
Date: Mon, 31 Oct 2022 05:27:12 +0100
Subject: [PATCH 141/174] Spelling mistake in rule-based-matching.md (#11717)

Changed retokenize to retokenizer
---
 website/docs/usage/rule-based-matching.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/website/docs/usage/rule-based-matching.md b/website/docs/usage/rule-based-matching.md
index f096890cb..64bbf8e7b 100644
--- a/website/docs/usage/rule-based-matching.md
+++ b/website/docs/usage/rule-based-matching.md
@@ -1792,7 +1792,7 @@ the entity `Span` – for example `._.orgs` or `._.prev_orgs` and
 > [`Doc.retokenize`](/api/doc#retokenize) context manager:
 >
 > ```python
-> with doc.retokenize() as retokenize:
+> with doc.retokenize() as retokenizer:
 >   for ent in doc.ents:
 >       retokenizer.merge(ent)
 > ```

From f7edd84b44a37b78d87fe6815399a576f1980b8b Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Wed, 2 Nov 2022 13:42:20 +0100
Subject: [PATCH 142/174] Switch CI to Python 3.11.0 (#11737)

---
 azure-pipelines.yml | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/azure-pipelines.yml b/azure-pipelines.yml
index eea07cb7a..bf3672b8b 100644
--- a/azure-pipelines.yml
+++ b/azure-pipelines.yml
@@ -87,13 +87,13 @@ jobs:
         #          python.version: "3.10"
         Python311Linux:
           imageName: 'ubuntu-latest'
-          python.version: '3.11.0-rc.2'
+          python.version: '3.11.0'
         Python311Windows:
           imageName: 'windows-latest'
-          python.version: '3.11.0-rc.2'
+          python.version: '3.11.0'
         Python311Mac:
           imageName: 'macos-latest'
-          python.version: '3.11.0-rc.2'
+          python.version: '3.11.0'
       maxParallel: 4
     pool:
       vmImage: $(imageName)

From 420b1d854be86e899088bb136f1daf23fc61ed1d Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Wed, 2 Nov 2022 15:35:04 +0100
Subject: [PATCH 143/174] Update textcat scorer threshold behavior (#11696)

* Update textcat scorer threshold behavior

For `textcat` (with exclusive classes) the scorer should always use a
threshold of 0.0 because there should be one predicted label per doc and
the numeric score for that particular label should not matter.

* Rename to test_textcat_multilabel_threshold

* Remove all uses of threshold for multi_label=False

* Update Scorer.score_cats API docs

* Add tests for score_cats with thresholds

* Update textcat API docs

* Fix types

* Convert threshold back to float

* Fix threshold type in docstring

* Improve formatting in Scorer API docs
---
 spacy/pipeline/textcat.py            |  7 +++--
 spacy/scorer.py                      | 12 +++----
 spacy/tests/pipeline/test_textcat.py |  6 ++--
 spacy/tests/test_scorer.py           | 47 ++++++++++++++++++++++++++++
 website/docs/api/scorer.md           | 21 +++++++------
 website/docs/api/textcategorizer.md  |  5 ++-
 6 files changed, 73 insertions(+), 25 deletions(-)

diff --git a/spacy/pipeline/textcat.py b/spacy/pipeline/textcat.py
index 59549ad99..238a768ed 100644
--- a/spacy/pipeline/textcat.py
+++ b/spacy/pipeline/textcat.py
@@ -72,7 +72,7 @@ subword_features = true
     "textcat",
     assigns=["doc.cats"],
     default_config={
-        "threshold": 0.5,
+        "threshold": 0.0,
         "model": DEFAULT_SINGLE_TEXTCAT_MODEL,
         "scorer": {"@scorers": "spacy.textcat_scorer.v1"},
     },
@@ -144,7 +144,8 @@ class TextCategorizer(TrainablePipe):
         model (thinc.api.Model): The Thinc Model powering the pipeline component.
         name (str): The component instance name, used to add entries to the
             losses during training.
-        threshold (float): Cutoff to consider a prediction "positive".
+        threshold (float): Unused, not needed for single-label (exclusive
+            classes) classification.
         scorer (Optional[Callable]): The scoring method. Defaults to
                 Scorer.score_cats for the attribute "cats".
 
@@ -154,7 +155,7 @@ class TextCategorizer(TrainablePipe):
         self.model = model
         self.name = name
         self._rehearsal_model = None
-        cfg = {"labels": [], "threshold": threshold, "positive_label": None}
+        cfg: Dict[str, Any] = {"labels": [], "threshold": threshold, "positive_label": None}
         self.cfg = dict(cfg)
         self.scorer = scorer
 
diff --git a/spacy/scorer.py b/spacy/scorer.py
index 8cd755ac4..16fc303a0 100644
--- a/spacy/scorer.py
+++ b/spacy/scorer.py
@@ -446,7 +446,7 @@ class Scorer:
         labels (Iterable[str]): The set of possible labels. Defaults to [].
         multi_label (bool): Whether the attribute allows multiple labels.
             Defaults to True. When set to False (exclusive labels), missing
-            gold labels are interpreted as 0.0.
+            gold labels are interpreted as 0.0 and the threshold is set to 0.0.
         positive_label (str): The positive label for a binary task with
             exclusive classes. Defaults to None.
         threshold (float): Cutoff to consider a prediction "positive". Defaults
@@ -471,6 +471,8 @@ class Scorer:
         """
         if threshold is None:
             threshold = 0.5 if multi_label else 0.0
+        if not multi_label:
+            threshold = 0.0
         f_per_type = {label: PRFScore() for label in labels}
         auc_per_type = {label: ROCAUCScore() for label in labels}
         labels = set(labels)
@@ -505,20 +507,18 @@ class Scorer:
                 # Get the highest-scoring for each.
                 pred_label, pred_score = max(pred_cats.items(), key=lambda it: it[1])
                 gold_label, gold_score = max(gold_cats.items(), key=lambda it: it[1])
-                if pred_label == gold_label and pred_score >= threshold:
+                if pred_label == gold_label:
                     f_per_type[pred_label].tp += 1
                 else:
                     f_per_type[gold_label].fn += 1
-                    if pred_score >= threshold:
-                        f_per_type[pred_label].fp += 1
+                    f_per_type[pred_label].fp += 1
             elif gold_cats:
                 gold_label, gold_score = max(gold_cats, key=lambda it: it[1])
                 if gold_score > 0:
                     f_per_type[gold_label].fn += 1
             elif pred_cats:
                 pred_label, pred_score = max(pred_cats.items(), key=lambda it: it[1])
-                if pred_score >= threshold:
-                    f_per_type[pred_label].fp += 1
+                f_per_type[pred_label].fp += 1
         micro_prf = PRFScore()
         for label_prf in f_per_type.values():
             micro_prf.tp += label_prf.tp
diff --git a/spacy/tests/pipeline/test_textcat.py b/spacy/tests/pipeline/test_textcat.py
index 0bb036a33..d359b77db 100644
--- a/spacy/tests/pipeline/test_textcat.py
+++ b/spacy/tests/pipeline/test_textcat.py
@@ -823,10 +823,10 @@ def test_textcat_loss(multi_label: bool, expected_loss: float):
     assert loss == expected_loss
 
 
-def test_textcat_threshold():
+def test_textcat_multilabel_threshold():
     # Ensure the scorer can be called with a different threshold
     nlp = English()
-    nlp.add_pipe("textcat")
+    nlp.add_pipe("textcat_multilabel")
 
     train_examples = []
     for text, annotations in TRAIN_DATA_SINGLE_LABEL:
@@ -849,7 +849,7 @@ def test_textcat_threshold():
     )
     pos_f = scores["cats_score"]
     assert scores["cats_f_per_type"]["POSITIVE"]["r"] == 1.0
-    assert pos_f > macro_f
+    assert pos_f >= macro_f
 
 
 def test_textcat_multi_threshold():
diff --git a/spacy/tests/test_scorer.py b/spacy/tests/test_scorer.py
index 6e15fa2de..b903f1669 100644
--- a/spacy/tests/test_scorer.py
+++ b/spacy/tests/test_scorer.py
@@ -474,3 +474,50 @@ def test_prf_score():
     assert (a.precision, a.recall, a.fscore) == approx(
         (c.precision, c.recall, c.fscore)
     )
+
+
+def test_score_cats(en_tokenizer):
+    text = "some text"
+    gold_doc = en_tokenizer(text)
+    gold_doc.cats = {"POSITIVE": 1.0, "NEGATIVE": 0.0}
+    pred_doc = en_tokenizer(text)
+    pred_doc.cats = {"POSITIVE": 0.75, "NEGATIVE": 0.25}
+    example = Example(pred_doc, gold_doc)
+    # threshold is ignored for multi_label=False
+    scores1 = Scorer.score_cats(
+        [example],
+        "cats",
+        labels=list(gold_doc.cats.keys()),
+        multi_label=False,
+        positive_label="POSITIVE",
+        threshold=0.1,
+    )
+    scores2 = Scorer.score_cats(
+        [example],
+        "cats",
+        labels=list(gold_doc.cats.keys()),
+        multi_label=False,
+        positive_label="POSITIVE",
+        threshold=0.9,
+    )
+    assert scores1["cats_score"] == 1.0
+    assert scores2["cats_score"] == 1.0
+    assert scores1 == scores2
+    # threshold is relevant for multi_label=True
+    scores = Scorer.score_cats(
+        [example],
+        "cats",
+        labels=list(gold_doc.cats.keys()),
+        multi_label=True,
+        threshold=0.9,
+    )
+    assert scores["cats_macro_f"] == 0.0
+    # threshold is relevant for multi_label=True
+    scores = Scorer.score_cats(
+        [example],
+        "cats",
+        labels=list(gold_doc.cats.keys()),
+        multi_label=True,
+        threshold=0.1,
+    )
+    assert scores["cats_macro_f"] == 0.5
diff --git a/website/docs/api/scorer.md b/website/docs/api/scorer.md
index ca3462aa9..9ef36e6fc 100644
--- a/website/docs/api/scorer.md
+++ b/website/docs/api/scorer.md
@@ -229,16 +229,17 @@ The reported `{attr}_score` depends on the classification properties:
 > print(scores["cats_macro_auc"])
 > ```
 
-| Name             | Description                                                                                                                                        |
-| ---------------- | -------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `examples`       | The `Example` objects holding both the predictions and the correct gold-standard annotations. ~~Iterable[Example]~~                                |
-| `attr`           | The attribute to score. ~~str~~                                                                                                                    |
-| _keyword-only_   |                                                                                                                                                    |
-| `getter`         | Defaults to `getattr`. If provided, `getter(doc, attr)` should return the cats for an individual `Doc`. ~~Callable[[Doc, str], Dict[str, float]]~~ |
-| labels           | The set of possible labels. Defaults to `[]`. ~~Iterable[str]~~                                                                                    |
-| `multi_label`    | Whether the attribute allows multiple labels. Defaults to `True`. ~~bool~~                                                                         |
-| `positive_label` | The positive label for a binary task with exclusive classes. Defaults to `None`. ~~Optional[str]~~                                                 |
-| **RETURNS**      | A dictionary containing the scores, with inapplicable scores as `None`. ~~Dict[str, Optional[float]]~~                                             |
+| Name             | Description                                                                                                                                                                                        |
+| ---------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `examples`       | The `Example` objects holding both the predictions and the correct gold-standard annotations. ~~Iterable[Example]~~                                                                                |
+| `attr`           | The attribute to score. ~~str~~                                                                                                                                                                    |
+| _keyword-only_   |                                                                                                                                                                                                    |
+| `getter`         | Defaults to `getattr`. If provided, `getter(doc, attr)` should return the cats for an individual `Doc`. ~~Callable[[Doc, str], Dict[str, float]]~~                                                 |
+| labels           | The set of possible labels. Defaults to `[]`. ~~Iterable[str]~~                                                                                                                                    |
+| `multi_label`    | Whether the attribute allows multiple labels. Defaults to `True`. When set to `False` (exclusive labels), missing gold labels are interpreted as `0.0` and the threshold is set to `0.0`. ~~bool~~ |
+| `positive_label` | The positive label for a binary task with exclusive classes. Defaults to `None`. ~~Optional[str]~~                                                                                                 |
+| `threshold`      | Cutoff to consider a prediction "positive". Defaults to `0.5` for multi-label, and `0.0` (i.e. whatever's highest scoring) otherwise. ~~float~~                                                    |
+| **RETURNS**      | A dictionary containing the scores, with inapplicable scores as `None`. ~~Dict[str, Optional[float]]~~                                                                                             |
 
 ## Scorer.score_links {#score_links tag="staticmethod" new="3"}
 
diff --git a/website/docs/api/textcategorizer.md b/website/docs/api/textcategorizer.md
index 042b4ab76..f5f8706ec 100644
--- a/website/docs/api/textcategorizer.md
+++ b/website/docs/api/textcategorizer.md
@@ -63,7 +63,6 @@ architectures and their arguments and hyperparameters.
 > ```python
 > from spacy.pipeline.textcat import DEFAULT_SINGLE_TEXTCAT_MODEL
 > config = {
->    "threshold": 0.5,
 >    "model": DEFAULT_SINGLE_TEXTCAT_MODEL,
 > }
 > nlp.add_pipe("textcat", config=config)
@@ -82,7 +81,7 @@ architectures and their arguments and hyperparameters.
 
 | Setting     | Description                                                                                                                                                      |
 | ----------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `threshold` | Cutoff to consider a prediction "positive", relevant when printing accuracy results. ~~float~~                                                                   |
+| `threshold` | Cutoff to consider a prediction "positive", relevant for `textcat_multilabel` when calculating accuracy scores. ~~float~~                                        |
 | `model`     | A model instance that predicts scores for each category. Defaults to [TextCatEnsemble](/api/architectures#TextCatEnsemble). ~~Model[List[Doc], List[Floats2d]]~~ |
 | `scorer`    | The scoring method. Defaults to [`Scorer.score_cats`](/api/scorer#score_cats) for the attribute `"cats"`. ~~Optional[Callable]~~                                 |
 
@@ -123,7 +122,7 @@ shortcut for this and instantiate the component using its string name and
 | `model`        | The Thinc [`Model`](https://thinc.ai/docs/api-model) powering the pipeline component. ~~Model[List[Doc], List[Floats2d]]~~       |
 | `name`         | String name of the component instance. Used to add entries to the `losses` during training. ~~str~~                              |
 | _keyword-only_ |                                                                                                                                  |
-| `threshold`    | Cutoff to consider a prediction "positive", relevant when printing accuracy results. ~~float~~                                   |
+| `threshold`    | Cutoff to consider a prediction "positive", relevant for `textcat_multilabel` when calculating accuracy scores. ~~float~~        |
 | `scorer`       | The scoring method. Defaults to [`Scorer.score_cats`](/api/scorer#score_cats) for the attribute `"cats"`. ~~Optional[Callable]~~ |
 
 ## TextCategorizer.\_\_call\_\_ {#call tag="method"}

From 2fb7e4dc74bd491ecec43971b2b29b0d28efd492 Mon Sep 17 00:00:00 2001
From: Ryn Daniels <397565+ryndaniels@users.noreply.github.com>
Date: Wed, 2 Nov 2022 16:36:30 +0200
Subject: [PATCH 144/174] More version updates for github action deprecation
 warnings (#11705)

* More version updates for github action deprecation warnings

* fix the deprecated set-output commands

* bump explosion-bot to run on ubuntu-latest
---
 .github/workflows/autoblack.yml            | 2 +-
 .github/workflows/explosionbot.yml         | 6 +++---
 .github/workflows/slowtests.yml            | 6 +++---
 .github/workflows/spacy_universe_alert.yml | 4 ++--
 4 files changed, 9 insertions(+), 9 deletions(-)

diff --git a/.github/workflows/autoblack.yml b/.github/workflows/autoblack.yml
index 3ad4cf408..70882c3cc 100644
--- a/.github/workflows/autoblack.yml
+++ b/.github/workflows/autoblack.yml
@@ -15,7 +15,7 @@ jobs:
       - uses: actions/checkout@v3
         with:
             ref: ${{ github.head_ref }}
-      - uses: actions/setup-python@v3
+      - uses: actions/setup-python@v4
       - run: pip install black
       - name: Auto-format code if needed
         run: black spacy
diff --git a/.github/workflows/explosionbot.yml b/.github/workflows/explosionbot.yml
index d585ecd9c..6b472cd12 100644
--- a/.github/workflows/explosionbot.yml
+++ b/.github/workflows/explosionbot.yml
@@ -8,14 +8,14 @@ on:
 
 jobs:
   explosion-bot:
-    runs-on: ubuntu-18.04
+    runs-on: ubuntu-latest
     steps:
       - name: Dump GitHub context
         env:
           GITHUB_CONTEXT: ${{ toJson(github) }}
         run: echo "$GITHUB_CONTEXT"
-      - uses: actions/checkout@v1
-      - uses: actions/setup-python@v1
+      - uses: actions/checkout@v3
+      - uses: actions/setup-python@v4
       - name: Install and run explosion-bot
         run: |
           pip install git+https://${{ secrets.EXPLOSIONBOT_TOKEN }}@github.com/explosion/explosion-bot
diff --git a/.github/workflows/slowtests.yml b/.github/workflows/slowtests.yml
index 38ceb18c6..f9fd3e817 100644
--- a/.github/workflows/slowtests.yml
+++ b/.github/workflows/slowtests.yml
@@ -14,7 +14,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Checkout
-        uses: actions/checkout@v1
+        uses: actions/checkout@v3
         with:
           ref: ${{ matrix.branch }}
       - name: Get commits from past 24 hours
@@ -23,9 +23,9 @@ jobs:
           today=$(date '+%Y-%m-%d %H:%M:%S')
           yesterday=$(date -d "yesterday" '+%Y-%m-%d %H:%M:%S')
           if git log --after="$yesterday" --before="$today" | grep commit ; then
-            echo "::set-output name=run_tests::true"
+            echo run_tests=true >> $GITHUB_OUTPUT
           else
-            echo "::set-output name=run_tests::false"
+            echo run_tests=false >> $GITHUB_OUTPUT
           fi
 
       - name: Trigger buildkite build
diff --git a/.github/workflows/spacy_universe_alert.yml b/.github/workflows/spacy_universe_alert.yml
index cbbf14c6e..f507e0594 100644
--- a/.github/workflows/spacy_universe_alert.yml
+++ b/.github/workflows/spacy_universe_alert.yml
@@ -17,8 +17,8 @@ jobs:
         run: |
           echo "$GITHUB_CONTEXT"
 
-      - uses: actions/checkout@v1
-      - uses: actions/setup-python@v1
+      - uses: actions/checkout@v3
+      - uses: actions/setup-python@v4
       - name: Install Bernadette app dependency and send an alert
         env:
           SLACK_BOT_TOKEN: ${{ secrets.SLACK_BOT_TOKEN }}

From 1211552f0ec84aef0b55f834d76899ab07e2c5cc Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Thu, 3 Nov 2022 09:29:46 +0100
Subject: [PATCH 145/174] Modernize and simplify CI steps (#11738)

* Use `build` instead of `python setup.py sdist`
* Remove in-place build with `setup.py`
* Remove `gpu` parameter and GPU tests
* Keep `architecture` and `num_build_jobs` in azure steps with CI
  defaults
* Fix use of `num_build_jobs` parameters
* Remove now-unused `prefix` parameter
* Test imports and CLI before installing test requirements
  * Remove `*.egg-info` directory in addition to source directory for an
    warning-free `import spacy`
* Switch `thinc-apple-ops` test to python 3.11 (as most recent python
  that is tested across platforms)
---
 .github/azure-steps.yml | 70 +++++++++++++++++++----------------------
 azure-pipelines.yml     | 17 ----------
 2 files changed, 33 insertions(+), 54 deletions(-)

diff --git a/.github/azure-steps.yml b/.github/azure-steps.yml
index cc0247b3a..b2bc80dd6 100644
--- a/.github/azure-steps.yml
+++ b/.github/azure-steps.yml
@@ -1,9 +1,7 @@
 parameters:
   python_version: ''
-  architecture: ''
-  prefix: ''
-  gpu: false
-  num_build_jobs: 1
+  architecture: 'x64'
+  num_build_jobs: 2
 
 steps:
   - task: UsePythonVersion@0
@@ -17,16 +15,16 @@ steps:
     displayName: 'Set variables'
 
   - script: |
-      ${{ parameters.prefix }} python -m pip install -U pip setuptools
-      ${{ parameters.prefix }} python -m pip install -U -r requirements.txt
+      python -m pip install -U build pip setuptools
+      python -m pip install -U -r requirements.txt
     displayName: "Install dependencies"
 
   - script: |
-      ${{ parameters.prefix }} python setup.py build_ext --inplace -j ${{ parameters.num_build_jobs }}
-      ${{ parameters.prefix }} python setup.py sdist --formats=gztar
-    displayName: "Compile and build sdist"
+      python -m build --sdist
+    displayName: "Build sdist"
 
-  - script: python -m mypy spacy
+  - script: |
+      python -m mypy spacy
     displayName: 'Run mypy'
     condition: ne(variables['python_version'], '3.6')
 
@@ -35,35 +33,24 @@ steps:
       contents: "spacy"
     displayName: "Delete source directory"
 
+  - task: DeleteFiles@1
+    inputs:
+      contents: "*.egg-info"
+    displayName: "Delete egg-info directory"
+
   - script: |
-      ${{ parameters.prefix }} python -m pip freeze --exclude torch --exclude cupy-cuda110 > installed.txt
-      ${{ parameters.prefix }} python -m pip uninstall -y -r installed.txt
+      python -m pip freeze > installed.txt
+      python -m pip uninstall -y -r installed.txt
     displayName: "Uninstall all packages"
 
   - bash: |
-      ${{ parameters.prefix }} SDIST=$(python -c "import os;print(os.listdir('./dist')[-1])" 2>&1)
-      ${{ parameters.prefix }} SPACY_NUM_BUILD_JOBS=2 python -m pip install dist/$SDIST
+      SDIST=$(python -c "import os;print(os.listdir('./dist')[-1])" 2>&1)
+      SPACY_NUM_BUILD_JOBS=${{ parameters.num_build_jobs }} python -m pip install dist/$SDIST
     displayName: "Install from sdist"
 
   - script: |
-      ${{ parameters.prefix }} python -m pip install -U -r requirements.txt
-    displayName: "Install test requirements"
-
-  - script: |
-      ${{ parameters.prefix }} python -m pip install -U cupy-cuda110 -f https://github.com/cupy/cupy/releases/v9.0.0
-      ${{ parameters.prefix }} python -m pip install "torch==1.7.1+cu110" -f https://download.pytorch.org/whl/torch_stable.html
-    displayName: "Install GPU requirements"
-    condition: eq(${{ parameters.gpu }}, true)
-
-  - script: |
-      ${{ parameters.prefix }} python -m pytest --pyargs spacy -W error
-    displayName: "Run CPU tests"
-    condition: eq(${{ parameters.gpu }}, false)
-
-  - script: |
-      ${{ parameters.prefix }} python -m pytest --pyargs spacy -W error -p spacy.tests.enable_gpu
-    displayName: "Run GPU tests"
-    condition: eq(${{ parameters.gpu }}, true)
+      python -W error -c "import spacy"
+    displayName: "Test import"
 
   - script: |
       python -m spacy download ca_core_news_sm
@@ -106,13 +93,22 @@ steps:
     displayName: 'Test assemble CLI vectors warning'
     condition: eq(variables['python_version'], '3.8')
 
+  - script: |
+      python -m pip install -U -r requirements.txt
+    displayName: "Install test requirements"
+
+  - script: |
+      python -m pytest --pyargs spacy -W error
+    displayName: "Run CPU tests"
+
+  - script: |
+      python -m pip install --pre thinc-apple-ops
+      python -m pytest --pyargs spacy
+    displayName: "Run CPU tests with thinc-apple-ops"
+    condition: and(startsWith(variables['imageName'], 'macos'), eq(variables['python.version'], '3.11'))
+
   - script: |
       python .github/validate_universe_json.py website/meta/universe.json
     displayName: 'Test website/meta/universe.json'
     condition: eq(variables['python_version'], '3.8')
 
-  - script: |
-      ${{ parameters.prefix }} python -m pip install --pre thinc-apple-ops
-      ${{ parameters.prefix }} python -m pytest --pyargs spacy
-    displayName: "Run CPU tests with thinc-apple-ops"
-    condition: and(startsWith(variables['imageName'], 'macos'), eq(variables['python.version'], '3.10'))
diff --git a/azure-pipelines.yml b/azure-pipelines.yml
index bf3672b8b..3499042cb 100644
--- a/azure-pipelines.yml
+++ b/azure-pipelines.yml
@@ -101,20 +101,3 @@ jobs:
       - template: .github/azure-steps.yml
         parameters:
           python_version: '$(python.version)'
-          architecture: 'x64'
-
-#  - job: "TestGPU"
-#    dependsOn: "Validate"
-#    strategy:
-#      matrix:
-#        Python38LinuxX64_GPU:
-#          python.version: '3.8'
-#    pool:
-#      name: "LinuxX64_GPU"
-#    steps:
-#      - template: .github/azure-steps.yml
-#        parameters:
-#          python_version: '$(python.version)'
-#          architecture: 'x64'
-#          gpu: true
-#          num_build_jobs: 24

From db56600536e2d615a766fc2fc973a6cc9e0f1a52 Mon Sep 17 00:00:00 2001
From: Paul O'Leary McCann <polm@dampfkraft.com>
Date: Thu, 3 Nov 2022 18:52:59 +0900
Subject: [PATCH 146/174] Fix default parameters for load functions (fix
 #11706) (#11713)

* Fix default parameters for load functions

Some load functions used SimpleFrozenList() directly instead of the
_DEFAULT_EMPTY_PIPES parameter. That mostly worked as intended, but
the changes in #11459 check for equality using identity, not value, so a
warning is incorrectly raised sometimes, as in #11706.

This change just has all the load functions use the singleton value
instead.

* Add test that there are no warnings on module-based load

This will succeed due to changes in this branch, but local tests with
the latest release failed as intended.

* Try reverting commit and see if CI changes

There is an error in CI that is probably unrelated.

Revert "Fix default parameters for load functions"

This reverts commit dc46b35687e92e4793e64edb11997d44b88c6a8b.

* Revert "Try reverting commit and see if CI changes"

This reverts commit 2514ed07ef29851b5ac60015442a7ce44c69decc.

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
---
 .github/azure-steps.yml |  5 +++++
 spacy/util.py           | 12 ++++++------
 2 files changed, 11 insertions(+), 6 deletions(-)

diff --git a/.github/azure-steps.yml b/.github/azure-steps.yml
index b2bc80dd6..e8bd0d212 100644
--- a/.github/azure-steps.yml
+++ b/.github/azure-steps.yml
@@ -59,6 +59,11 @@ steps:
     displayName: 'Test download CLI'
     condition: eq(variables['python_version'], '3.8')
 
+  - script: |
+      python -W error -c "import ca_core_news_sm; nlp = ca_core_news_sm.load(); doc=nlp('test')"
+    displayName: 'Test no warnings on load (#11713)'
+    condition: eq(variables['python_version'], '3.8')
+
   - script: |
       python -m spacy convert extra/example_data/ner_example_data/ner-token-per-line-conll2003.json .
     displayName: 'Test convert CLI'
diff --git a/spacy/util.py b/spacy/util.py
index 3034808ba..76a1e0bfa 100644
--- a/spacy/util.py
+++ b/spacy/util.py
@@ -443,9 +443,9 @@ def load_model_from_package(
     name: str,
     *,
     vocab: Union["Vocab", bool] = True,
-    disable: Union[str, Iterable[str]] = SimpleFrozenList(),
-    enable: Union[str, Iterable[str]] = SimpleFrozenList(),
-    exclude: Union[str, Iterable[str]] = SimpleFrozenList(),
+    disable: Union[str, Iterable[str]] = _DEFAULT_EMPTY_PIPES,
+    enable: Union[str, Iterable[str]] = _DEFAULT_EMPTY_PIPES,
+    exclude: Union[str, Iterable[str]] = _DEFAULT_EMPTY_PIPES,
     config: Union[Dict[str, Any], Config] = SimpleFrozenDict(),
 ) -> "Language":
     """Load a model from an installed package.
@@ -619,9 +619,9 @@ def load_model_from_init_py(
     init_file: Union[Path, str],
     *,
     vocab: Union["Vocab", bool] = True,
-    disable: Union[str, Iterable[str]] = SimpleFrozenList(),
-    enable: Union[str, Iterable[str]] = SimpleFrozenList(),
-    exclude: Union[str, Iterable[str]] = SimpleFrozenList(),
+    disable: Union[str, Iterable[str]] = _DEFAULT_EMPTY_PIPES,
+    enable: Union[str, Iterable[str]] = _DEFAULT_EMPTY_PIPES,
+    exclude: Union[str, Iterable[str]] = _DEFAULT_EMPTY_PIPES,
     config: Union[Dict[str, Any], Config] = SimpleFrozenDict(),
 ) -> "Language":
     """Helper function to use in the `load()` method of a model package's

From 40e1000db08858e8c928efacab8f710e027dde61 Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Thu, 3 Nov 2022 11:49:08 +0100
Subject: [PATCH 147/174] Restore Doc attr getter values in Doc.to_json
 (#11700)

---
 spacy/tests/doc/test_json_doc_conversion.py |  9 +++++++
 spacy/tokens/doc.pyx                        | 27 ++++++++++++++-------
 2 files changed, 27 insertions(+), 9 deletions(-)

diff --git a/spacy/tests/doc/test_json_doc_conversion.py b/spacy/tests/doc/test_json_doc_conversion.py
index 19698cfb2..11a1817e6 100644
--- a/spacy/tests/doc/test_json_doc_conversion.py
+++ b/spacy/tests/doc/test_json_doc_conversion.py
@@ -370,3 +370,12 @@ def test_json_to_doc_validation_error(doc):
     doc_json.pop("tokens")
     with pytest.raises(ValueError):
         Doc(doc.vocab).from_json(doc_json, validate=True)
+
+
+def test_to_json_underscore_doc_getters(doc):
+    def get_text_length(doc):
+        return len(doc.text)
+
+    Doc.set_extension("text_length", getter=get_text_length)
+    doc_json = doc.to_json(underscore=["text_length"])
+    assert doc_json["_"]["text_length"] == get_text_length(doc)
diff --git a/spacy/tokens/doc.pyx b/spacy/tokens/doc.pyx
index 295f91c28..f2621292c 100644
--- a/spacy/tokens/doc.pyx
+++ b/spacy/tokens/doc.pyx
@@ -1668,6 +1668,20 @@ cdef class Doc:
 
         if underscore:
             user_keys = set()
+            # Handle doc attributes with .get to include values from getters
+            # and not only values stored in user_data, for backwards
+            # compatibility
+            for attr in underscore:
+                if self.has_extension(attr):
+                    if "_" not in data:
+                        data["_"] = {}
+                    value = self._.get(attr)
+                    if not srsly.is_json_serializable(value):
+                        raise ValueError(Errors.E107.format(attr=attr, value=repr(value)))
+                    data["_"][attr] = value
+                    user_keys.add(attr)
+            # Token and span attributes only include values stored in user_data
+            # and not values generated by getters
             if self.user_data:
                 for data_key, value in self.user_data.copy().items():
                     if type(data_key) == tuple and len(data_key) >= 4 and data_key[0] == "._.":
@@ -1678,20 +1692,15 @@ cdef class Doc:
                             user_keys.add(attr)
                             if not srsly.is_json_serializable(value):
                                 raise ValueError(Errors.E107.format(attr=attr, value=repr(value)))
-                            # Check if doc attribute
-                            if start is None:
-                                if "_" not in data:
-                                    data["_"] = {}
-                                data["_"][attr] = value
-                            # Check if token attribute
-                            elif end is None:
+                            # Token attribute
+                            if start is not None and end is None:
                                 if "underscore_token" not in data:
                                     data["underscore_token"] = {}
                                 if attr not in data["underscore_token"]:
                                     data["underscore_token"][attr] = []
                                 data["underscore_token"][attr].append({"start": start, "value": value})
-                            # Else span attribute
-                            else:
+                            # Span attribute
+                            elif start is not None and end is not None:
                                 if "underscore_span" not in data:
                                     data["underscore_span"] = {}
                                 if attr not in data["underscore_span"]:

From bbf64cfc4391cccba447346badaacca4d42e583d Mon Sep 17 00:00:00 2001
From: "github-actions[bot]"
 <41898282+github-actions[bot]@users.noreply.github.com>
Date: Fri, 4 Nov 2022 11:17:43 +0100
Subject: [PATCH 148/174] Auto-format code with black (#11749)

Co-authored-by: explosion-bot <explosion-bot@users.noreply.github.com>
---
 spacy/pipeline/textcat.py | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/spacy/pipeline/textcat.py b/spacy/pipeline/textcat.py
index 238a768ed..4023c4456 100644
--- a/spacy/pipeline/textcat.py
+++ b/spacy/pipeline/textcat.py
@@ -155,7 +155,11 @@ class TextCategorizer(TrainablePipe):
         self.model = model
         self.name = name
         self._rehearsal_model = None
-        cfg: Dict[str, Any] = {"labels": [], "threshold": threshold, "positive_label": None}
+        cfg: Dict[str, Any] = {
+            "labels": [],
+            "threshold": threshold,
+            "positive_label": None,
+        }
         self.cfg = dict(cfg)
         self.scorer = scorer
 

From ea326cf47d5324cff14bef983b0da122b9f0d1ed Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Mon, 7 Nov 2022 08:11:13 +0100
Subject: [PATCH 149/174] Fix types for Span.id and Span.id_ (#11744)

---
 spacy/tokens/span.pyi | 6 ++----
 1 file changed, 2 insertions(+), 4 deletions(-)

diff --git a/spacy/tokens/span.pyi b/spacy/tokens/span.pyi
index 617e3d19d..0a6f306a6 100644
--- a/spacy/tokens/span.pyi
+++ b/spacy/tokens/span.pyi
@@ -117,15 +117,13 @@ class Span:
     end_char: int
     label: int
     kb_id: int
+    id: int
     ent_id: int
     ent_id_: str
     @property
-    def id(self) -> int: ...
-    @property
-    def id_(self) -> str: ...
-    @property
     def orth_(self) -> str: ...
     @property
     def lemma_(self) -> str: ...
     label_: str
     kb_id_: str
+    id_: str

From b76222e56adb49e33d7d0471674dfe2f207b2020 Mon Sep 17 00:00:00 2001
From: Paul O'Leary McCann <polm@dampfkraft.com>
Date: Mon, 7 Nov 2022 16:11:55 +0900
Subject: [PATCH 150/174] Raise Typer limit (#11720)

* Raise typer limit to <0.7.0

* Raise limit to <0.8.0
---
 requirements.txt | 2 +-
 setup.cfg        | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/requirements.txt b/requirements.txt
index 9d6bbb2c4..d91a3b3d4 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -9,7 +9,7 @@ murmurhash>=0.28.0,<1.1.0
 wasabi>=0.9.1,<1.1.0
 srsly>=2.4.3,<3.0.0
 catalogue>=2.0.6,<2.1.0
-typer>=0.3.0,<0.5.0
+typer>=0.3.0,<0.8.0
 pathy>=0.3.5
 # Third party dependencies
 numpy>=1.15.0
diff --git a/setup.cfg b/setup.cfg
index c2653feba..82d4d2758 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -51,7 +51,7 @@ install_requires =
     srsly>=2.4.3,<3.0.0
     catalogue>=2.0.6,<2.1.0
     # Third-party dependencies
-    typer>=0.3.0,<0.5.0
+    typer>=0.3.0,<0.8.0
     pathy>=0.3.5
     tqdm>=4.38.0,<5.0.0
     numpy>=1.15.0

From e91b47a22655c0384202f797e9d50d3660596d32 Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Mon, 7 Nov 2022 10:43:34 +0100
Subject: [PATCH 151/174] Check for unsafe paths in tarfile.extractall
 (CVE-2007-4559) (#11746)

* Adding tarfile member sanitization to extractall()

* Format

* Simplify and add error message

* Fix import

* Add comment about CVE

Co-authored-by: TrellixVulnTeam <charles.mcfarland@trellix.com>
---
 spacy/cli/project/remote_storage.py | 19 ++++++++++++++++++-
 spacy/errors.py                     |  2 ++
 2 files changed, 20 insertions(+), 1 deletion(-)

diff --git a/spacy/cli/project/remote_storage.py b/spacy/cli/project/remote_storage.py
index 336a4bcb3..12e252b3c 100644
--- a/spacy/cli/project/remote_storage.py
+++ b/spacy/cli/project/remote_storage.py
@@ -10,6 +10,7 @@ from .._util import get_hash, get_checksum, download_file, ensure_pathy
 from ...util import make_tempdir, get_minor_version, ENV_VARS, check_bool_env_var
 from ...git_info import GIT_VERSION
 from ... import about
+from ...errors import Errors
 
 if TYPE_CHECKING:
     from pathy import Pathy  # noqa: F401
@@ -84,7 +85,23 @@ class RemoteStorage:
                 with tarfile.open(tar_loc, mode=mode_string) as tar_file:
                     # This requires that the path is added correctly, relative
                     # to root. This is how we set things up in push()
-                    tar_file.extractall(self.root)
+
+                    # Disallow paths outside the current directory for the tar
+                    # file (CVE-2007-4559, directory traversal vulnerability)
+                    def is_within_directory(directory, target):
+                        abs_directory = os.path.abspath(directory)
+                        abs_target = os.path.abspath(target)
+                        prefix = os.path.commonprefix([abs_directory, abs_target])
+                        return prefix == abs_directory
+
+                    def safe_extract(tar, path):
+                        for member in tar.getmembers():
+                            member_path = os.path.join(path, member.name)
+                            if not is_within_directory(path, member_path):
+                                raise ValueError(Errors.E852)
+                        tar.extractall(path)
+
+                    safe_extract(tar_file, self.root)
         return url
 
     def find(
diff --git a/spacy/errors.py b/spacy/errors.py
index e0628819d..2f8a3996f 100644
--- a/spacy/errors.py
+++ b/spacy/errors.py
@@ -544,6 +544,8 @@ class Errors(metaclass=ErrorsWithCodes):
             "during training, make sure to include it in 'annotating components'")
 
     # New errors added in v3.x
+    E852 = ("The tar file pulled from the remote attempted an unsafe path "
+            "traversal.")
     E853 = ("Unsupported component factory name '{name}'. The character '.' is "
             "not permitted in factory names.")
     E854 = ("Unable to set doc.ents. Check that the 'ents_filter' does not "

From 6105f20d8a10a18a0e5985d310664812198840a8 Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Mon, 7 Nov 2022 13:25:40 +0100
Subject: [PATCH 152/174] Switch CI to python 3.11 (#11765)

---
 azure-pipelines.yml | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/azure-pipelines.yml b/azure-pipelines.yml
index 3499042cb..9c3b92f06 100644
--- a/azure-pipelines.yml
+++ b/azure-pipelines.yml
@@ -87,13 +87,13 @@ jobs:
         #          python.version: "3.10"
         Python311Linux:
           imageName: 'ubuntu-latest'
-          python.version: '3.11.0'
+          python.version: '3.11'
         Python311Windows:
           imageName: 'windows-latest'
-          python.version: '3.11.0'
+          python.version: '3.11'
         Python311Mac:
           imageName: 'macos-latest'
-          python.version: '3.11.0'
+          python.version: '3.11'
       maxParallel: 4
     pool:
       vmImage: $(imageName)

From e116395f890a70447c75109026e7b37f20c142c2 Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Mon, 7 Nov 2022 14:46:08 +0100
Subject: [PATCH 153/174] Add fallback in requirements check, only check once
 (#11735)

* Add fallback in requirements check, only check once

* Rename to skip_requirements_check

* Update spacy/cli/project/run.py

Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com>

Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com>
---
 spacy/cli/project/run.py | 15 ++++++++++++---
 1 file changed, 12 insertions(+), 3 deletions(-)

diff --git a/spacy/cli/project/run.py b/spacy/cli/project/run.py
index ebab7471e..638e7fab1 100644
--- a/spacy/cli/project/run.py
+++ b/spacy/cli/project/run.py
@@ -53,6 +53,7 @@ def project_run(
     force: bool = False,
     dry: bool = False,
     capture: bool = False,
+    skip_requirements_check: bool = False,
 ) -> None:
     """Run a named script defined in the project.yml. If the script is part
     of the default pipeline (defined in the "run" section), DVC is used to
@@ -69,6 +70,7 @@ def project_run(
         sys.exit will be called with the return code. You should use capture=False
         when you want to turn over execution to the command, and capture=True
         when you want to run the command more like a function.
+    skip_requirements_check (bool): Whether to skip the requirements check.
     """
     config = load_project_config(project_dir, overrides=overrides)
     commands = {cmd["name"]: cmd for cmd in config.get("commands", [])}
@@ -76,9 +78,10 @@ def project_run(
     validate_subcommand(list(commands.keys()), list(workflows.keys()), subcommand)
 
     req_path = project_dir / "requirements.txt"
-    if config.get("check_requirements", True) and os.path.exists(req_path):
-        with req_path.open() as requirements_file:
-            _check_requirements([req.replace("\n", "") for req in requirements_file])
+    if not skip_requirements_check:
+        if config.get("check_requirements", True) and os.path.exists(req_path):
+            with req_path.open() as requirements_file:
+                _check_requirements([req.strip() for req in requirements_file])
 
     if subcommand in workflows:
         msg.info(f"Running workflow '{subcommand}'")
@@ -90,6 +93,7 @@ def project_run(
                 force=force,
                 dry=dry,
                 capture=capture,
+                skip_requirements_check=True,
             )
     else:
         cmd = commands[subcommand]
@@ -338,6 +342,11 @@ def _check_requirements(requirements: List[str]) -> Tuple[bool, bool]:
             failed_pkgs_msgs.append(dnf.report())
         except pkg_resources.VersionConflict as vc:
             conflicting_pkgs_msgs.append(vc.report())
+        except Exception:
+            msg.warn(f"Unable to check requirement: {req} "
+                     "Check that the requirement is formatted according to PEP "
+                     "440, in particular that URLs are formatted as "
+                     "'package_name @ URL'")
 
     if len(failed_pkgs_msgs) or len(conflicting_pkgs_msgs):
         msg.warn(

From 2e3cfd758ea414497802843970666a18ed4d123e Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Tue, 8 Nov 2022 04:46:19 +0100
Subject: [PATCH 154/174] Use python 3.10 for GHA universe alert (#11768)

---
 .github/workflows/spacy_universe_alert.yml | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/.github/workflows/spacy_universe_alert.yml b/.github/workflows/spacy_universe_alert.yml
index f507e0594..837aaeb33 100644
--- a/.github/workflows/spacy_universe_alert.yml
+++ b/.github/workflows/spacy_universe_alert.yml
@@ -19,6 +19,8 @@ jobs:
 
       - uses: actions/checkout@v3
       - uses: actions/setup-python@v4
+        with:
+          python-version: '3.10'
       - name: Install Bernadette app dependency and send an alert
         env:
           SLACK_BOT_TOKEN: ${{ secrets.SLACK_BOT_TOKEN }}

From 20bbbe3e44f14d42a4861d1399ad98d6e1707d84 Mon Sep 17 00:00:00 2001
From: Raphael Mitsch <r.mitsch@outlook.com>
Date: Tue, 8 Nov 2022 14:58:10 +0100
Subject: [PATCH 155/174] Revert disable/disabled merging behavior (#11745)

* Merge disable with disabled. Adjust warnings, errors and tests.

* Replace any() with set operation.

* Update spacy/tests/pipeline/test_pipe_methods.py

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

* Update docs.

* Remve reference to config entry nlp.enabled from docs.

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
---
 spacy/errors.py                               |  4 +-
 spacy/language.py                             | 45 ++++++++-----------
 spacy/tests/pipeline/test_pipe_methods.py     | 18 ++++----
 .../serialize/test_serialize_pipeline.py      |  7 ++-
 website/docs/api/language.md                  | 24 +++++-----
 website/docs/api/top-level.md                 | 20 ++++-----
 website/docs/usage/processing-pipelines.md    |  3 +-
 7 files changed, 56 insertions(+), 65 deletions(-)

diff --git a/spacy/errors.py b/spacy/errors.py
index 2f8a3996f..278e5496a 100644
--- a/spacy/errors.py
+++ b/spacy/errors.py
@@ -212,8 +212,8 @@ class Warnings(metaclass=ErrorsWithCodes):
     W121 = ("Attempting to trace non-existent method '{method}' in pipe '{pipe}'")
     W122 = ("Couldn't trace method '{method}' in pipe '{pipe}'. This can happen if the pipe class "
             "is a Cython extension type.")
-    W123 = ("Argument {arg} with value {arg_value} is used instead of {config_value} as specified in the config. Be "
-            "aware that this might affect other components in your pipeline.")
+    W123 = ("Argument `enable` with value {enable} does not contain all values specified in the config option "
+            "`enabled` ({enabled}). Be aware that this might affect other components in your pipeline.")
 
 
 class Errors(metaclass=ErrorsWithCodes):
diff --git a/spacy/language.py b/spacy/language.py
index d391f15ab..967af1e62 100644
--- a/spacy/language.py
+++ b/spacy/language.py
@@ -1879,31 +1879,22 @@ class Language:
         if isinstance(exclude, str):
             exclude = [exclude]
 
-        def fetch_pipes_status(value: Iterable[str], key: str) -> Iterable[str]:
-            """Fetch value for `enable` or `disable` w.r.t. the specified config and passed arguments passed to
-            .load(). If both arguments and config specified values for this field, the passed arguments take precedence
-            and a warning is printed.
-            value (Iterable[str]): Passed value for `enable` or `disable`.
-            key (str): Key for field in config (either "enabled" or "disabled").
-            RETURN (Iterable[str]):
-            """
-            # We assume that no argument was passed if the value is the specified default value.
-            if id(value) == id(_DEFAULT_EMPTY_PIPES):
-                return config["nlp"].get(key, [])
-            else:
-                if len(config["nlp"].get(key, [])):
-                    warnings.warn(
-                        Warnings.W123.format(
-                            arg=key[:-1],
-                            arg_value=value,
-                            config_value=config["nlp"][key],
-                        )
+        # `enable` should not be merged with `enabled` (the opposite is true for `disable`/`disabled`). If the config
+        # specifies values for `enabled` not included in `enable`, emit warning.
+        if id(enable) != id(_DEFAULT_EMPTY_PIPES):
+            enabled = config["nlp"].get("enabled", [])
+            if len(enabled) and not set(enabled).issubset(enable):
+                warnings.warn(
+                    Warnings.W123.format(
+                        enable=enable,
+                        enabled=enabled,
                     )
-                return value
+                )
 
+        # Ensure sets of disabled/enabled pipe names are not contradictory.
         disabled_pipes = cls._resolve_component_status(
-            fetch_pipes_status(disable, "disabled"),
-            fetch_pipes_status(enable, "enabled"),
+            list({*disable, *config["nlp"].get("disabled", [])}),
+            enable,
             config["nlp"]["pipeline"],
         )
         nlp._disabled = set(p for p in disabled_pipes if p not in exclude)
@@ -2084,10 +2075,12 @@ class Language:
         if enable:
             if isinstance(enable, str):
                 enable = [enable]
-            to_disable = [
-                pipe_name for pipe_name in pipe_names if pipe_name not in enable
-            ]
-            if disable and disable != to_disable:
+            to_disable = {
+                *[pipe_name for pipe_name in pipe_names if pipe_name not in enable],
+                *disable,
+            }
+            # If any pipe to be enabled is in to_disable, the specification is inconsistent.
+            if len(set(enable) & to_disable):
                 raise ValueError(Errors.E1042.format(enable=enable, disable=disable))
 
         return tuple(to_disable)
diff --git a/spacy/tests/pipeline/test_pipe_methods.py b/spacy/tests/pipeline/test_pipe_methods.py
index 14a7a36e5..4dd7bae16 100644
--- a/spacy/tests/pipeline/test_pipe_methods.py
+++ b/spacy/tests/pipeline/test_pipe_methods.py
@@ -615,20 +615,18 @@ def test_enable_disable_conflict_with_config():
 
     with make_tempdir() as tmp_dir:
         nlp.to_disk(tmp_dir)
-        # Expected to fail, as config and arguments conflict.
-        with pytest.raises(ValueError):
-            spacy.load(
-                tmp_dir, enable=["tagger"], config={"nlp": {"disabled": ["senter"]}}
-            )
+        # Expected to succeed, as config and arguments do not conflict.
+        assert spacy.load(
+            tmp_dir, enable=["tagger"], config={"nlp": {"disabled": ["senter"]}}
+        ).disabled == ["senter", "sentencizer"]
         # Expected to succeed without warning due to the lack of a conflicting config option.
         spacy.load(tmp_dir, enable=["tagger"])
-        # Expected to succeed with a warning, as disable=[] should override the config setting.
-        with pytest.warns(UserWarning):
+        # Expected to fail due to conflict between enable and disabled.
+        with pytest.raises(ValueError):
             spacy.load(
                 tmp_dir,
-                enable=["tagger"],
-                disable=[],
-                config={"nlp": {"disabled": ["senter"]}},
+                enable=["senter"],
+                config={"nlp": {"disabled": ["senter", "tagger"]}},
             )
 
 
diff --git a/spacy/tests/serialize/test_serialize_pipeline.py b/spacy/tests/serialize/test_serialize_pipeline.py
index b948bb76c..9fcf18e2d 100644
--- a/spacy/tests/serialize/test_serialize_pipeline.py
+++ b/spacy/tests/serialize/test_serialize_pipeline.py
@@ -404,11 +404,10 @@ def test_serialize_pipeline_disable_enable():
     assert nlp3.component_names == ["ner", "tagger"]
     with make_tempdir() as d:
         nlp3.to_disk(d)
-        with pytest.warns(UserWarning):
-            nlp4 = spacy.load(d, disable=["ner"])
-    assert nlp4.pipe_names == ["tagger"]
+        nlp4 = spacy.load(d, disable=["ner"])
+    assert nlp4.pipe_names == []
     assert nlp4.component_names == ["ner", "tagger"]
-    assert nlp4.disabled == ["ner"]
+    assert nlp4.disabled == ["ner", "tagger"]
     with make_tempdir() as d:
         nlp.to_disk(d)
         nlp5 = spacy.load(d, exclude=["tagger"])
diff --git a/website/docs/api/language.md b/website/docs/api/language.md
index 767a7450a..504640d57 100644
--- a/website/docs/api/language.md
+++ b/website/docs/api/language.md
@@ -63,18 +63,18 @@ spaCy loads a model under the hood based on its
 > nlp = Language.from_config(config)
 > ```
 
-| Name                                  | Description                                                                                                                                                                                                                                                          |
-| ------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `config`                              | The loaded config. ~~Union[Dict[str, Any], Config]~~                                                                                                                                                                                                                 |
-| _keyword-only_                        |                                                                                                                                                                                                                                                                      |
-| `vocab`                               | A `Vocab` object. If `True`, a vocab is created using the default language data settings. ~~Vocab~~                                                                                                                                                                  |
-| `disable`                             | Name(s) of pipeline component(s) to [disable](/usage/processing-pipelines#disabling). Disabled pipes will be loaded but they won't be run unless you explicitly enable them by calling [`nlp.enable_pipe`](/api/language#enable_pipe). ~~Union[str, Iterable[str]]~~ |
-| `enable` <Tag variant="new">3.4</Tag> | Name(s) of pipeline component(s) to [enable](/usage/processing-pipelines#disabling). All other pipes will be disabled, but can be enabled again using [`nlp.enable_pipe`](/api/language#enable_pipe). ~~Union[str, Iterable[str]]~~                                  |
-| `exclude`                             | Name(s) of pipeline component(s) to [exclude](/usage/processing-pipelines#disabling). Excluded components won't be loaded. ~~Union[str, Iterable[str]]~~                                                                                                             |
-| `meta`                                | [Meta data](/api/data-formats#meta) overrides. ~~Dict[str, Any]~~                                                                                                                                                                                                    |
-| `auto_fill`                           | Whether to automatically fill in missing values in the config, based on defaults and function argument annotations. Defaults to `True`. ~~bool~~                                                                                                                     |
-| `validate`                            | Whether to validate the component config and arguments against the types expected by the factory. Defaults to `True`. ~~bool~~                                                                                                                                       |
-| **RETURNS**                           | The initialized object. ~~Language~~                                                                                                                                                                                                                                 |
+| Name                                  | Description                                                                                                                                                                                                                                                                                                      |
+| ------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `config`                              | The loaded config. ~~Union[Dict[str, Any], Config]~~                                                                                                                                                                                                                                                             |
+| _keyword-only_                        |                                                                                                                                                                                                                                                                                                                  |
+| `vocab`                               | A `Vocab` object. If `True`, a vocab is created using the default language data settings. ~~Vocab~~                                                                                                                                                                                                              |
+| `disable`                             | Name(s) of pipeline component(s) to [disable](/usage/processing-pipelines#disabling). Disabled pipes will be loaded but they won't be run unless you explicitly enable them by calling [nlp.enable_pipe](/api/language#enable_pipe). Is merged with the config entry `nlp.disabled`. ~~Union[str, Iterable[str]]~~ |
+| `enable` <Tag variant="new">3.4</Tag> | Name(s) of pipeline component(s) to [enable](/usage/processing-pipelines#disabling). All other pipes will be disabled, but can be enabled again using [nlp.enable_pipe](/api/language#enable_pipe). ~~Union[str, Iterable[str]]~~                                       |
+| `exclude`                             | Name(s) of pipeline component(s) to [exclude](/usage/processing-pipelines#disabling). Excluded components won't be loaded. ~~Union[str, Iterable[str]]~~                                                                                                                                                         |
+| `meta`                                | [Meta data](/api/data-formats#meta) overrides. ~~Dict[str, Any]~~                                                                                                                                                                                                                                                |
+| `auto_fill`                           | Whether to automatically fill in missing values in the config, based on defaults and function argument annotations. Defaults to `True`. ~~bool~~                                                                                                                                                                 |
+| `validate`                            | Whether to validate the component config and arguments against the types expected by the factory. Defaults to `True`. ~~bool~~                                                                                                                                                                                   |
+| **RETURNS**                           | The initialized object. ~~Language~~                                                                                                                                                                                                                                                                             |
 
 ## Language.component {#component tag="classmethod" new="3"}
 
diff --git a/website/docs/api/top-level.md b/website/docs/api/top-level.md
index bc53fc868..c798f2a8d 100644
--- a/website/docs/api/top-level.md
+++ b/website/docs/api/top-level.md
@@ -45,16 +45,16 @@ specified separately using the new `exclude` keyword argument.
 > nlp = spacy.load("en_core_web_sm", exclude=["parser", "tagger"])
 > ```
 
-| Name                                  | Description                                                                                                                                                                                                                                                        |
-| ------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
-| `name`                                | Pipeline to load, i.e. package name or path. ~~Union[str, Path]~~                                                                                                                                                                                                  |
-| _keyword-only_                        |                                                                                                                                                                                                                                                                    |
-| `vocab`                               | Optional shared vocab to pass in on initialization. If `True` (default), a new `Vocab` object will be created. ~~Union[Vocab, bool]~~                                                                                                                              |
-| `disable`                             | Name(s) of pipeline component(s) to [disable](/usage/processing-pipelines#disabling). Disabled pipes will be loaded but they won't be run unless you explicitly enable them by calling [nlp.enable_pipe](/api/language#enable_pipe). ~~Union[str, Iterable[str]]~~ |
-| `enable` <Tag variant="new">3.4</Tag> | Name(s) of pipeline component(s) to [enable](/usage/processing-pipelines#disabling). All other pipes will be disabled. ~~Union[str, Iterable[str]]~~                                                                                                               |
-| `exclude` <Tag variant="new">3</Tag>  | Name(s) of pipeline component(s) to [exclude](/usage/processing-pipelines#disabling). Excluded components won't be loaded. ~~Union[str, Iterable[str]]~~                                                                                                           |
-| `config` <Tag variant="new">3</Tag>   | Optional config overrides, either as nested dict or dict keyed by section value in dot notation, e.g. `"components.name.value"`. ~~Union[Dict[str, Any], Config]~~                                                                                                 |
-| **RETURNS**                           | A `Language` object with the loaded pipeline. ~~Language~~                                                                                                                                                                                                         |
+| Name                                  | Description                                                                                                                                                                                                                                                                                                      |
+| ------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `name`                                | Pipeline to load, i.e. package name or path. ~~Union[str, Path]~~                                                                                                                                                                                                                                                |
+| _keyword-only_                        |                                                                                                                                                                                                                                                                                                                  |
+| `vocab`                               | Optional shared vocab to pass in on initialization. If `True` (default), a new `Vocab` object will be created. ~~Union[Vocab, bool]~~                                                                                                                                                                            |
+| `disable`                             | Name(s) of pipeline component(s) to [disable](/usage/processing-pipelines#disabling). Disabled pipes will be loaded but they won't be run unless you explicitly enable them by calling [nlp.enable_pipe](/api/language#enable_pipe). Is merged with the config entry `nlp.disabled`. ~~Union[str, Iterable[str]]~~ |
+| `enable` <Tag variant="new">3.4</Tag> | Name(s) of pipeline component(s) to [enable](/usage/processing-pipelines#disabling). All other pipes will be disabled. ~~Union[str, Iterable[str]]~~                                                                                                                    |
+| `exclude` <Tag variant="new">3</Tag>  | Name(s) of pipeline component(s) to [exclude](/usage/processing-pipelines#disabling). Excluded components won't be loaded. ~~Union[str, Iterable[str]]~~                                                                                                                                                         |
+| `config` <Tag variant="new">3</Tag>   | Optional config overrides, either as nested dict or dict keyed by section value in dot notation, e.g. `"components.name.value"`. ~~Union[Dict[str, Any], Config]~~                                                                                                                                               |
+| **RETURNS**                           | A `Language` object with the loaded pipeline. ~~Language~~                                                                                                                                                                                                                                                       |
 
 Essentially, `spacy.load()` is a convenience wrapper that reads the pipeline's
 [`config.cfg`](/api/data-formats#config), uses the language and pipeline
diff --git a/website/docs/usage/processing-pipelines.md b/website/docs/usage/processing-pipelines.md
index bd28810ae..0b63cdcb8 100644
--- a/website/docs/usage/processing-pipelines.md
+++ b/website/docs/usage/processing-pipelines.md
@@ -363,7 +363,8 @@ nlp.enable_pipe("tagger")
 ```
 
 In addition to `disable`, `spacy.load()` also accepts `enable`. If `enable` is
-set, all components except for those in `enable` are disabled.
+set, all components except for those in `enable` are disabled. If `enable` and
+`disable` conflict (i.e. the same component is included in both), an error is raised.
 
 ```python
 # Load the complete pipeline, but disable all components except for tok2vec and tagger

From 03eebe9d1c79d39a632876205e93f023fc096d85 Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Wed, 9 Nov 2022 10:59:28 +0100
Subject: [PATCH 156/174] Update warning, add tests for project requirements
 check (#11777)

* Update warning, add tests for project requirements check

* Make warning more general for differences between PEP 508 and pip
* Add tests for _check_requirements

* Parameterize test
---
 spacy/cli/project/run.py |  5 ++---
 spacy/tests/test_cli.py  | 41 ++++++++++++++++++++++++++++++++++++++++
 2 files changed, 43 insertions(+), 3 deletions(-)

diff --git a/spacy/cli/project/run.py b/spacy/cli/project/run.py
index 638e7fab1..5db9e14f4 100644
--- a/spacy/cli/project/run.py
+++ b/spacy/cli/project/run.py
@@ -344,9 +344,8 @@ def _check_requirements(requirements: List[str]) -> Tuple[bool, bool]:
             conflicting_pkgs_msgs.append(vc.report())
         except Exception:
             msg.warn(f"Unable to check requirement: {req} "
-                     "Check that the requirement is formatted according to PEP "
-                     "440, in particular that URLs are formatted as "
-                     "'package_name @ URL'")
+                     "Checks are currently limited to requirement specifiers "
+                     "(PEP 508)")
 
     if len(failed_pkgs_msgs) or len(conflicting_pkgs_msgs):
         msg.warn(
diff --git a/spacy/tests/test_cli.py b/spacy/tests/test_cli.py
index 838e00369..8225e14f1 100644
--- a/spacy/tests/test_cli.py
+++ b/spacy/tests/test_cli.py
@@ -1,5 +1,6 @@
 import os
 import math
+import pkg_resources
 from random import sample
 from typing import Counter
 
@@ -25,6 +26,7 @@ from spacy.cli.download import get_compatibility, get_version
 from spacy.cli.init_config import RECOMMENDATIONS, init_config, fill_config
 from spacy.cli.package import get_third_party_dependencies
 from spacy.cli.package import _is_permitted_package_name
+from spacy.cli.project.run import _check_requirements
 from spacy.cli.validate import get_model_pkgs
 from spacy.lang.en import English
 from spacy.lang.nl import Dutch
@@ -855,3 +857,42 @@ def test_span_length_freq_dist_output_must_be_correct():
     span_freqs = _get_spans_length_freq_dist(sample_span_lengths, threshold)
     assert sum(span_freqs.values()) >= threshold
     assert list(span_freqs.keys()) == [3, 1, 4, 5, 2]
+
+
+@pytest.mark.parametrize(
+    "reqs,output",
+    [
+        [
+            """
+            spacy
+
+            # comment
+
+            thinc""",
+            (False, False),
+        ],
+        [
+            """# comment
+            --some-flag
+            spacy""",
+            (False, False),
+        ],
+        [
+            """# comment
+            --some-flag
+            spacy; python_version >= '3.6'""",
+            (False, False),
+        ],
+        [
+            """# comment
+             spacyunknowndoesnotexist12345""",
+            (True, False),
+        ],
+    ],
+)
+def test_project_check_requirements(reqs, output):
+    # excessive guard against unlikely package name
+    try:
+        pkg_resources.require("spacyunknowndoesnotexist12345")
+    except pkg_resources.DistributionNotFound:
+        assert output == _check_requirements([req.strip() for req in reqs.split("\n")])

From 322b5dc1df7031139780963cebaa081a75384834 Mon Sep 17 00:00:00 2001
From: Jacobo Myerston <43222279+jmyerston@users.noreply.github.com>
Date: Wed, 9 Nov 2022 20:21:20 -0800
Subject: [PATCH 157/174] Add greCy to Universe (#11774)

* Update universe.json

* Update universe.json

fixes Github value
---
 website/meta/universe.json | 26 ++++++++++++++++++++++++++
 1 file changed, 26 insertions(+)

diff --git a/website/meta/universe.json b/website/meta/universe.json
index d7c99956b..fa765f640 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -1,5 +1,31 @@
 {
     "resources": [
+         {
+            "id": "grecy",
+            "title": "greCy",
+            "slogan": "Ancient Greek pipelines for spaCy",
+            "description": "greCy offers state-of-the-art pipelines for ancient Greek NLP. The repository makes language models available in various sizes, some of them containing floret word vectors and a BERT transformer layer.",
+            "github": "jmyerston/greCy",
+            "code_example": [
+                "import spacy",
+                "#After installing the grc_ud_proiel_trf wheel package from the greCy repository",
+                "",
+                "nlp = spacy.load('grc_ud_proiel_trf')",
+                "doc = nlp('δοκῶ μοι περὶ ὧν πυνθάνεσθε οὐκ ἀμελέτητος εἶναι.')",
+                "",
+                "for token in doc:",
+                "   print(token.text, token.norm_, token.lemma_, token.pos_, token.tag_)"
+            ],
+            "code_language": "python",
+            "author": "Jacobo Myerston",
+            "author_links": {
+                "twitter": "@jcbmyrstn",
+                "github": "jmyerston",
+                "website": "https://huggingface.co/spaces/Jacobo/syntax"
+            },
+            "category": ["pipeline", "research"],
+            "tags": ["ancient Greek"]
+        },
         {
             "id": "spacy-cleaner",
             "title": "spacy-cleaner",

From 188a7d00eb552faaa70ba6ee3032757eecefbb5a Mon Sep 17 00:00:00 2001
From: "github-actions[bot]"
 <41898282+github-actions[bot]@users.noreply.github.com>
Date: Fri, 11 Nov 2022 09:58:31 +0100
Subject: [PATCH 158/174] Auto-format code with black (#11792)

Co-authored-by: explosion-bot <explosion-bot@users.noreply.github.com>
---
 spacy/cli/project/run.py | 8 +++++---
 1 file changed, 5 insertions(+), 3 deletions(-)

diff --git a/spacy/cli/project/run.py b/spacy/cli/project/run.py
index 5db9e14f4..a109c4a5a 100644
--- a/spacy/cli/project/run.py
+++ b/spacy/cli/project/run.py
@@ -343,9 +343,11 @@ def _check_requirements(requirements: List[str]) -> Tuple[bool, bool]:
         except pkg_resources.VersionConflict as vc:
             conflicting_pkgs_msgs.append(vc.report())
         except Exception:
-            msg.warn(f"Unable to check requirement: {req} "
-                     "Checks are currently limited to requirement specifiers "
-                     "(PEP 508)")
+            msg.warn(
+                f"Unable to check requirement: {req} "
+                "Checks are currently limited to requirement specifiers "
+                "(PEP 508)"
+            )
 
     if len(failed_pkgs_msgs) or len(conflicting_pkgs_msgs):
         msg.warn(

From 3478ff1eb0fd57c48a332e7787efe6ea47492e13 Mon Sep 17 00:00:00 2001
From: Edward <43848523+thomashacker@users.noreply.github.com>
Date: Mon, 14 Nov 2022 09:41:01 +0100
Subject: [PATCH 159/174] remove new v2 tags (#11780)

---
 website/README.md                         |   4 +-
 website/docs/api/cli.md                   |  81 ++++++------
 website/docs/api/doc.md                   |  50 ++++----
 website/docs/api/language.md              |  72 +++++------
 website/docs/api/lexeme.md                |  82 ++++++------
 website/docs/api/matcher.md               |  14 +--
 website/docs/api/phrasematcher.md         |  10 +-
 website/docs/api/span.md                  |  62 +++++-----
 website/docs/api/token.md                 | 144 +++++++++++-----------
 website/docs/api/top-level.md             |  52 ++++----
 website/docs/api/vocab.md                 |  22 ++--
 website/docs/usage/rule-based-matching.md |   6 +-
 website/docs/usage/saving-loading.md      |  12 +-
 13 files changed, 305 insertions(+), 306 deletions(-)

diff --git a/website/README.md b/website/README.md
index db050cf03..66bc20ad9 100644
--- a/website/README.md
+++ b/website/README.md
@@ -155,7 +155,7 @@ import Tag from 'components/tag'
 
 > ```jsx
 > <Tag>method</Tag>
-> <Tag variant="new">2.1</Tag>
+> <Tag variant="new">4</Tag>
 > <Tag variant="model">tagger, parser</Tag>
 > ```
 
@@ -170,7 +170,7 @@ installed.
 
 <InlineList>
 
-<Tag>method</Tag> <Tag variant="new">2</Tag> <Tag variant="model">tagger,
+<Tag>method</Tag> <Tag variant="new">4</Tag> <Tag variant="model">tagger,
 parser</Tag>
 
 </InlineList>
diff --git a/website/docs/api/cli.md b/website/docs/api/cli.md
index fc2c46022..024450920 100644
--- a/website/docs/api/cli.md
+++ b/website/docs/api/cli.md
@@ -53,7 +53,7 @@ $ python -m spacy download [model] [--direct] [--sdist] [pip_args]
 | `--direct`, `-D`                           | Force direct download of exact package version. ~~bool (flag)~~                                                                                                                                                                           |
 | `--sdist`, `-S` <Tag variant="new">3</Tag> | Download the source package (`.tar.gz` archive) instead of the default pre-built binary wheel. ~~bool (flag)~~                                                                                                                            |
 | `--help`, `-h`                             | Show help message and available arguments. ~~bool (flag)~~                                                                                                                                                                                |
-| pip args <Tag variant="new">2.1</Tag>      | Additional installation options to be passed to `pip install` when installing the pipeline package. For example, `--user` to install to the user home directory or `--no-deps` to not install package dependencies. ~~Any (option/flag)~~ |
+| pip args                                   | Additional installation options to be passed to `pip install` when installing the pipeline package. For example, `--user` to install to the user home directory or `--no-deps` to not install package dependencies. ~~Any (option/flag)~~ |
 | **CREATES**                                | The installed pipeline package in your `site-packages` directory.                                                                                                                                                                         |
 
 ## info {#info tag="command"}
@@ -77,15 +77,15 @@ $ python -m spacy info [--markdown] [--silent] [--exclude]
 $ python -m spacy info [model] [--markdown] [--silent] [--exclude]
 ```
 
-| Name                                             | Description                                                                                                             |
-| ------------------------------------------------ | ----------------------------------------------------------------------------------------------------------------------- |
-| `model`                                          | A trained pipeline, i.e. package name or path (optional). ~~Optional[str] \(option)~~                                   |
-| `--markdown`, `-md`                              | Print information as Markdown. ~~bool (flag)~~                                                                          |
-| `--silent`, `-s` <Tag variant="new">2.0.12</Tag> | Don't print anything, just return the values. ~~bool (flag)~~                                                           |
-| `--exclude`, `-e`                                | Comma-separated keys to exclude from the print-out. Defaults to `"labels"`. ~~Optional[str]~~                           |
-| `--url`, `-u` <Tag variant="new">3.5.0</Tag>     | Print the URL to download the most recent compatible version of the pipeline. Requires a pipeline name. ~~bool (flag)~~ |
-| `--help`, `-h`                                   | Show help message and available arguments. ~~bool (flag)~~                                                              |
-| **PRINTS**                                       | Information about your spaCy installation.                                                                              |
+| Name                                         | Description                                                                                                             |
+| -------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------- |
+| `model`                                      | A trained pipeline, i.e. package name or path (optional). ~~Optional[str] \(option)~~                                   |
+| `--markdown`, `-md`                          | Print information as Markdown. ~~bool (flag)~~                                                                          |
+| `--silent`, `-s`                             | Don't print anything, just return the values. ~~bool (flag)~~                                                           |
+| `--exclude`, `-e`                            | Comma-separated keys to exclude from the print-out. Defaults to `"labels"`. ~~Optional[str]~~                           |
+| `--url`, `-u` <Tag variant="new">3.5.0</Tag> | Print the URL to download the most recent compatible version of the pipeline. Requires a pipeline name. ~~bool (flag)~~ |
+| `--help`, `-h`                               | Show help message and available arguments. ~~bool (flag)~~                                                              |
+| **PRINTS**                                   | Information about your spaCy installation.                                                                              |
 
 ## validate {#validate new="2" tag="command"}
 
@@ -260,22 +260,22 @@ chosen based on the file extension of the input file.
 $ python -m spacy convert [input_file] [output_dir] [--converter] [--file-type] [--n-sents] [--seg-sents] [--base] [--morphology] [--merge-subtokens] [--ner-map] [--lang]
 ```
 
-| Name                                             | Description                                                                                                                               |
-| ------------------------------------------------ | ----------------------------------------------------------------------------------------------------------------------------------------- |
-| `input_path`                                     | Input file or directory. ~~Path (positional)~~                                                                                            |
-| `output_dir`                                     | Output directory for converted file. Defaults to `"-"`, meaning data will be written to `stdout`. ~~Optional[Path] \(option)~~            |
-| `--converter`, `-c` <Tag variant="new">2</Tag>   | Name of converter to use (see below). ~~str (option)~~                                                                                    |
-| `--file-type`, `-t` <Tag variant="new">2.1</Tag> | Type of file to create. Either `spacy` (default) for binary [`DocBin`](/api/docbin) data or `json` for v2.x JSON format. ~~str (option)~~ |
-| `--n-sents`, `-n`                                | Number of sentences per document. Supported for: `conll`, `conllu`, `iob`, `ner` ~~int (option)~~                                         |
-| `--seg-sents`, `-s` <Tag variant="new">2.2</Tag> | Segment sentences. Supported for: `conll`, `ner` ~~bool (flag)~~                                                                          |
-| `--base`, `-b`, `--model`                        | Trained spaCy pipeline for sentence segmentation to use as base (for `--seg-sents`). ~~Optional[str](option)~~                            |
-| `--morphology`, `-m`                             | Enable appending morphology to tags. Supported for: `conllu` ~~bool (flag)~~                                                              |
-| `--merge-subtokens`, `-T`                        | Merge CoNLL-U subtokens ~~bool (flag)~~                                                                                                   |
-| `--ner-map`, `-nm`                               | NER tag mapping (as JSON-encoded dict of entity types). Supported for: `conllu` ~~Optional[Path](option)~~                                |
-| `--lang`, `-l` <Tag variant="new">2.1</Tag>      | Language code (if tokenizer required). ~~Optional[str] \(option)~~                                                                        |
-| `--concatenate`, `-C`                            | Concatenate output to a single file ~~bool (flag)~~                                                                                       |
-| `--help`, `-h`                                   | Show help message and available arguments. ~~bool (flag)~~                                                                                |
-| **CREATES**                                      | Binary [`DocBin`](/api/docbin) training data that can be used with [`spacy train`](/api/cli#train).                                       |
+| Name                      | Description                                                                                                                               |
+| ------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------- |
+| `input_path`              | Input file or directory. ~~Path (positional)~~                                                                                            |
+| `output_dir`              | Output directory for converted file. Defaults to `"-"`, meaning data will be written to `stdout`. ~~Optional[Path] \(option)~~            |
+| `--converter`, `-c`       | Name of converter to use (see below). ~~str (option)~~                                                                                    |
+| `--file-type`, `-t`       | Type of file to create. Either `spacy` (default) for binary [`DocBin`](/api/docbin) data or `json` for v2.x JSON format. ~~str (option)~~ |
+| `--n-sents`, `-n`         | Number of sentences per document. Supported for: `conll`, `conllu`, `iob`, `ner` ~~int (option)~~                                         |
+| `--seg-sents`, `-s`       | Segment sentences. Supported for: `conll`, `ner` ~~bool (flag)~~                                                                          |
+| `--base`, `-b`, `--model` | Trained spaCy pipeline for sentence segmentation to use as base (for `--seg-sents`). ~~Optional[str](option)~~                            |
+| `--morphology`, `-m`      | Enable appending morphology to tags. Supported for: `conllu` ~~bool (flag)~~                                                              |
+| `--merge-subtokens`, `-T` | Merge CoNLL-U subtokens ~~bool (flag)~~                                                                                                   |
+| `--ner-map`, `-nm`        | NER tag mapping (as JSON-encoded dict of entity types). Supported for: `conllu` ~~Optional[Path](option)~~                                |
+| `--lang`, `-l`            | Language code (if tokenizer required). ~~Optional[str] \(option)~~                                                                        |
+| `--concatenate`, `-C`     | Concatenate output to a single file ~~bool (flag)~~                                                                                       |
+| `--help`, `-h`            | Show help message and available arguments. ~~bool (flag)~~                                                                                |
+| **CREATES**               | Binary [`DocBin`](/api/docbin) training data that can be used with [`spacy train`](/api/cli#train).                                       |
 
 ### Converters {#converters}
 
@@ -474,8 +474,7 @@ report span characteristics such as the average span length and the span (or
 span boundary) distinctiveness. The distinctiveness measure shows how different
 the tokens are with respect to the rest of the corpus using the KL-divergence of
 the token distributions. To learn more, you can check out Papay et al.'s work on
-[*Dissecting Span Identification Tasks with Performance Prediction* (EMNLP
-2020)](https://aclanthology.org/2020.emnlp-main.396/).
+[*Dissecting Span Identification Tasks with Performance Prediction* (EMNLP 2020)](https://aclanthology.org/2020.emnlp-main.396/).
 
 </Infobox>
 
@@ -1229,19 +1228,19 @@ $ python -m spacy package [input_dir] [output_dir] [--code] [--meta-path] [--cre
 > $ pip install dist/en_pipeline-0.0.0.tar.gz
 > ```
 
-| Name                                             | Description                                                                                                                                                                                                                                                                      |
-| ------------------------------------------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `input_dir`                                      | Path to directory containing pipeline data. ~~Path (positional)~~                                                                                                                                                                                                                |
-| `output_dir`                                     | Directory to create package folder in. ~~Path (positional)~~                                                                                                                                                                                                                     |
-| `--code`, `-c` <Tag variant="new">3</Tag>        | Comma-separated paths to Python files to be included in the package and imported in its `__init__.py`. This allows including [registering functions](/usage/training#custom-functions) and [custom components](/usage/processing-pipelines#custom-components). ~~str (option)~~  |
-| `--meta-path`, `-m` <Tag variant="new">2</Tag>   | Path to [`meta.json`](/api/data-formats#meta) file (optional). ~~Optional[Path] \(option)~~                                                                                                                                                                                      |
-| `--create-meta`, `-C` <Tag variant="new">2</Tag> | Create a `meta.json` file on the command line, even if one already exists in the directory. If an existing file is found, its entries will be shown as the defaults in the command line prompt. ~~bool (flag)~~                                                                  |
-| `--build`, `-b` <Tag variant="new">3</Tag>       | Comma-separated artifact formats to build. Can be `sdist` (for a `.tar.gz` archive) and/or `wheel` (for a binary `.whl` file), or `none` if you want to run this step manually. The generated artifacts can be installed by `pip install`. Defaults to `sdist`. ~~str (option)~~ |
-| `--name`, `-n` <Tag variant="new">3</Tag>        | Package name to override in meta. ~~Optional[str] \(option)~~                                                                                                                                                                                                                    |
-| `--version`, `-v` <Tag variant="new">3</Tag>     | Package version to override in meta. Useful when training new versions, as it doesn't require editing the meta template. ~~Optional[str] \(option)~~                                                                                                                             |
-| `--force`, `-f`                                  | Force overwriting of existing folder in output directory. ~~bool (flag)~~                                                                                                                                                                                                        |
-| `--help`, `-h`                                   | Show help message and available arguments. ~~bool (flag)~~                                                                                                                                                                                                                       |
-| **CREATES**                                      | A Python package containing the spaCy pipeline.                                                                                                                                                                                                                                  |
+| Name                                         | Description                                                                                                                                                                                                                                                                      |
+| -------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `input_dir`                                  | Path to directory containing pipeline data. ~~Path (positional)~~                                                                                                                                                                                                                |
+| `output_dir`                                 | Directory to create package folder in. ~~Path (positional)~~                                                                                                                                                                                                                     |
+| `--code`, `-c` <Tag variant="new">3</Tag>    | Comma-separated paths to Python files to be included in the package and imported in its `__init__.py`. This allows including [registering functions](/usage/training#custom-functions) and [custom components](/usage/processing-pipelines#custom-components). ~~str (option)~~  |
+| `--meta-path`, `-m`                          | Path to [`meta.json`](/api/data-formats#meta) file (optional). ~~Optional[Path] \(option)~~                                                                                                                                                                                      |
+| `--create-meta`, `-C`                        | Create a `meta.json` file on the command line, even if one already exists in the directory. If an existing file is found, its entries will be shown as the defaults in the command line prompt. ~~bool (flag)~~                                                                  |
+| `--build`, `-b` <Tag variant="new">3</Tag>   | Comma-separated artifact formats to build. Can be `sdist` (for a `.tar.gz` archive) and/or `wheel` (for a binary `.whl` file), or `none` if you want to run this step manually. The generated artifacts can be installed by `pip install`. Defaults to `sdist`. ~~str (option)~~ |
+| `--name`, `-n` <Tag variant="new">3</Tag>    | Package name to override in meta. ~~Optional[str] \(option)~~                                                                                                                                                                                                                    |
+| `--version`, `-v` <Tag variant="new">3</Tag> | Package version to override in meta. Useful when training new versions, as it doesn't require editing the meta template. ~~Optional[str] \(option)~~                                                                                                                             |
+| `--force`, `-f`                              | Force overwriting of existing folder in output directory. ~~bool (flag)~~                                                                                                                                                                                                        |
+| `--help`, `-h`                               | Show help message and available arguments. ~~bool (flag)~~                                                                                                                                                                                                                       |
+| **CREATES**                                  | A Python package containing the spaCy pipeline.                                                                                                                                                                                                                                  |
 
 ## project {#project new="3"}
 
diff --git a/website/docs/api/doc.md b/website/docs/api/doc.md
index f97ed4547..090489d83 100644
--- a/website/docs/api/doc.md
+++ b/website/docs/api/doc.md
@@ -209,15 +209,15 @@ alignment mode `"strict".
 > assert span.text == "New York"
 > ```
 
-| Name                                 | Description                                                                                                                                                                                                                                                                  |
-| ------------------------------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `start`                              | The index of the first character of the span. ~~int~~                                                                                                                                                                                                                        |
-| `end`                                | The index of the last character after the span. ~~int~~                                                                                                                                                                                                                      |
-| `label`                              | A label to attach to the span, e.g. for named entities. ~~Union[int, str]~~                                                                                                                                                                                                  |
-| `kb_id` <Tag variant="new">2.2</Tag> | An ID from a knowledge base to capture the meaning of a named entity. ~~Union[int, str]~~                                                                                                                                                                                    |
-| `vector`                             | A meaning representation of the span. ~~numpy.ndarray[ndim=1, dtype=float32]~~                                                                                                                                                                                               |
-| `alignment_mode`                     | How character indices snap to token boundaries. Options: `"strict"` (no snapping), `"contract"` (span of all tokens completely within the character span), `"expand"` (span of all tokens at least partially covered by the character span). Defaults to `"strict"`. ~~str~~ |
-| **RETURNS**                          | The newly constructed object or `None`. ~~Optional[Span]~~                                                                                                                                                                                                                   |
+| Name             | Description                                                                                                                                                                                                                                                                  |
+| ---------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `start`          | The index of the first character of the span. ~~int~~                                                                                                                                                                                                                        |
+| `end`            | The index of the last character after the span. ~~int~~                                                                                                                                                                                                                      |
+| `label`          | A label to attach to the span, e.g. for named entities. ~~Union[int, str]~~                                                                                                                                                                                                  |
+| `kb_id`          | An ID from a knowledge base to capture the meaning of a named entity. ~~Union[int, str]~~                                                                                                                                                                                    |
+| `vector`         | A meaning representation of the span. ~~numpy.ndarray[ndim=1, dtype=float32]~~                                                                                                                                                                                               |
+| `alignment_mode` | How character indices snap to token boundaries. Options: `"strict"` (no snapping), `"contract"` (span of all tokens completely within the character span), `"expand"` (span of all tokens at least partially covered by the character span). Defaults to `"strict"`. ~~str~~ |
+| **RETURNS**      | The newly constructed object or `None`. ~~Optional[Span]~~                                                                                                                                                                                                                   |
 
 ## Doc.set_ents {#set_ents tag="method" new="3"}
 
@@ -751,22 +751,22 @@ The L2 norm of the document's vector representation.
 
 ## Attributes {#attributes}
 
-| Name                                 | Description                                                                                                                         |
-| ------------------------------------ | ----------------------------------------------------------------------------------------------------------------------------------- |
-| `text`                               | A string representation of the document text. ~~str~~                                                                               |
-| `text_with_ws`                       | An alias of `Doc.text`, provided for duck-type compatibility with `Span` and `Token`. ~~str~~                                       |
-| `mem`                                | The document's local memory heap, for all C data it owns. ~~cymem.Pool~~                                                            |
-| `vocab`                              | The store of lexical types. ~~Vocab~~                                                                                               |
-| `tensor` <Tag variant="new">2</Tag>  | Container for dense vector representations. ~~numpy.ndarray~~                                                                       |
-| `user_data`                          | A generic storage area, for user custom data. ~~Dict[str, Any]~~                                                                    |
-| `lang` <Tag variant="new">2.1</Tag>  | Language of the document's vocabulary. ~~int~~                                                                                      |
-| `lang_` <Tag variant="new">2.1</Tag> | Language of the document's vocabulary. ~~str~~                                                                                      |
-| `sentiment`                          | The document's positivity/negativity score, if available. ~~float~~                                                                 |
-| `user_hooks`                         | A dictionary that allows customization of the `Doc`'s properties. ~~Dict[str, Callable]~~                                           |
-| `user_token_hooks`                   | A dictionary that allows customization of properties of `Token` children. ~~Dict[str, Callable]~~                                   |
-| `user_span_hooks`                    | A dictionary that allows customization of properties of `Span` children. ~~Dict[str, Callable]~~                                    |
-| `has_unknown_spaces`                 | Whether the document was constructed without known spacing between tokens (typically when created from gold tokenization). ~~bool~~ |
-| `_`                                  | User space for adding custom [attribute extensions](/usage/processing-pipelines#custom-components-attributes). ~~Underscore~~       |
+| Name                 | Description                                                                                                                         |
+| -------------------- | ----------------------------------------------------------------------------------------------------------------------------------- |
+| `text`               | A string representation of the document text. ~~str~~                                                                               |
+| `text_with_ws`       | An alias of `Doc.text`, provided for duck-type compatibility with `Span` and `Token`. ~~str~~                                       |
+| `mem`                | The document's local memory heap, for all C data it owns. ~~cymem.Pool~~                                                            |
+| `vocab`              | The store of lexical types. ~~Vocab~~                                                                                               |
+| `tensor`             | Container for dense vector representations. ~~numpy.ndarray~~                                                                       |
+| `user_data`          | A generic storage area, for user custom data. ~~Dict[str, Any]~~                                                                    |
+| `lang`               | Language of the document's vocabulary. ~~int~~                                                                                      |
+| `lang_`              | Language of the document's vocabulary. ~~str~~                                                                                      |
+| `sentiment`          | The document's positivity/negativity score, if available. ~~float~~                                                                 |
+| `user_hooks`         | A dictionary that allows customization of the `Doc`'s properties. ~~Dict[str, Callable]~~                                           |
+| `user_token_hooks`   | A dictionary that allows customization of properties of `Token` children. ~~Dict[str, Callable]~~                                   |
+| `user_span_hooks`    | A dictionary that allows customization of properties of `Span` children. ~~Dict[str, Callable]~~                                    |
+| `has_unknown_spaces` | Whether the document was constructed without known spacing between tokens (typically when created from gold tokenization). ~~bool~~ |
+| `_`                  | User space for adding custom [attribute extensions](/usage/processing-pipelines#custom-components-attributes). ~~Underscore~~       |
 
 ## Serialization fields {#serialization-fields}
 
diff --git a/website/docs/api/language.md b/website/docs/api/language.md
index 504640d57..ad0ac2a46 100644
--- a/website/docs/api/language.md
+++ b/website/docs/api/language.md
@@ -63,18 +63,18 @@ spaCy loads a model under the hood based on its
 > nlp = Language.from_config(config)
 > ```
 
-| Name                                  | Description                                                                                                                                                                                                                                                                                                      |
-| ------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `config`                              | The loaded config. ~~Union[Dict[str, Any], Config]~~                                                                                                                                                                                                                                                             |
-| _keyword-only_                        |                                                                                                                                                                                                                                                                                                                  |
-| `vocab`                               | A `Vocab` object. If `True`, a vocab is created using the default language data settings. ~~Vocab~~                                                                                                                                                                                                              |
+| Name                                  | Description                                                                                                                                                                                                                                                                                                        |
+| ------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
+| `config`                              | The loaded config. ~~Union[Dict[str, Any], Config]~~                                                                                                                                                                                                                                                               |
+| _keyword-only_                        |                                                                                                                                                                                                                                                                                                                    |
+| `vocab`                               | A `Vocab` object. If `True`, a vocab is created using the default language data settings. ~~Vocab~~                                                                                                                                                                                                                |
 | `disable`                             | Name(s) of pipeline component(s) to [disable](/usage/processing-pipelines#disabling). Disabled pipes will be loaded but they won't be run unless you explicitly enable them by calling [nlp.enable_pipe](/api/language#enable_pipe). Is merged with the config entry `nlp.disabled`. ~~Union[str, Iterable[str]]~~ |
-| `enable` <Tag variant="new">3.4</Tag> | Name(s) of pipeline component(s) to [enable](/usage/processing-pipelines#disabling). All other pipes will be disabled, but can be enabled again using [nlp.enable_pipe](/api/language#enable_pipe). ~~Union[str, Iterable[str]]~~                                       |
-| `exclude`                             | Name(s) of pipeline component(s) to [exclude](/usage/processing-pipelines#disabling). Excluded components won't be loaded. ~~Union[str, Iterable[str]]~~                                                                                                                                                         |
-| `meta`                                | [Meta data](/api/data-formats#meta) overrides. ~~Dict[str, Any]~~                                                                                                                                                                                                                                                |
-| `auto_fill`                           | Whether to automatically fill in missing values in the config, based on defaults and function argument annotations. Defaults to `True`. ~~bool~~                                                                                                                                                                 |
-| `validate`                            | Whether to validate the component config and arguments against the types expected by the factory. Defaults to `True`. ~~bool~~                                                                                                                                                                                   |
-| **RETURNS**                           | The initialized object. ~~Language~~                                                                                                                                                                                                                                                                             |
+| `enable` <Tag variant="new">3.4</Tag> | Name(s) of pipeline component(s) to [enable](/usage/processing-pipelines#disabling). All other pipes will be disabled, but can be enabled again using [nlp.enable_pipe](/api/language#enable_pipe). ~~Union[str, Iterable[str]]~~                                                                                  |
+| `exclude`                             | Name(s) of pipeline component(s) to [exclude](/usage/processing-pipelines#disabling). Excluded components won't be loaded. ~~Union[str, Iterable[str]]~~                                                                                                                                                           |
+| `meta`                                | [Meta data](/api/data-formats#meta) overrides. ~~Dict[str, Any]~~                                                                                                                                                                                                                                                  |
+| `auto_fill`                           | Whether to automatically fill in missing values in the config, based on defaults and function argument annotations. Defaults to `True`. ~~bool~~                                                                                                                                                                   |
+| `validate`                            | Whether to validate the component config and arguments against the types expected by the factory. Defaults to `True`. ~~bool~~                                                                                                                                                                                     |
+| **RETURNS**                           | The initialized object. ~~Language~~                                                                                                                                                                                                                                                                               |
 
 ## Language.component {#component tag="classmethod" new="3"}
 
@@ -198,16 +198,16 @@ tokenization is skipped but the rest of the pipeline is run.
 >     assert doc.has_annotation("DEP")
 > ```
 
-| Name                                       | Description                                                                                                                                                         |
-| ------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `texts`                                    | A sequence of strings (or `Doc` objects). ~~Iterable[Union[str, Doc]]~~                                                                                             |
-| _keyword-only_                             |                                                                                                                                                                     |
-| `as_tuples`                                | If set to `True`, inputs should be a sequence of `(text, context)` tuples. Output will then be a sequence of `(doc, context)` tuples. Defaults to `False`. ~~bool~~ |
-| `batch_size`                               | The number of texts to buffer. ~~Optional[int]~~                                                                                                                    |
-| `disable`                                  | Names of pipeline components to [disable](/usage/processing-pipelines#disabling). ~~List[str]~~                                                                     |
-| `component_cfg`                            | Optional dictionary of keyword arguments for components, keyed by component names. Defaults to `None`. ~~Optional[Dict[str, Dict[str, Any]]]~~                      |
-| `n_process` <Tag variant="new">2.2.2</Tag> | Number of processors to use. Defaults to `1`. ~~int~~                                                                                                               |
-| **YIELDS**                                 | Documents in the order of the original text. ~~Doc~~                                                                                                                |
+| Name            | Description                                                                                                                                                         |
+| --------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `texts`         | A sequence of strings (or `Doc` objects). ~~Iterable[Union[str, Doc]]~~                                                                                             |
+| _keyword-only_  |                                                                                                                                                                     |
+| `as_tuples`     | If set to `True`, inputs should be a sequence of `(text, context)` tuples. Output will then be a sequence of `(doc, context)` tuples. Defaults to `False`. ~~bool~~ |
+| `batch_size`    | The number of texts to buffer. ~~Optional[int]~~                                                                                                                    |
+| `disable`       | Names of pipeline components to [disable](/usage/processing-pipelines#disabling). ~~List[str]~~                                                                     |
+| `component_cfg` | Optional dictionary of keyword arguments for components, keyed by component names. Defaults to `None`. ~~Optional[Dict[str, Dict[str, Any]]]~~                      |
+| `n_process`     | Number of processors to use. Defaults to `1`. ~~int~~                                                                                                               |
+| **YIELDS**      | Documents in the order of the original text. ~~Doc~~                                                                                                                |
 
 ## Language.set_error_handler {#set_error_handler tag="method" new="3"}
 
@@ -1030,21 +1030,21 @@ details.
 
 ## Attributes {#attributes}
 
-| Name                                          | Description                                                                                                                                    |
-| --------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------- |
-| `vocab`                                       | A container for the lexical types. ~~Vocab~~                                                                                                   |
-| `tokenizer`                                   | The tokenizer. ~~Tokenizer~~                                                                                                                   |
-| `make_doc`                                    | Callable that takes a string and returns a `Doc`. ~~Callable[[str], Doc]~~                                                                     |
-| `pipeline`                                    | List of `(name, component)` tuples describing the current processing pipeline, in order. ~~List[Tuple[str, Callable[[Doc], Doc]]]~~            |
-| `pipe_names` <Tag variant="new">2</Tag>       | List of pipeline component names, in order. ~~List[str]~~                                                                                      |
-| `pipe_labels` <Tag variant="new">2.2</Tag>    | List of labels set by the pipeline components, if available, keyed by component name. ~~Dict[str, List[str]]~~                                 |
-| `pipe_factories` <Tag variant="new">2.2</Tag> | Dictionary of pipeline component names, mapped to their factory names. ~~Dict[str, str]~~                                                      |
-| `factories`                                   | All available factory functions, keyed by name. ~~Dict[str, Callable[[...], Callable[[Doc], Doc]]]~~                                           |
-| `factory_names` <Tag variant="new">3</Tag>    | List of all available factory names. ~~List[str]~~                                                                                             |
-| `components` <Tag variant="new">3</Tag>       | List of all available `(name, component)` tuples, including components that are currently disabled. ~~List[Tuple[str, Callable[[Doc], Doc]]]~~ |
-| `component_names` <Tag variant="new">3</Tag>  | List of all available component names, including components that are currently disabled. ~~List[str]~~                                         |
-| `disabled` <Tag variant="new">3</Tag>         | Names of components that are currently disabled and don't run as part of the pipeline. ~~List[str]~~                                           |
-| `path` <Tag variant="new">2</Tag>             | Path to the pipeline data directory, if a pipeline is loaded from a path or package. Otherwise `None`. ~~Optional[Path]~~                      |
+| Name                                         | Description                                                                                                                                    |
+| -------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------- |
+| `vocab`                                      | A container for the lexical types. ~~Vocab~~                                                                                                   |
+| `tokenizer`                                  | The tokenizer. ~~Tokenizer~~                                                                                                                   |
+| `make_doc`                                   | Callable that takes a string and returns a `Doc`. ~~Callable[[str], Doc]~~                                                                     |
+| `pipeline`                                   | List of `(name, component)` tuples describing the current processing pipeline, in order. ~~List[Tuple[str, Callable[[Doc], Doc]]]~~            |
+| `pipe_names`                                 | List of pipeline component names, in order. ~~List[str]~~                                                                                      |
+| `pipe_labels`                                | List of labels set by the pipeline components, if available, keyed by component name. ~~Dict[str, List[str]]~~                                 |
+| `pipe_factories`                             | Dictionary of pipeline component names, mapped to their factory names. ~~Dict[str, str]~~                                                      |
+| `factories`                                  | All available factory functions, keyed by name. ~~Dict[str, Callable[[...], Callable[[Doc], Doc]]]~~                                           |
+| `factory_names` <Tag variant="new">3</Tag>   | List of all available factory names. ~~List[str]~~                                                                                             |
+| `components` <Tag variant="new">3</Tag>      | List of all available `(name, component)` tuples, including components that are currently disabled. ~~List[Tuple[str, Callable[[Doc], Doc]]]~~ |
+| `component_names` <Tag variant="new">3</Tag> | List of all available component names, including components that are currently disabled. ~~List[str]~~                                         |
+| `disabled` <Tag variant="new">3</Tag>        | Names of components that are currently disabled and don't run as part of the pipeline. ~~List[str]~~                                           |
+| `path`                                       | Path to the pipeline data directory, if a pipeline is loaded from a path or package. Otherwise `None`. ~~Optional[Path]~~                      |
 
 ## Class attributes {#class-attributes}
 
diff --git a/website/docs/api/lexeme.md b/website/docs/api/lexeme.md
index c5d4b7544..eb76afa90 100644
--- a/website/docs/api/lexeme.md
+++ b/website/docs/api/lexeme.md
@@ -121,44 +121,44 @@ The L2 norm of the lexeme's vector representation.
 
 ## Attributes {#attributes}
 
-| Name                                         | Description                                                                                                                                                                                                                                                          |
-| -------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `vocab`                                      | The lexeme's vocabulary. ~~Vocab~~                                                                                                                                                                                                                                   |
-| `text`                                       | Verbatim text content. ~~str~~                                                                                                                                                                                                                                       |
-| `orth`                                       | ID of the verbatim text content. ~~int~~                                                                                                                                                                                                                             |
-| `orth_`                                      | Verbatim text content (identical to `Lexeme.text`). Exists mostly for consistency with the other attributes. ~~str~~                                                                                                                                                 |
-| `rank`                                       | Sequential ID of the lexeme's lexical type, used to index into tables, e.g. for word vectors. ~~int~~                                                                                                                                                                |
-| `flags`                                      | Container of the lexeme's binary flags. ~~int~~                                                                                                                                                                                                                      |
-| `norm`                                       | The lexeme's norm, i.e. a normalized form of the lexeme text. ~~int~~                                                                                                                                                                                                |
-| `norm_`                                      | The lexeme's norm, i.e. a normalized form of the lexeme text. ~~str~~                                                                                                                                                                                                |
-| `lower`                                      | Lowercase form of the word. ~~int~~                                                                                                                                                                                                                                  |
-| `lower_`                                     | Lowercase form of the word. ~~str~~                                                                                                                                                                                                                                  |
-| `shape`                                      | Transform of the word's string, to show orthographic features. Alphabetic characters are replaced by `x` or `X`, and numeric characters are replaced by `d`, and sequences of the same character are truncated after length 4. For example,`"Xxxx"`or`"dd"`. ~~int~~ |
-| `shape_`                                     | Transform of the word's string, to show orthographic features. Alphabetic characters are replaced by `x` or `X`, and numeric characters are replaced by `d`, and sequences of the same character are truncated after length 4. For example,`"Xxxx"`or`"dd"`. ~~str~~ |
-| `prefix`                                     | Length-N substring from the start of the word. Defaults to `N=1`. ~~int~~                                                                                                                                                                                            |
-| `prefix_`                                    | Length-N substring from the start of the word. Defaults to `N=1`. ~~str~~                                                                                                                                                                                            |
-| `suffix`                                     | Length-N substring from the end of the word. Defaults to `N=3`. ~~int~~                                                                                                                                                                                              |
-| `suffix_`                                    | Length-N substring from the start of the word. Defaults to `N=3`. ~~str~~                                                                                                                                                                                            |
-| `is_alpha`                                   | Does the lexeme consist of alphabetic characters? Equivalent to `lexeme.text.isalpha()`. ~~bool~~                                                                                                                                                                    |
-| `is_ascii`                                   | Does the lexeme consist of ASCII characters? Equivalent to `[any(ord(c) >= 128 for c in lexeme.text)]`. ~~bool~~                                                                                                                                                     |
-| `is_digit`                                   | Does the lexeme consist of digits? Equivalent to `lexeme.text.isdigit()`. ~~bool~~                                                                                                                                                                                   |
-| `is_lower`                                   | Is the lexeme in lowercase? Equivalent to `lexeme.text.islower()`. ~~bool~~                                                                                                                                                                                          |
-| `is_upper`                                   | Is the lexeme in uppercase? Equivalent to `lexeme.text.isupper()`. ~~bool~~                                                                                                                                                                                          |
-| `is_title`                                   | Is the lexeme in titlecase? Equivalent to `lexeme.text.istitle()`. ~~bool~~                                                                                                                                                                                          |
-| `is_punct`                                   | Is the lexeme punctuation? ~~bool~~                                                                                                                                                                                                                                  |
-| `is_left_punct`                              | Is the lexeme a left punctuation mark, e.g. `(`? ~~bool~~                                                                                                                                                                                                            |
-| `is_right_punct`                             | Is the lexeme a right punctuation mark, e.g. `)`? ~~bool~~                                                                                                                                                                                                           |
-| `is_space`                                   | Does the lexeme consist of whitespace characters? Equivalent to `lexeme.text.isspace()`. ~~bool~~                                                                                                                                                                    |
-| `is_bracket`                                 | Is the lexeme a bracket? ~~bool~~                                                                                                                                                                                                                                    |
-| `is_quote`                                   | Is the lexeme a quotation mark? ~~bool~~                                                                                                                                                                                                                             |
-| `is_currency` <Tag variant="new">2.0.8</Tag> | Is the lexeme a currency symbol? ~~bool~~                                                                                                                                                                                                                            |
-| `like_url`                                   | Does the lexeme resemble a URL? ~~bool~~                                                                                                                                                                                                                             |
-| `like_num`                                   | Does the lexeme represent a number? e.g. "10.9", "10", "ten", etc. ~~bool~~                                                                                                                                                                                          |
-| `like_email`                                 | Does the lexeme resemble an email address? ~~bool~~                                                                                                                                                                                                                  |
-| `is_oov`                                     | Is the lexeme out-of-vocabulary (i.e. does it not have a word vector)? ~~bool~~                                                                                                                                                                                      |
-| `is_stop`                                    | Is the lexeme part of a "stop list"? ~~bool~~                                                                                                                                                                                                                        |
-| `lang`                                       | Language of the parent vocabulary. ~~int~~                                                                                                                                                                                                                           |
-| `lang_`                                      | Language of the parent vocabulary. ~~str~~                                                                                                                                                                                                                           |
-| `prob`                                       | Smoothed log probability estimate of the lexeme's word type (context-independent entry in the vocabulary). ~~float~~                                                                                                                                                 |
-| `cluster`                                    | Brown cluster ID. ~~int~~                                                                                                                                                                                                                                            |
-| `sentiment`                                  | A scalar value indicating the positivity or negativity of the lexeme. ~~float~~                                                                                                                                                                                      |
+| Name             | Description                                                                                                                                                                                                                                                          |
+| ---------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `vocab`          | The lexeme's vocabulary. ~~Vocab~~                                                                                                                                                                                                                                   |
+| `text`           | Verbatim text content. ~~str~~                                                                                                                                                                                                                                       |
+| `orth`           | ID of the verbatim text content. ~~int~~                                                                                                                                                                                                                             |
+| `orth_`          | Verbatim text content (identical to `Lexeme.text`). Exists mostly for consistency with the other attributes. ~~str~~                                                                                                                                                 |
+| `rank`           | Sequential ID of the lexeme's lexical type, used to index into tables, e.g. for word vectors. ~~int~~                                                                                                                                                                |
+| `flags`          | Container of the lexeme's binary flags. ~~int~~                                                                                                                                                                                                                      |
+| `norm`           | The lexeme's norm, i.e. a normalized form of the lexeme text. ~~int~~                                                                                                                                                                                                |
+| `norm_`          | The lexeme's norm, i.e. a normalized form of the lexeme text. ~~str~~                                                                                                                                                                                                |
+| `lower`          | Lowercase form of the word. ~~int~~                                                                                                                                                                                                                                  |
+| `lower_`         | Lowercase form of the word. ~~str~~                                                                                                                                                                                                                                  |
+| `shape`          | Transform of the word's string, to show orthographic features. Alphabetic characters are replaced by `x` or `X`, and numeric characters are replaced by `d`, and sequences of the same character are truncated after length 4. For example,`"Xxxx"`or`"dd"`. ~~int~~ |
+| `shape_`         | Transform of the word's string, to show orthographic features. Alphabetic characters are replaced by `x` or `X`, and numeric characters are replaced by `d`, and sequences of the same character are truncated after length 4. For example,`"Xxxx"`or`"dd"`. ~~str~~ |
+| `prefix`         | Length-N substring from the start of the word. Defaults to `N=1`. ~~int~~                                                                                                                                                                                            |
+| `prefix_`        | Length-N substring from the start of the word. Defaults to `N=1`. ~~str~~                                                                                                                                                                                            |
+| `suffix`         | Length-N substring from the end of the word. Defaults to `N=3`. ~~int~~                                                                                                                                                                                              |
+| `suffix_`        | Length-N substring from the start of the word. Defaults to `N=3`. ~~str~~                                                                                                                                                                                            |
+| `is_alpha`       | Does the lexeme consist of alphabetic characters? Equivalent to `lexeme.text.isalpha()`. ~~bool~~                                                                                                                                                                    |
+| `is_ascii`       | Does the lexeme consist of ASCII characters? Equivalent to `[any(ord(c) >= 128 for c in lexeme.text)]`. ~~bool~~                                                                                                                                                     |
+| `is_digit`       | Does the lexeme consist of digits? Equivalent to `lexeme.text.isdigit()`. ~~bool~~                                                                                                                                                                                   |
+| `is_lower`       | Is the lexeme in lowercase? Equivalent to `lexeme.text.islower()`. ~~bool~~                                                                                                                                                                                          |
+| `is_upper`       | Is the lexeme in uppercase? Equivalent to `lexeme.text.isupper()`. ~~bool~~                                                                                                                                                                                          |
+| `is_title`       | Is the lexeme in titlecase? Equivalent to `lexeme.text.istitle()`. ~~bool~~                                                                                                                                                                                          |
+| `is_punct`       | Is the lexeme punctuation? ~~bool~~                                                                                                                                                                                                                                  |
+| `is_left_punct`  | Is the lexeme a left punctuation mark, e.g. `(`? ~~bool~~                                                                                                                                                                                                            |
+| `is_right_punct` | Is the lexeme a right punctuation mark, e.g. `)`? ~~bool~~                                                                                                                                                                                                           |
+| `is_space`       | Does the lexeme consist of whitespace characters? Equivalent to `lexeme.text.isspace()`. ~~bool~~                                                                                                                                                                    |
+| `is_bracket`     | Is the lexeme a bracket? ~~bool~~                                                                                                                                                                                                                                    |
+| `is_quote`       | Is the lexeme a quotation mark? ~~bool~~                                                                                                                                                                                                                             |
+| `is_currency`    | Is the lexeme a currency symbol? ~~bool~~                                                                                                                                                                                                                            |
+| `like_url`       | Does the lexeme resemble a URL? ~~bool~~                                                                                                                                                                                                                             |
+| `like_num`       | Does the lexeme represent a number? e.g. "10.9", "10", "ten", etc. ~~bool~~                                                                                                                                                                                          |
+| `like_email`     | Does the lexeme resemble an email address? ~~bool~~                                                                                                                                                                                                                  |
+| `is_oov`         | Is the lexeme out-of-vocabulary (i.e. does it not have a word vector)? ~~bool~~                                                                                                                                                                                      |
+| `is_stop`        | Is the lexeme part of a "stop list"? ~~bool~~                                                                                                                                                                                                                        |
+| `lang`           | Language of the parent vocabulary. ~~int~~                                                                                                                                                                                                                           |
+| `lang_`          | Language of the parent vocabulary. ~~str~~                                                                                                                                                                                                                           |
+| `prob`           | Smoothed log probability estimate of the lexeme's word type (context-independent entry in the vocabulary). ~~float~~                                                                                                                                                 |
+| `cluster`        | Brown cluster ID. ~~int~~                                                                                                                                                                                                                                            |
+| `sentiment`      | A scalar value indicating the positivity or negativity of the lexeme. ~~float~~                                                                                                                                                                                      |
diff --git a/website/docs/api/matcher.md b/website/docs/api/matcher.md
index 8cc446c6a..cd7bfa070 100644
--- a/website/docs/api/matcher.md
+++ b/website/docs/api/matcher.md
@@ -33,7 +33,7 @@ rule-based matching are:
 | Attribute                                      | Description                                                                                                               |
 | ---------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------- |
 | `ORTH`                                         | The exact verbatim text of a token. ~~str~~                                                                               |
-| `TEXT` <Tag variant="new">2.1</Tag>            | The exact verbatim text of a token. ~~str~~                                                                               |
+| `TEXT`                                         | The exact verbatim text of a token. ~~str~~                                                                               |
 | `NORM`                                         | The normalized form of the token text. ~~str~~                                                                            |
 | `LOWER`                                        | The lowercase form of the token text. ~~str~~                                                                             |
 | `LENGTH`                                       | The length of the token text. ~~int~~                                                                                     |
@@ -48,7 +48,7 @@ rule-based matching are:
 | `ENT_IOB`                                      | The IOB part of the token's entity tag. ~~str~~                                                                           |
 | `ENT_ID`                                       | The token's entity ID (`ent_id`). ~~str~~                                                                                 |
 | `ENT_KB_ID`                                    | The token's entity knowledge base ID (`ent_kb_id`). ~~str~~                                                               |
-| `_` <Tag variant="new">2.1</Tag>               | Properties in [custom extension attributes](/usage/processing-pipelines#custom-components-attributes). ~~Dict[str, Any]~~ |
+| `_`                                            | Properties in [custom extension attributes](/usage/processing-pipelines#custom-components-attributes). ~~Dict[str, Any]~~ |
 | `OP`                                           | Operator or quantifier to determine how often to match a token pattern. ~~str~~                                           |
 
 Operators and quantifiers define **how often** a token pattern should be
@@ -64,7 +64,7 @@ matched:
 > ```
 
 | OP      | Description                                                            |
-|---------|------------------------------------------------------------------------|
+| ------- | ---------------------------------------------------------------------- |
 | `!`     | Negate the pattern, by requiring it to match exactly 0 times.          |
 | `?`     | Make the pattern optional, by allowing it to match 0 or 1 times.       |
 | `+`     | Require the pattern to match 1 or more times.                          |
@@ -109,10 +109,10 @@ string where an integer is expected) or unexpected property names.
 > matcher = Matcher(nlp.vocab)
 > ```
 
-| Name                                    | Description                                                                                           |
-| --------------------------------------- | ----------------------------------------------------------------------------------------------------- |
-| `vocab`                                 | The vocabulary object, which must be shared with the documents the matcher will operate on. ~~Vocab~~ |
-| `validate` <Tag variant="new">2.1</Tag> | Validate all patterns added to this matcher. ~~bool~~                                                 |
+| Name       | Description                                                                                           |
+| ---------- | ----------------------------------------------------------------------------------------------------- |
+| `vocab`    | The vocabulary object, which must be shared with the documents the matcher will operate on. ~~Vocab~~ |
+| `validate` | Validate all patterns added to this matcher. ~~bool~~                                                 |
 
 ## Matcher.\_\_call\_\_ {#call tag="method"}
 
diff --git a/website/docs/api/phrasematcher.md b/website/docs/api/phrasematcher.md
index 2cef9ac2a..cd419ae5c 100644
--- a/website/docs/api/phrasematcher.md
+++ b/website/docs/api/phrasematcher.md
@@ -36,11 +36,11 @@ be shown.
 > matcher = PhraseMatcher(nlp.vocab)
 > ```
 
-| Name                                    | Description                                                                                            |
-| --------------------------------------- | ------------------------------------------------------------------------------------------------------ |
-| `vocab`                                 | The vocabulary object, which must be shared with the documents the matcher will operate on. ~~Vocab~~  |
-| `attr` <Tag variant="new">2.1</Tag>     | The token attribute to match on. Defaults to `ORTH`, i.e. the verbatim token text. ~~Union[int, str]~~ |
-| `validate` <Tag variant="new">2.1</Tag> | Validate patterns added to the matcher. ~~bool~~                                                       |
+| Name       | Description                                                                                            |
+| ---------- | ------------------------------------------------------------------------------------------------------ |
+| `vocab`    | The vocabulary object, which must be shared with the documents the matcher will operate on. ~~Vocab~~  |
+| `attr`     | The token attribute to match on. Defaults to `ORTH`, i.e. the verbatim token text. ~~Union[int, str]~~ |
+| `validate` | Validate patterns added to the matcher. ~~bool~~                                                       |
 
 ## PhraseMatcher.\_\_call\_\_ {#call tag="method"}
 
diff --git a/website/docs/api/span.md b/website/docs/api/span.md
index 89f608994..69bbe8db1 100644
--- a/website/docs/api/span.md
+++ b/website/docs/api/span.md
@@ -186,14 +186,14 @@ the character indices don't map to a valid span.
 > assert span.text == "New York"
 > ```
 
-| Name                                 | Description                                                                               |
-| ------------------------------------ | ----------------------------------------------------------------------------------------- |
-| `start`                              | The index of the first character of the span. ~~int~~                                     |
-| `end`                                | The index of the last character after the span. ~~int~~                                   |
-| `label`                              | A label to attach to the span, e.g. for named entities. ~~Union[int, str]~~               |
-| `kb_id` <Tag variant="new">2.2</Tag> | An ID from a knowledge base to capture the meaning of a named entity. ~~Union[int, str]~~ |
-| `vector`                             | A meaning representation of the span. ~~numpy.ndarray[ndim=1, dtype=float32]~~            |
-| **RETURNS**                          | The newly constructed object or `None`. ~~Optional[Span]~~                                |
+| Name        | Description                                                                               |
+| ----------- | ----------------------------------------------------------------------------------------- |
+| `start`     | The index of the first character of the span. ~~int~~                                     |
+| `end`       | The index of the last character after the span. ~~int~~                                   |
+| `label`     | A label to attach to the span, e.g. for named entities. ~~Union[int, str]~~               |
+| `kb_id`     | An ID from a knowledge base to capture the meaning of a named entity. ~~Union[int, str]~~ |
+| `vector`    | A meaning representation of the span. ~~numpy.ndarray[ndim=1, dtype=float32]~~            |
+| **RETURNS** | The newly constructed object or `None`. ~~Optional[Span]~~                                |
 
 ## Span.similarity {#similarity tag="method" model="vectors"}
 
@@ -544,26 +544,26 @@ overlaps with will be returned.
 
 ## Attributes {#attributes}
 
-| Name                                    | Description                                                                                                                   |
-| --------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------- |
-| `doc`                                   | The parent document. ~~Doc~~                                                                                                  |
-| `tensor` <Tag variant="new">2.1.7</Tag> | The span's slice of the parent `Doc`'s tensor. ~~numpy.ndarray~~                                                              |
-| `start`                                 | The token offset for the start of the span. ~~int~~                                                                           |
-| `end`                                   | The token offset for the end of the span. ~~int~~                                                                             |
-| `start_char`                            | The character offset for the start of the span. ~~int~~                                                                       |
-| `end_char`                              | The character offset for the end of the span. ~~int~~                                                                         |
-| `text`                                  | A string representation of the span text. ~~str~~                                                                             |
-| `text_with_ws`                          | The text content of the span with a trailing whitespace character if the last token has one. ~~str~~                          |
-| `orth`                                  | ID of the verbatim text content. ~~int~~                                                                                      |
-| `orth_`                                 | Verbatim text content (identical to `Span.text`). Exists mostly for consistency with the other attributes. ~~str~~            |
-| `label`                                 | The hash value of the span's label. ~~int~~                                                                                   |
-| `label_`                                | The span's label. ~~str~~                                                                                                     |
-| `lemma_`                                | The span's lemma. Equivalent to `"".join(token.text_with_ws for token in span)`. ~~str~~                                      |
-| `kb_id`                                 | The hash value of the knowledge base ID referred to by the span. ~~int~~                                                      |
-| `kb_id_`                                | The knowledge base ID referred to by the span. ~~str~~                                                                        |
-| `ent_id`                                | The hash value of the named entity the root token is an instance of. ~~int~~                                                  |
-| `ent_id_`                               | The string ID of the named entity the root token is an instance of. ~~str~~                                                   |
-| `id`                                    | The hash value of the span's ID. ~~int~~                                                                                      |
-| `id_`                                   | The span's ID. ~~str~~                                                                                                        |
-| `sentiment`                             | A scalar value indicating the positivity or negativity of the span. ~~float~~                                                 |
-| `_`                                     | User space for adding custom [attribute extensions](/usage/processing-pipelines#custom-components-attributes). ~~Underscore~~ |
+| Name           | Description                                                                                                                   |
+| -------------- | ----------------------------------------------------------------------------------------------------------------------------- |
+| `doc`          | The parent document. ~~Doc~~                                                                                                  |
+| `tensor`       | The span's slice of the parent `Doc`'s tensor. ~~numpy.ndarray~~                                                              |
+| `start`        | The token offset for the start of the span. ~~int~~                                                                           |
+| `end`          | The token offset for the end of the span. ~~int~~                                                                             |
+| `start_char`   | The character offset for the start of the span. ~~int~~                                                                       |
+| `end_char`     | The character offset for the end of the span. ~~int~~                                                                         |
+| `text`         | A string representation of the span text. ~~str~~                                                                             |
+| `text_with_ws` | The text content of the span with a trailing whitespace character if the last token has one. ~~str~~                          |
+| `orth`         | ID of the verbatim text content. ~~int~~                                                                                      |
+| `orth_`        | Verbatim text content (identical to `Span.text`). Exists mostly for consistency with the other attributes. ~~str~~            |
+| `label`        | The hash value of the span's label. ~~int~~                                                                                   |
+| `label_`       | The span's label. ~~str~~                                                                                                     |
+| `lemma_`       | The span's lemma. Equivalent to `"".join(token.text_with_ws for token in span)`. ~~str~~                                      |
+| `kb_id`        | The hash value of the knowledge base ID referred to by the span. ~~int~~                                                      |
+| `kb_id_`       | The knowledge base ID referred to by the span. ~~str~~                                                                        |
+| `ent_id`       | The hash value of the named entity the root token is an instance of. ~~int~~                                                  |
+| `ent_id_`      | The string ID of the named entity the root token is an instance of. ~~str~~                                                   |
+| `id`           | The hash value of the span's ID. ~~int~~                                                                                      |
+| `id_`          | The span's ID. ~~str~~                                                                                                        |
+| `sentiment`    | A scalar value indicating the positivity or negativity of the span. ~~float~~                                                 |
+| `_`            | User space for adding custom [attribute extensions](/usage/processing-pipelines#custom-components-attributes). ~~Underscore~~ |
diff --git a/website/docs/api/token.md b/website/docs/api/token.md
index d43cd3ff1..89bd77447 100644
--- a/website/docs/api/token.md
+++ b/website/docs/api/token.md
@@ -403,75 +403,75 @@ The L2 norm of the token's vector representation.
 
 ## Attributes {#attributes}
 
-| Name                                         | Description                                                                                                                                                                                                                                                          |
-| -------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `doc`                                        | The parent document. ~~Doc~~                                                                                                                                                                                                                                         |
-| `lex` <Tag variant="new">3</Tag>             | The underlying lexeme. ~~Lexeme~~                                                                                                                                                                                                                                    |
-| `sent` <Tag variant="new">2.0.12</Tag>       | The sentence span that this token is a part of. ~~Span~~                                                                                                                                                                                                             |
-| `text`                                       | Verbatim text content. ~~str~~                                                                                                                                                                                                                                       |
-| `text_with_ws`                               | Text content, with trailing space character if present. ~~str~~                                                                                                                                                                                                      |
-| `whitespace_`                                | Trailing space character if present. ~~str~~                                                                                                                                                                                                                         |
-| `orth`                                       | ID of the verbatim text content. ~~int~~                                                                                                                                                                                                                             |
-| `orth_`                                      | Verbatim text content (identical to `Token.text`). Exists mostly for consistency with the other attributes. ~~str~~                                                                                                                                                  |
-| `vocab`                                      | The vocab object of the parent `Doc`. ~~vocab~~                                                                                                                                                                                                                      |
-| `tensor` <Tag variant="new">2.1.7</Tag>      | The token's slice of the parent `Doc`'s tensor. ~~numpy.ndarray~~                                                                                                                                                                                                    |
-| `head`                                       | The syntactic parent, or "governor", of this token. ~~Token~~                                                                                                                                                                                                        |
-| `left_edge`                                  | The leftmost token of this token's syntactic descendants. ~~Token~~                                                                                                                                                                                                  |
-| `right_edge`                                 | The rightmost token of this token's syntactic descendants. ~~Token~~                                                                                                                                                                                                 |
-| `i`                                          | The index of the token within the parent document. ~~int~~                                                                                                                                                                                                           |
-| `ent_type`                                   | Named entity type. ~~int~~                                                                                                                                                                                                                                           |
-| `ent_type_`                                  | Named entity type. ~~str~~                                                                                                                                                                                                                                           |
-| `ent_iob`                                    | IOB code of named entity tag. `3` means the token begins an entity, `2` means it is outside an entity, `1` means it is inside an entity, and `0` means no entity tag is set. ~~int~~                                                                                 |
-| `ent_iob_`                                   | IOB code of named entity tag. "B" means the token begins an entity, "I" means it is inside an entity, "O" means it is outside an entity, and "" means no entity tag is set. ~~str~~                                                                                  |
-| `ent_kb_id` <Tag variant="new">2.2</Tag>     | Knowledge base ID that refers to the named entity this token is a part of, if any. ~~int~~                                                                                                                                                                           |
-| `ent_kb_id_` <Tag variant="new">2.2</Tag>    | Knowledge base ID that refers to the named entity this token is a part of, if any. ~~str~~                                                                                                                                                                           |
-| `ent_id`                                     | ID of the entity the token is an instance of, if any. Currently not used, but potentially for coreference resolution. ~~int~~                                                                                                                                        |
-| `ent_id_`                                    | ID of the entity the token is an instance of, if any. Currently not used, but potentially for coreference resolution. ~~str~~                                                                                                                                        |
-| `lemma`                                      | Base form of the token, with no inflectional suffixes. ~~int~~                                                                                                                                                                                                       |
-| `lemma_`                                     | Base form of the token, with no inflectional suffixes. ~~str~~                                                                                                                                                                                                       |
-| `norm`                                       | The token's norm, i.e. a normalized form of the token text. Can be set in the language's [tokenizer exceptions](/usage/linguistic-features#language-data). ~~int~~                                                                                                   |
-| `norm_`                                      | The token's norm, i.e. a normalized form of the token text. Can be set in the language's [tokenizer exceptions](/usage/linguistic-features#language-data). ~~str~~                                                                                                   |
-| `lower`                                      | Lowercase form of the token. ~~int~~                                                                                                                                                                                                                                 |
-| `lower_`                                     | Lowercase form of the token text. Equivalent to `Token.text.lower()`. ~~str~~                                                                                                                                                                                        |
-| `shape`                                      | Transform of the token's string to show orthographic features. Alphabetic characters are replaced by `x` or `X`, and numeric characters are replaced by `d`, and sequences of the same character are truncated after length 4. For example,`"Xxxx"`or`"dd"`. ~~int~~ |
-| `shape_`                                     | Transform of the token's string to show orthographic features. Alphabetic characters are replaced by `x` or `X`, and numeric characters are replaced by `d`, and sequences of the same character are truncated after length 4. For example,`"Xxxx"`or`"dd"`. ~~str~~ |
-| `prefix`                                     | Hash value of a length-N substring from the start of the token. Defaults to `N=1`. ~~int~~                                                                                                                                                                           |
-| `prefix_`                                    | A length-N substring from the start of the token. Defaults to `N=1`. ~~str~~                                                                                                                                                                                         |
-| `suffix`                                     | Hash value of a length-N substring from the end of the token. Defaults to `N=3`. ~~int~~                                                                                                                                                                             |
-| `suffix_`                                    | Length-N substring from the end of the token. Defaults to `N=3`. ~~str~~                                                                                                                                                                                             |
-| `is_alpha`                                   | Does the token consist of alphabetic characters? Equivalent to `token.text.isalpha()`. ~~bool~~                                                                                                                                                                      |
-| `is_ascii`                                   | Does the token consist of ASCII characters? Equivalent to `all(ord(c) < 128 for c in token.text)`. ~~bool~~                                                                                                                                                          |
-| `is_digit`                                   | Does the token consist of digits? Equivalent to `token.text.isdigit()`. ~~bool~~                                                                                                                                                                                     |
-| `is_lower`                                   | Is the token in lowercase? Equivalent to `token.text.islower()`. ~~bool~~                                                                                                                                                                                            |
-| `is_upper`                                   | Is the token in uppercase? Equivalent to `token.text.isupper()`. ~~bool~~                                                                                                                                                                                            |
-| `is_title`                                   | Is the token in titlecase? Equivalent to `token.text.istitle()`. ~~bool~~                                                                                                                                                                                            |
-| `is_punct`                                   | Is the token punctuation? ~~bool~~                                                                                                                                                                                                                                   |
-| `is_left_punct`                              | Is the token a left punctuation mark, e.g. `"("` ? ~~bool~~                                                                                                                                                                                                          |
-| `is_right_punct`                             | Is the token a right punctuation mark, e.g. `")"` ? ~~bool~~                                                                                                                                                                                                         |
-| `is_sent_start`                              | Does the token start a sentence? ~~bool~~ or `None` if unknown. Defaults to `True` for the first token in the `Doc`.                                                                                                                                                 |
-| `is_sent_end`                                | Does the token end a sentence? ~~bool~~ or `None` if unknown.                                                                                                                                                                                                        |
-| `is_space`                                   | Does the token consist of whitespace characters? Equivalent to `token.text.isspace()`. ~~bool~~                                                                                                                                                                      |
-| `is_bracket`                                 | Is the token a bracket? ~~bool~~                                                                                                                                                                                                                                     |
-| `is_quote`                                   | Is the token a quotation mark? ~~bool~~                                                                                                                                                                                                                              |
-| `is_currency` <Tag variant="new">2.0.8</Tag> | Is the token a currency symbol? ~~bool~~                                                                                                                                                                                                                             |
-| `like_url`                                   | Does the token resemble a URL? ~~bool~~                                                                                                                                                                                                                              |
-| `like_num`                                   | Does the token represent a number? e.g. "10.9", "10", "ten", etc. ~~bool~~                                                                                                                                                                                           |
-| `like_email`                                 | Does the token resemble an email address? ~~bool~~                                                                                                                                                                                                                   |
-| `is_oov`                                     | Is the token out-of-vocabulary (i.e. does it not have a word vector)? ~~bool~~                                                                                                                                                                                       |
-| `is_stop`                                    | Is the token part of a "stop list"? ~~bool~~                                                                                                                                                                                                                         |
-| `pos`                                        | Coarse-grained part-of-speech from the [Universal POS tag set](https://universaldependencies.org/u/pos/). ~~int~~                                                                                                                                                    |
-| `pos_`                                       | Coarse-grained part-of-speech from the [Universal POS tag set](https://universaldependencies.org/u/pos/). ~~str~~                                                                                                                                                    |
-| `tag`                                        | Fine-grained part-of-speech. ~~int~~                                                                                                                                                                                                                                 |
-| `tag_`                                       | Fine-grained part-of-speech. ~~str~~                                                                                                                                                                                                                                 |
-| `morph` <Tag variant="new">3</Tag>           | Morphological analysis. ~~MorphAnalysis~~                                                                                                                                                                                                                            |
-| `dep`                                        | Syntactic dependency relation. ~~int~~                                                                                                                                                                                                                               |
-| `dep_`                                       | Syntactic dependency relation. ~~str~~                                                                                                                                                                                                                               |
-| `lang`                                       | Language of the parent document's vocabulary. ~~int~~                                                                                                                                                                                                                |
-| `lang_`                                      | Language of the parent document's vocabulary. ~~str~~                                                                                                                                                                                                                |
-| `prob`                                       | Smoothed log probability estimate of token's word type (context-independent entry in the vocabulary). ~~float~~                                                                                                                                                      |
-| `idx`                                        | The character offset of the token within the parent document. ~~int~~                                                                                                                                                                                                |
-| `sentiment`                                  | A scalar value indicating the positivity or negativity of the token. ~~float~~                                                                                                                                                                                       |
-| `lex_id`                                     | Sequential ID of the token's lexical type, used to index into tables, e.g. for word vectors. ~~int~~                                                                                                                                                                 |
-| `rank`                                       | Sequential ID of the token's lexical type, used to index into tables, e.g. for word vectors. ~~int~~                                                                                                                                                                 |
-| `cluster`                                    | Brown cluster ID. ~~int~~                                                                                                                                                                                                                                            |
-| `_`                                          | User space for adding custom [attribute extensions](/usage/processing-pipelines#custom-components-attributes). ~~Underscore~~                                                                                                                                        |
+| Name                               | Description                                                                                                                                                                                                                                                          |
+| ---------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `doc`                              | The parent document. ~~Doc~~                                                                                                                                                                                                                                         |
+| `lex` <Tag variant="new">3</Tag>   | The underlying lexeme. ~~Lexeme~~                                                                                                                                                                                                                                    |
+| `sent`                             | The sentence span that this token is a part of. ~~Span~~                                                                                                                                                                                                             |
+| `text`                             | Verbatim text content. ~~str~~                                                                                                                                                                                                                                       |
+| `text_with_ws`                     | Text content, with trailing space character if present. ~~str~~                                                                                                                                                                                                      |
+| `whitespace_`                      | Trailing space character if present. ~~str~~                                                                                                                                                                                                                         |
+| `orth`                             | ID of the verbatim text content. ~~int~~                                                                                                                                                                                                                             |
+| `orth_`                            | Verbatim text content (identical to `Token.text`). Exists mostly for consistency with the other attributes. ~~str~~                                                                                                                                                  |
+| `vocab`                            | The vocab object of the parent `Doc`. ~~vocab~~                                                                                                                                                                                                                      |
+| `tensor`                           | The token's slice of the parent `Doc`'s tensor. ~~numpy.ndarray~~                                                                                                                                                                                                    |
+| `head`                             | The syntactic parent, or "governor", of this token. ~~Token~~                                                                                                                                                                                                        |
+| `left_edge`                        | The leftmost token of this token's syntactic descendants. ~~Token~~                                                                                                                                                                                                  |
+| `right_edge`                       | The rightmost token of this token's syntactic descendants. ~~Token~~                                                                                                                                                                                                 |
+| `i`                                | The index of the token within the parent document. ~~int~~                                                                                                                                                                                                           |
+| `ent_type`                         | Named entity type. ~~int~~                                                                                                                                                                                                                                           |
+| `ent_type_`                        | Named entity type. ~~str~~                                                                                                                                                                                                                                           |
+| `ent_iob`                          | IOB code of named entity tag. `3` means the token begins an entity, `2` means it is outside an entity, `1` means it is inside an entity, and `0` means no entity tag is set. ~~int~~                                                                                 |
+| `ent_iob_`                         | IOB code of named entity tag. "B" means the token begins an entity, "I" means it is inside an entity, "O" means it is outside an entity, and "" means no entity tag is set. ~~str~~                                                                                  |
+| `ent_kb_id`                        | Knowledge base ID that refers to the named entity this token is a part of, if any. ~~int~~                                                                                                                                                                           |
+| `ent_kb_id_`                       | Knowledge base ID that refers to the named entity this token is a part of, if any. ~~str~~                                                                                                                                                                           |
+| `ent_id`                           | ID of the entity the token is an instance of, if any. Currently not used, but potentially for coreference resolution. ~~int~~                                                                                                                                        |
+| `ent_id_`                          | ID of the entity the token is an instance of, if any. Currently not used, but potentially for coreference resolution. ~~str~~                                                                                                                                        |
+| `lemma`                            | Base form of the token, with no inflectional suffixes. ~~int~~                                                                                                                                                                                                       |
+| `lemma_`                           | Base form of the token, with no inflectional suffixes. ~~str~~                                                                                                                                                                                                       |
+| `norm`                             | The token's norm, i.e. a normalized form of the token text. Can be set in the language's [tokenizer exceptions](/usage/linguistic-features#language-data). ~~int~~                                                                                                   |
+| `norm_`                            | The token's norm, i.e. a normalized form of the token text. Can be set in the language's [tokenizer exceptions](/usage/linguistic-features#language-data). ~~str~~                                                                                                   |
+| `lower`                            | Lowercase form of the token. ~~int~~                                                                                                                                                                                                                                 |
+| `lower_`                           | Lowercase form of the token text. Equivalent to `Token.text.lower()`. ~~str~~                                                                                                                                                                                        |
+| `shape`                            | Transform of the token's string to show orthographic features. Alphabetic characters are replaced by `x` or `X`, and numeric characters are replaced by `d`, and sequences of the same character are truncated after length 4. For example,`"Xxxx"`or`"dd"`. ~~int~~ |
+| `shape_`                           | Transform of the token's string to show orthographic features. Alphabetic characters are replaced by `x` or `X`, and numeric characters are replaced by `d`, and sequences of the same character are truncated after length 4. For example,`"Xxxx"`or`"dd"`. ~~str~~ |
+| `prefix`                           | Hash value of a length-N substring from the start of the token. Defaults to `N=1`. ~~int~~                                                                                                                                                                           |
+| `prefix_`                          | A length-N substring from the start of the token. Defaults to `N=1`. ~~str~~                                                                                                                                                                                         |
+| `suffix`                           | Hash value of a length-N substring from the end of the token. Defaults to `N=3`. ~~int~~                                                                                                                                                                             |
+| `suffix_`                          | Length-N substring from the end of the token. Defaults to `N=3`. ~~str~~                                                                                                                                                                                             |
+| `is_alpha`                         | Does the token consist of alphabetic characters? Equivalent to `token.text.isalpha()`. ~~bool~~                                                                                                                                                                      |
+| `is_ascii`                         | Does the token consist of ASCII characters? Equivalent to `all(ord(c) < 128 for c in token.text)`. ~~bool~~                                                                                                                                                          |
+| `is_digit`                         | Does the token consist of digits? Equivalent to `token.text.isdigit()`. ~~bool~~                                                                                                                                                                                     |
+| `is_lower`                         | Is the token in lowercase? Equivalent to `token.text.islower()`. ~~bool~~                                                                                                                                                                                            |
+| `is_upper`                         | Is the token in uppercase? Equivalent to `token.text.isupper()`. ~~bool~~                                                                                                                                                                                            |
+| `is_title`                         | Is the token in titlecase? Equivalent to `token.text.istitle()`. ~~bool~~                                                                                                                                                                                            |
+| `is_punct`                         | Is the token punctuation? ~~bool~~                                                                                                                                                                                                                                   |
+| `is_left_punct`                    | Is the token a left punctuation mark, e.g. `"("` ? ~~bool~~                                                                                                                                                                                                          |
+| `is_right_punct`                   | Is the token a right punctuation mark, e.g. `")"` ? ~~bool~~                                                                                                                                                                                                         |
+| `is_sent_start`                    | Does the token start a sentence? ~~bool~~ or `None` if unknown. Defaults to `True` for the first token in the `Doc`.                                                                                                                                                 |
+| `is_sent_end`                      | Does the token end a sentence? ~~bool~~ or `None` if unknown.                                                                                                                                                                                                        |
+| `is_space`                         | Does the token consist of whitespace characters? Equivalent to `token.text.isspace()`. ~~bool~~                                                                                                                                                                      |
+| `is_bracket`                       | Is the token a bracket? ~~bool~~                                                                                                                                                                                                                                     |
+| `is_quote`                         | Is the token a quotation mark? ~~bool~~                                                                                                                                                                                                                              |
+| `is_currency`                      | Is the token a currency symbol? ~~bool~~                                                                                                                                                                                                                             |
+| `like_url`                         | Does the token resemble a URL? ~~bool~~                                                                                                                                                                                                                              |
+| `like_num`                         | Does the token represent a number? e.g. "10.9", "10", "ten", etc. ~~bool~~                                                                                                                                                                                           |
+| `like_email`                       | Does the token resemble an email address? ~~bool~~                                                                                                                                                                                                                   |
+| `is_oov`                           | Is the token out-of-vocabulary (i.e. does it not have a word vector)? ~~bool~~                                                                                                                                                                                       |
+| `is_stop`                          | Is the token part of a "stop list"? ~~bool~~                                                                                                                                                                                                                         |
+| `pos`                              | Coarse-grained part-of-speech from the [Universal POS tag set](https://universaldependencies.org/u/pos/). ~~int~~                                                                                                                                                    |
+| `pos_`                             | Coarse-grained part-of-speech from the [Universal POS tag set](https://universaldependencies.org/u/pos/). ~~str~~                                                                                                                                                    |
+| `tag`                              | Fine-grained part-of-speech. ~~int~~                                                                                                                                                                                                                                 |
+| `tag_`                             | Fine-grained part-of-speech. ~~str~~                                                                                                                                                                                                                                 |
+| `morph` <Tag variant="new">3</Tag> | Morphological analysis. ~~MorphAnalysis~~                                                                                                                                                                                                                            |
+| `dep`                              | Syntactic dependency relation. ~~int~~                                                                                                                                                                                                                               |
+| `dep_`                             | Syntactic dependency relation. ~~str~~                                                                                                                                                                                                                               |
+| `lang`                             | Language of the parent document's vocabulary. ~~int~~                                                                                                                                                                                                                |
+| `lang_`                            | Language of the parent document's vocabulary. ~~str~~                                                                                                                                                                                                                |
+| `prob`                             | Smoothed log probability estimate of token's word type (context-independent entry in the vocabulary). ~~float~~                                                                                                                                                      |
+| `idx`                              | The character offset of the token within the parent document. ~~int~~                                                                                                                                                                                                |
+| `sentiment`                        | A scalar value indicating the positivity or negativity of the token. ~~float~~                                                                                                                                                                                       |
+| `lex_id`                           | Sequential ID of the token's lexical type, used to index into tables, e.g. for word vectors. ~~int~~                                                                                                                                                                 |
+| `rank`                             | Sequential ID of the token's lexical type, used to index into tables, e.g. for word vectors. ~~int~~                                                                                                                                                                 |
+| `cluster`                          | Brown cluster ID. ~~int~~                                                                                                                                                                                                                                            |
+| `_`                                | User space for adding custom [attribute extensions](/usage/processing-pipelines#custom-components-attributes). ~~Underscore~~                                                                                                                                        |
diff --git a/website/docs/api/top-level.md b/website/docs/api/top-level.md
index c798f2a8d..211affa4a 100644
--- a/website/docs/api/top-level.md
+++ b/website/docs/api/top-level.md
@@ -45,16 +45,16 @@ specified separately using the new `exclude` keyword argument.
 > nlp = spacy.load("en_core_web_sm", exclude=["parser", "tagger"])
 > ```
 
-| Name                                  | Description                                                                                                                                                                                                                                                                                                      |
-| ------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `name`                                | Pipeline to load, i.e. package name or path. ~~Union[str, Path]~~                                                                                                                                                                                                                                                |
-| _keyword-only_                        |                                                                                                                                                                                                                                                                                                                  |
-| `vocab`                               | Optional shared vocab to pass in on initialization. If `True` (default), a new `Vocab` object will be created. ~~Union[Vocab, bool]~~                                                                                                                                                                            |
+| Name                                  | Description                                                                                                                                                                                                                                                                                                        |
+| ------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
+| `name`                                | Pipeline to load, i.e. package name or path. ~~Union[str, Path]~~                                                                                                                                                                                                                                                  |
+| _keyword-only_                        |                                                                                                                                                                                                                                                                                                                    |
+| `vocab`                               | Optional shared vocab to pass in on initialization. If `True` (default), a new `Vocab` object will be created. ~~Union[Vocab, bool]~~                                                                                                                                                                              |
 | `disable`                             | Name(s) of pipeline component(s) to [disable](/usage/processing-pipelines#disabling). Disabled pipes will be loaded but they won't be run unless you explicitly enable them by calling [nlp.enable_pipe](/api/language#enable_pipe). Is merged with the config entry `nlp.disabled`. ~~Union[str, Iterable[str]]~~ |
-| `enable` <Tag variant="new">3.4</Tag> | Name(s) of pipeline component(s) to [enable](/usage/processing-pipelines#disabling). All other pipes will be disabled. ~~Union[str, Iterable[str]]~~                                                                                                                    |
-| `exclude` <Tag variant="new">3</Tag>  | Name(s) of pipeline component(s) to [exclude](/usage/processing-pipelines#disabling). Excluded components won't be loaded. ~~Union[str, Iterable[str]]~~                                                                                                                                                         |
-| `config` <Tag variant="new">3</Tag>   | Optional config overrides, either as nested dict or dict keyed by section value in dot notation, e.g. `"components.name.value"`. ~~Union[Dict[str, Any], Config]~~                                                                                                                                               |
-| **RETURNS**                           | A `Language` object with the loaded pipeline. ~~Language~~                                                                                                                                                                                                                                                       |
+| `enable` <Tag variant="new">3.4</Tag> | Name(s) of pipeline component(s) to [enable](/usage/processing-pipelines#disabling). All other pipes will be disabled. ~~Union[str, Iterable[str]]~~                                                                                                                                                               |
+| `exclude` <Tag variant="new">3</Tag>  | Name(s) of pipeline component(s) to [exclude](/usage/processing-pipelines#disabling). Excluded components won't be loaded. ~~Union[str, Iterable[str]]~~                                                                                                                                                           |
+| `config` <Tag variant="new">3</Tag>   | Optional config overrides, either as nested dict or dict keyed by section value in dot notation, e.g. `"components.name.value"`. ~~Union[Dict[str, Any], Config]~~                                                                                                                                                 |
+| **RETURNS**                           | A `Language` object with the loaded pipeline. ~~Language~~                                                                                                                                                                                                                                                         |
 
 Essentially, `spacy.load()` is a convenience wrapper that reads the pipeline's
 [`config.cfg`](/api/data-formats#config), uses the language and pipeline
@@ -354,22 +354,22 @@ If a setting is not present in the options, the default value will be used.
 > displacy.serve(doc, style="dep", options=options)
 > ```
 
-| Name                                       | Description                                                                                                                                  |
-| ------------------------------------------ | -------------------------------------------------------------------------------------------------------------------------------------------- |
-| `fine_grained`                             | Use fine-grained part-of-speech tags (`Token.tag_`) instead of coarse-grained tags (`Token.pos_`). Defaults to `False`. ~~bool~~             |
-| `add_lemma` <Tag variant="new">2.2.4</Tag> | Print the lemmas in a separate row below the token texts. Defaults to `False`. ~~bool~~                                                      |
-| `collapse_punct`                           | Attach punctuation to tokens. Can make the parse more readable, as it prevents long arcs to attach punctuation. Defaults to `True`. ~~bool~~ |
-| `collapse_phrases`                         | Merge noun phrases into one token. Defaults to `False`. ~~bool~~                                                                             |
-| `compact`                                  | "Compact mode" with square arrows that takes up less space. Defaults to `False`. ~~bool~~                                                    |
-| `color`                                    | Text color (HEX, RGB or color names). Defaults to `"#000000"`. ~~str~~                                                                       |
-| `bg`                                       | Background color (HEX, RGB or color names). Defaults to `"#ffffff"`. ~~str~~                                                                 |
-| `font`                                     | Font name or font family for all text. Defaults to `"Arial"`. ~~str~~                                                                        |
-| `offset_x`                                 | Spacing on left side of the SVG in px. Defaults to `50`. ~~int~~                                                                             |
-| `arrow_stroke`                             | Width of arrow path in px. Defaults to `2`. ~~int~~                                                                                          |
-| `arrow_width`                              | Width of arrow head in px. Defaults to `10` in regular mode and `8` in compact mode. ~~int~~                                                 |
-| `arrow_spacing`                            | Spacing between arrows in px to avoid overlaps. Defaults to `20` in regular mode and `12` in compact mode. ~~int~~                           |
-| `word_spacing`                             | Vertical spacing between words and arcs in px. Defaults to `45`. ~~int~~                                                                     |
-| `distance`                                 | Distance between words in px. Defaults to `175` in regular mode and `150` in compact mode. ~~int~~                                           |
+| Name               | Description                                                                                                                                  |
+| ------------------ | -------------------------------------------------------------------------------------------------------------------------------------------- |
+| `fine_grained`     | Use fine-grained part-of-speech tags (`Token.tag_`) instead of coarse-grained tags (`Token.pos_`). Defaults to `False`. ~~bool~~             |
+| `add_lemma`        | Print the lemmas in a separate row below the token texts. Defaults to `False`. ~~bool~~                                                      |
+| `collapse_punct`   | Attach punctuation to tokens. Can make the parse more readable, as it prevents long arcs to attach punctuation. Defaults to `True`. ~~bool~~ |
+| `collapse_phrases` | Merge noun phrases into one token. Defaults to `False`. ~~bool~~                                                                             |
+| `compact`          | "Compact mode" with square arrows that takes up less space. Defaults to `False`. ~~bool~~                                                    |
+| `color`            | Text color (HEX, RGB or color names). Defaults to `"#000000"`. ~~str~~                                                                       |
+| `bg`               | Background color (HEX, RGB or color names). Defaults to `"#ffffff"`. ~~str~~                                                                 |
+| `font`             | Font name or font family for all text. Defaults to `"Arial"`. ~~str~~                                                                        |
+| `offset_x`         | Spacing on left side of the SVG in px. Defaults to `50`. ~~int~~                                                                             |
+| `arrow_stroke`     | Width of arrow path in px. Defaults to `2`. ~~int~~                                                                                          |
+| `arrow_width`      | Width of arrow head in px. Defaults to `10` in regular mode and `8` in compact mode. ~~int~~                                                 |
+| `arrow_spacing`    | Spacing between arrows in px to avoid overlaps. Defaults to `20` in regular mode and `12` in compact mode. ~~int~~                           |
+| `word_spacing`     | Vertical spacing between words and arcs in px. Defaults to `45`. ~~int~~                                                                     |
+| `distance`         | Distance between words in px. Defaults to `175` in regular mode and `150` in compact mode. ~~int~~                                           |
 
 #### Named Entity Visualizer options {#displacy_options-ent}
 
@@ -385,7 +385,7 @@ If a setting is not present in the options, the default value will be used.
 | ------------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
 | `ents`                                           | Entity types to highlight or `None` for all types (default). ~~Optional[List[str]]~~                                                                                                                                                        |
 | `colors`                                         | Color overrides. Entity types should be mapped to color names or values. ~~Dict[str, str]~~                                                                                                                                                 |
-| `template` <Tag variant="new">2.2</Tag>          | Optional template to overwrite the HTML used to render entity spans. Should be a format string and can use `{bg}`, `{text}` and `{label}`. See [`templates.py`](%%GITHUB_SPACY/spacy/displacy/templates.py) for examples. ~~Optional[str]~~ |
+| `template`                                       | Optional template to overwrite the HTML used to render entity spans. Should be a format string and can use `{bg}`, `{text}` and `{label}`. See [`templates.py`](%%GITHUB_SPACY/spacy/displacy/templates.py) for examples. ~~Optional[str]~~ |
 | `kb_url_template` <Tag variant="new">3.2.1</Tag> | Optional template to construct the KB url for the entity to link to. Expects a python f-string format with single field to fill in. ~~Optional[str]~~                                                                                       |
 
 #### Span Visualizer options {#displacy_options-span}
diff --git a/website/docs/api/vocab.md b/website/docs/api/vocab.md
index 2e4a206ec..afbd1301d 100644
--- a/website/docs/api/vocab.md
+++ b/website/docs/api/vocab.md
@@ -21,15 +21,15 @@ Create the vocabulary.
 > vocab = Vocab(strings=["hello", "world"])
 > ```
 
-| Name                                        | Description                                                                                                                                                             |
-| ------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `lex_attr_getters`                          | A dictionary mapping attribute IDs to functions to compute them. Defaults to `None`. ~~Optional[Dict[str, Callable[[str], Any]]]~~                                      |
-| `strings`                                   | A [`StringStore`](/api/stringstore) that maps strings to hash values, and vice versa, or a list of strings. ~~Union[List[str], StringStore]~~                           |
-| `lookups`                                   | A [`Lookups`](/api/lookups) that stores the `lexeme_norm` and other large lookup tables. Defaults to `None`. ~~Optional[Lookups]~~                                      |
-| `oov_prob`                                  | The default OOV probability. Defaults to `-20.0`. ~~float~~                                                                                                             |
-| `vectors_name` <Tag variant="new">2.2</Tag> | A name to identify the vectors table. ~~str~~                                                                                                                           |
-| `writing_system`                            | A dictionary describing the language's writing system. Typically provided by [`Language.Defaults`](/api/language#defaults). ~~Dict[str, Any]~~                          |
-| `get_noun_chunks`                           | A function that yields base noun phrases used for [`Doc.noun_chunks`](/api/doc#noun_chunks). ~~Optional[Callable[[Union[Doc, Span], Iterator[Tuple[int, int, int]]]]]~~ |
+| Name               | Description                                                                                                                                                             |
+| ------------------ | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `lex_attr_getters` | A dictionary mapping attribute IDs to functions to compute them. Defaults to `None`. ~~Optional[Dict[str, Callable[[str], Any]]]~~                                      |
+| `strings`          | A [`StringStore`](/api/stringstore) that maps strings to hash values, and vice versa, or a list of strings. ~~Union[List[str], StringStore]~~                           |
+| `lookups`          | A [`Lookups`](/api/lookups) that stores the `lexeme_norm` and other large lookup tables. Defaults to `None`. ~~Optional[Lookups]~~                                      |
+| `oov_prob`         | The default OOV probability. Defaults to `-20.0`. ~~float~~                                                                                                             |
+| `vectors_name`     | A name to identify the vectors table. ~~str~~                                                                                                                           |
+| `writing_system`   | A dictionary describing the language's writing system. Typically provided by [`Language.Defaults`](/api/language#defaults). ~~Dict[str, Any]~~                          |
+| `get_noun_chunks`  | A function that yields base noun phrases used for [`Doc.noun_chunks`](/api/doc#noun_chunks). ~~Optional[Callable[[Union[Doc, Span], Iterator[Tuple[int, int, int]]]]]~~ |
 
 ## Vocab.\_\_len\_\_ {#len tag="method"}
 
@@ -311,10 +311,10 @@ Load state from a binary string.
 | Name                                           | Description                                                                                                                                                            |
 | ---------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
 | `strings`                                      | A table managing the string-to-int mapping. ~~StringStore~~                                                                                                            |
-| `vectors` <Tag variant="new">2</Tag>           | A table associating word IDs to word vectors. ~~Vectors~~                                                                                                              |
+| `vectors`                                      | A table associating word IDs to word vectors. ~~Vectors~~                                                                                                              |
 | `vectors_length`                               | Number of dimensions for each word vector. ~~int~~                                                                                                                     |
 | `lookups`                                      | The available lookup tables in this vocab. ~~Lookups~~                                                                                                                 |
-| `writing_system` <Tag variant="new">2.1</Tag>  | A dict with information about the language's writing system. ~~Dict[str, Any]~~                                                                                        |
+| `writing_system`                               | A dict with information about the language's writing system. ~~Dict[str, Any]~~                                                                                        |
 | `get_noun_chunks` <Tag variant="new">3.0</Tag> | A function that yields base noun phrases used for [`Doc.noun_chunks`](/ap/doc#noun_chunks). ~~Optional[Callable[[Union[Doc, Span], Iterator[Tuple[int, int, int]]]]]~~ |
 
 ## Serialization fields {#serialization-fields}
diff --git a/website/docs/usage/rule-based-matching.md b/website/docs/usage/rule-based-matching.md
index 64bbf8e7b..ad8ea27f3 100644
--- a/website/docs/usage/rule-based-matching.md
+++ b/website/docs/usage/rule-based-matching.md
@@ -162,7 +162,7 @@ rule-based matching are:
 | Attribute                                      | Description                                                                                                                                                                                                                                                                                               |
 | ---------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
 | `ORTH`                                         | The exact verbatim text of a token. ~~str~~                                                                                                                                                                                                                                                               |
-| `TEXT` <Tag variant="new">2.1</Tag>            | The exact verbatim text of a token. ~~str~~                                                                                                                                                                                                                                                               |
+| `TEXT`                                         | The exact verbatim text of a token. ~~str~~                                                                                                                                                                                                                                                               |
 | `NORM`                                         | The normalized form of the token text. ~~str~~                                                                                                                                                                                                                                                            |
 | `LOWER`                                        | The lowercase form of the token text. ~~str~~                                                                                                                                                                                                                                                             |
 | `LENGTH`                                       | The length of the token text. ~~int~~                                                                                                                                                                                                                                                                     |
@@ -174,7 +174,7 @@ rule-based matching are:
 | `SPACY`                                        | Token has a trailing space. ~~bool~~                                                                                                                                                                                                                                                                      |
 | `POS`, `TAG`, `MORPH`, `DEP`, `LEMMA`, `SHAPE` | The token's simple and extended part-of-speech tag, morphological analysis, dependency label, lemma, shape. Note that the values of these attributes are case-sensitive. For a list of available part-of-speech tags and dependency labels, see the [Annotation Specifications](/api/annotation). ~~str~~ |
 | `ENT_TYPE`                                     | The token's entity label. ~~str~~                                                                                                                                                                                                                                                                         |
-| `_` <Tag variant="new">2.1</Tag>               | Properties in [custom extension attributes](/usage/processing-pipelines#custom-components-attributes). ~~Dict[str, Any]~~                                                                                                                                                                                 |
+| `_`                                            | Properties in [custom extension attributes](/usage/processing-pipelines#custom-components-attributes). ~~Dict[str, Any]~~                                                                                                                                                                                 |
 | `OP`                                           | [Operator or quantifier](#quantifiers) to determine how often to match a token pattern. ~~str~~                                                                                                                                                                                                           |
 
 <Accordion title="Does it matter if the attribute names are uppercase or lowercase?">
@@ -375,7 +375,7 @@ scoped quantifiers – instead, you can build those behaviors with `on_match`
 callbacks.
 
 | OP      | Description                                                            |
-|---------|------------------------------------------------------------------------|
+| ------- | ---------------------------------------------------------------------- |
 | `!`     | Negate the pattern, by requiring it to match exactly 0 times.          |
 | `?`     | Make the pattern optional, by allowing it to match 0 or 1 times.       |
 | `+`     | Require the pattern to match 1 or more times.                          |
diff --git a/website/docs/usage/saving-loading.md b/website/docs/usage/saving-loading.md
index 0fd713a49..29870a2e3 100644
--- a/website/docs/usage/saving-loading.md
+++ b/website/docs/usage/saving-loading.md
@@ -306,12 +306,12 @@ pipeline component factories, language classes and other settings. To make spaCy
 use your entry points, your package needs to expose them and it needs to be
 installed in the same environment – that's it.
 
-| Entry point                                                                    | Description                                                                                                                                                                                                                                              |
-| ------------------------------------------------------------------------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| [`spacy_factories`](#entry-points-components)                                  | Group of entry points for pipeline component factories, keyed by component name. Can be used to expose custom components defined by another package.                                                                                                     |
-| [`spacy_languages`](#entry-points-languages)                                   | Group of entry points for custom [`Language` subclasses](/usage/linguistic-features#language-data), keyed by language shortcut.                                                                                                                          |
-| `spacy_lookups` <Tag variant="new">2.2</Tag>                                   | Group of entry points for custom [`Lookups`](/api/lookups), including lemmatizer data. Used by spaCy's [`spacy-lookups-data`](https://github.com/explosion/spacy-lookups-data) package.                                                                  |
-| [`spacy_displacy_colors`](#entry-points-displacy) <Tag variant="new">2.2</Tag> | Group of entry points of custom label colors for the [displaCy visualizer](/usage/visualizers#ent). The key name doesn't matter, but it should point to a dict of labels and color values. Useful for custom models that predict different entity types. |
+| Entry point                                       | Description                                                                                                                                                                                                                                              |
+| ------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| [`spacy_factories`](#entry-points-components)     | Group of entry points for pipeline component factories, keyed by component name. Can be used to expose custom components defined by another package.                                                                                                     |
+| [`spacy_languages`](#entry-points-languages)      | Group of entry points for custom [`Language` subclasses](/usage/linguistic-features#language-data), keyed by language shortcut.                                                                                                                          |
+| `spacy_lookups`                                   | Group of entry points for custom [`Lookups`](/api/lookups), including lemmatizer data. Used by spaCy's [`spacy-lookups-data`](https://github.com/explosion/spacy-lookups-data) package.                                                                  |
+| [`spacy_displacy_colors`](#entry-points-displacy) | Group of entry points of custom label colors for the [displaCy visualizer](/usage/visualizers#ent). The key name doesn't matter, but it should point to a dict of labels and color values. Useful for custom models that predict different entity types. |
 
 ### Custom components via entry points {#entry-points-components}
 

From bb523d4d9105d417e240e6f8f83b63ed3dcc565e Mon Sep 17 00:00:00 2001
From: Paul O'Leary McCann <polm@dampfkraft.com>
Date: Mon, 14 Nov 2022 19:58:38 +0900
Subject: [PATCH 160/174] Remove spacy-ray from docs (#11781)

* Remove spacy ray from cli docs

* Remove more ray docs

* Remove ray from universe
---
 website/docs/api/cli.md        | 45 ---------------------
 website/docs/usage/index.md    |  1 -
 website/docs/usage/projects.md | 48 -----------------------
 website/docs/usage/training.md | 71 ----------------------------------
 website/meta/universe.json     | 11 ------
 5 files changed, 176 deletions(-)

diff --git a/website/docs/api/cli.md b/website/docs/api/cli.md
index 024450920..6e581b903 100644
--- a/website/docs/api/cli.md
+++ b/website/docs/api/cli.md
@@ -15,7 +15,6 @@ menu:
   - ['assemble', 'assemble']
   - ['package', 'package']
   - ['project', 'project']
-  - ['ray', 'ray']
   - ['huggingface-hub', 'huggingface-hub']
 ---
 
@@ -1502,50 +1501,6 @@ $ python -m spacy project dvc [project_dir] [workflow] [--force] [--verbose] [--
 | `--help`, `-h`    | Show help message and available arguments. ~~bool (flag)~~                                                    |
 | **CREATES**       | A `dvc.yaml` file in the project directory, based on the steps defined in the given workflow.                 |
 
-## ray {#ray new="3"}
-
-The `spacy ray` CLI includes commands for parallel and distributed computing via
-[Ray](https://ray.io).
-
-<Infobox variant="warning">
-
-To use this command, you need the
-[`spacy-ray`](https://github.com/explosion/spacy-ray) package installed.
-Installing the package will automatically add the `ray` command to the spaCy
-CLI.
-
-</Infobox>
-
-### ray train {#ray-train tag="command"}
-
-Train a spaCy pipeline using [Ray](https://ray.io) for parallel training. The
-command works just like [`spacy train`](/api/cli#train). For more details and
-examples, see the usage guide on
-[parallel training](/usage/training#parallel-training) and the spaCy project
-[integration](/usage/projects#ray).
-
-```cli
-$ python -m spacy ray train [config_path] [--code] [--output] [--n-workers] [--address] [--gpu-id] [--verbose] [overrides]
-```
-
-> #### Example
->
-> ```cli
-> $ python -m spacy ray train config.cfg --n-workers 2
-> ```
-
-| Name                | Description                                                                                                                                                                                |
-| ------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
-| `config_path`       | Path to [training config](/api/data-formats#config) file containing all settings and hyperparameters. ~~Path (positional)~~                                                                |
-| `--code`, `-c`      | Path to Python file with additional code to be imported. Allows [registering custom functions](/usage/training#custom-functions) for new architectures. ~~Optional[Path] \(option)~~       |
-| `--output`, `-o`    | Directory or remote storage URL for saving trained pipeline. The directory will be created if it doesn't exist. ~~Optional[Path] \(option)~~                                               |
-| `--n-workers`, `-n` | The number of workers. Defaults to `1`. ~~int (option)~~                                                                                                                                   |
-| `--address`, `-a`   | Optional address of the Ray cluster. If not set (default), Ray will run locally. ~~Optional[str] \(option)~~                                                                               |
-| `--gpu-id`, `-g`    | GPU ID or `-1` for CPU. Defaults to `-1`. ~~int (option)~~                                                                                                                                 |
-| `--verbose`, `-V`   | Display more information for debugging purposes. ~~bool (flag)~~                                                                                                                           |
-| `--help`, `-h`      | Show help message and available arguments. ~~bool (flag)~~                                                                                                                                 |
-| overrides           | Config parameters to override. Should be options starting with `--` that correspond to the config section and value to override, e.g. `--paths.train ./train.spacy`. ~~Any (option/flag)~~ |
-
 ## huggingface-hub {#huggingface-hub new="3.1"}
 
 The `spacy huggingface-cli` CLI includes commands for uploading your trained
diff --git a/website/docs/usage/index.md b/website/docs/usage/index.md
index 1f4869606..dff5a16ba 100644
--- a/website/docs/usage/index.md
+++ b/website/docs/usage/index.md
@@ -75,7 +75,6 @@ spaCy's [`setup.cfg`](%%GITHUB_SPACY/setup.cfg) for details on what's included.
 | ---------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
 | `lookups`        | Install [`spacy-lookups-data`](https://github.com/explosion/spacy-lookups-data) for data tables for lemmatization and lexeme normalization. The data is serialized with trained pipelines, so you only need this package if you want to train your own models. |
 | `transformers`   | Install [`spacy-transformers`](https://github.com/explosion/spacy-transformers). The package will be installed automatically when you install a transformer-based pipeline.                                                                                    |
-| `ray`            | Install [`spacy-ray`](https://github.com/explosion/spacy-ray) to add CLI commands for [parallel training](/usage/training#parallel-training).                                                                                                                  |
 | `cuda`, ...      | Install spaCy with GPU support provided by [CuPy](https://cupy.chainer.org) for your given CUDA version. See the GPU [installation instructions](#gpu) for details and options.                                                                                |
 | `apple`          | Install [`thinc-apple-ops`](https://github.com/explosion/thinc-apple-ops) to improve performance on an Apple M1.                                                                                                                                               |
 | `ja`, `ko`, `th` | Install additional dependencies required for tokenization for the [languages](/usage/models#languages).                                                                                                                                                        |
diff --git a/website/docs/usage/projects.md b/website/docs/usage/projects.md
index 90b612358..34315e4e7 100644
--- a/website/docs/usage/projects.md
+++ b/website/docs/usage/projects.md
@@ -1014,54 +1014,6 @@ https://github.com/explosion/projects/blob/v3/integrations/fastapi/scripts/main.
 
 ---
 
-### Ray {#ray} <IntegrationLogo name="ray" width={100} height="auto" align="right" />
-
-> #### Installation
->
-> ```cli
-> $ pip install -U %%SPACY_PKG_NAME[ray]%%SPACY_PKG_FLAGS
-> # Check that the CLI is registered
-> $ python -m spacy ray --help
-> ```
-
-[Ray](https://ray.io/) is a fast and simple framework for building and running
-**distributed applications**. You can use Ray for parallel and distributed
-training with spaCy via our lightweight
-[`spacy-ray`](https://github.com/explosion/spacy-ray) extension package. If the
-package is installed in the same environment as spaCy, it will automatically add
-[`spacy ray`](/api/cli#ray) commands to your spaCy CLI. See the usage guide on
-[parallel training](/usage/training#parallel-training) for more details on how
-it works under the hood.
-
-<Project id="integrations/ray">
-
-Get started with parallel training using our project template. It trains a
-simple model on a Universal Dependencies Treebank and lets you parallelize the
-training with Ray.
-
-</Project>
-
-You can integrate [`spacy ray train`](/api/cli#ray-train) into your
-`project.yml` just like the regular training command and pass it the config, and
-optional output directory or remote storage URL and config overrides if needed.
-
-<!-- prettier-ignore -->
-```yaml
-### project.yml
-commands:
-  - name: "ray"
-    help: "Train a model via parallel training with Ray"
-    script:
-      - "python -m spacy ray train configs/config.cfg -o training/ --paths.train corpus/train.spacy --paths.dev corpus/dev.spacy"
-    deps:
-      - "corpus/train.spacy"
-      - "corpus/dev.spacy"
-    outputs:
-      - "training/model-best"
-```
-
----
-
 ### Weights & Biases {#wandb} <IntegrationLogo name="wandb" width={175} height="auto" align="right" />
 
 [Weights & Biases](https://www.wandb.com/) is a popular platform for experiment
diff --git a/website/docs/usage/training.md b/website/docs/usage/training.md
index 27a8bbca7..e40a395c4 100644
--- a/website/docs/usage/training.md
+++ b/website/docs/usage/training.md
@@ -1572,77 +1572,6 @@ token-based annotations like the dependency parse or entity labels, you'll need
 to take care to adjust the `Example` object so its annotations match and remain
 valid.
 
-## Parallel & distributed training with Ray {#parallel-training}
-
-> #### Installation
->
-> ```cli
-> $ pip install -U %%SPACY_PKG_NAME[ray]%%SPACY_PKG_FLAGS
-> # Check that the CLI is registered
-> $ python -m spacy ray --help
-> ```
-
-[Ray](https://ray.io/) is a fast and simple framework for building and running
-**distributed applications**. You can use Ray to train spaCy on one or more
-remote machines, potentially speeding up your training process. Parallel
-training won't always be faster though – it depends on your batch size, models,
-and hardware.
-
-<Infobox variant="warning">
-
-To use Ray with spaCy, you need the
-[`spacy-ray`](https://github.com/explosion/spacy-ray) package installed.
-Installing the package will automatically add the `ray` command to the spaCy
-CLI.
-
-</Infobox>
-
-The [`spacy ray train`](/api/cli#ray-train) command follows the same API as
-[`spacy train`](/api/cli#train), with a few extra options to configure the Ray
-setup. You can optionally set the `--address` option to point to your Ray
-cluster. If it's not set, Ray will run locally.
-
-```cli
-python -m spacy ray train config.cfg --n-workers 2
-```
-
-<Project id="integrations/ray">
-
-Get started with parallel training using our project template. It trains a
-simple model on a Universal Dependencies Treebank and lets you parallelize the
-training with Ray.
-
-</Project>
-
-### How parallel training works {#parallel-training-details}
-
-Each worker receives a shard of the **data** and builds a copy of the **model
-and optimizer** from the [`config.cfg`](#config). It also has a communication
-channel to **pass gradients and parameters** to the other workers. Additionally,
-each worker is given ownership of a subset of the parameter arrays. Every
-parameter array is owned by exactly one worker, and the workers are given a
-mapping so they know which worker owns which parameter.
-
-![Illustration of setup](../images/spacy-ray.svg)
-
-As training proceeds, every worker will be computing gradients for **all** of
-the model parameters. When they compute gradients for parameters they don't own,
-they'll **send them to the worker** that does own that parameter, along with a
-version identifier so that the owner can decide whether to discard the gradient.
-Workers use the gradients they receive and the ones they compute locally to
-update the parameters they own, and then broadcast the updated array and a new
-version ID to the other workers.
-
-This training procedure is **asynchronous** and **non-blocking**. Workers always
-push their gradient increments and parameter updates, they do not have to pull
-them and block on the result, so the transfers can happen in the background,
-overlapped with the actual training work. The workers also do not have to stop
-and wait for each other ("synchronize") at the start of each batch. This is very
-useful for spaCy, because spaCy is often trained on long documents, which means
-**batches can vary in size** significantly. Uneven workloads make synchronous
-gradient descent inefficient, because if one batch is slow, all of the other
-workers are stuck waiting for it to complete before they can continue.
-
 ## Internal training API {#api}
 
 <Infobox variant="danger">
diff --git a/website/meta/universe.json b/website/meta/universe.json
index fa765f640..661f5da12 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -557,17 +557,6 @@
             "tags": ["sentiment", "textblob"],
             "spacy_version": 3
         },
-        {
-            "id": "spacy-ray",
-            "title": "spacy-ray",
-            "slogan": "Parallel and distributed training with spaCy and Ray",
-            "description": "[Ray](https://ray.io/) is a fast and simple framework for building and running **distributed applications**. This very lightweight extension package lets you use Ray for parallel and distributed training with spaCy. If `spacy-ray` is installed in the same environment as spaCy, it will automatically add `spacy ray` commands to your spaCy CLI.",
-            "github": "explosion/spacy-ray",
-            "pip": "spacy-ray",
-            "category": ["training"],
-            "author": "Explosion / Anyscale",
-            "thumb": "https://i.imgur.com/7so6ZpS.png"
-        },
         {
             "id": "spacy-sentence-bert",
             "title": "spaCy - sentence-transformers",

From 9baa686f827eeaecf28bf6d75836eeaec090cd69 Mon Sep 17 00:00:00 2001
From: Peter Baumgartner <5107405+pmbaumgartner@users.noreply.github.com>
Date: Mon, 14 Nov 2022 10:53:14 -0500
Subject: [PATCH 161/174] remove migration support form (#11802)

---
 website/docs/usage/v3.md | 12 ------------
 1 file changed, 12 deletions(-)

diff --git a/website/docs/usage/v3.md b/website/docs/usage/v3.md
index 971779ed3..64f93b7c0 100644
--- a/website/docs/usage/v3.md
+++ b/website/docs/usage/v3.md
@@ -15,18 +15,6 @@ menu:
 > To help you make the transition from v2.x to v3.0, we've uploaded the old
 > website to [**v2.spacy.io**](https://v2.spacy.io/docs).
 
-<Infobox title="New: Commercial migration support for your spaCy pipelines" variant="warning" emoji="📣">
-
-Want to make the transition from spaCy v2 to spaCy v3 as smooth as possible for
-you and your organization? We're now offering commercial **migration support**
-for your spaCy pipelines! We've put a lot of work into making it easy to upgrade
-your existing code and training workflows – but custom projects may always need
-some custom work, especially when it comes to taking advantage of the new
-capabilities.
-[**Details & application &rarr;**](https://form.typeform.com/to/vMs2zSjM)
-
-</Infobox>
-
 <Grid cols={2} gutterBottom={false}>
 
 <div>

From 7e684ad691992e759e71026a11c1ddd77c401f39 Mon Sep 17 00:00:00 2001
From: Denis Bezykornov <archidevil52@gmail.com>
Date: Tue, 15 Nov 2022 13:37:25 +0300
Subject: [PATCH 162/174] Update russian tokenizer exceptions (#11753)

* Fix typos, add couple of new abbreviations, remove nonbreaking spaces

* Remove space from abbreviation

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
---
 spacy/lang/ru/tokenizer_exceptions.py | 18 ++++++++++++------
 1 file changed, 12 insertions(+), 6 deletions(-)

diff --git a/spacy/lang/ru/tokenizer_exceptions.py b/spacy/lang/ru/tokenizer_exceptions.py
index f3756e26c..e1889f785 100644
--- a/spacy/lang/ru/tokenizer_exceptions.py
+++ b/spacy/lang/ru/tokenizer_exceptions.py
@@ -61,6 +61,11 @@ for abbr in [
     {ORTH: "2к23", NORM: "2023"},
     {ORTH: "2к24", NORM: "2024"},
     {ORTH: "2к25", NORM: "2025"},
+    {ORTH: "2к26", NORM: "2026"},
+    {ORTH: "2к27", NORM: "2027"},
+    {ORTH: "2к28", NORM: "2028"},
+    {ORTH: "2к29", NORM: "2029"},
+    {ORTH: "2к30", NORM: "2030"},
 ]:
     _exc[abbr[ORTH]] = [abbr]
 
@@ -268,8 +273,8 @@ for abbr in [
     {ORTH: "з-ка", NORM: "заимка"},
     {ORTH: "п-к", NORM: "починок"},
     {ORTH: "киш.", NORM: "кишлак"},
-    {ORTH: "п. ст. ", NORM: "поселок станция"},
-    {ORTH: "п. ж/д ст. ", NORM: "поселок при железнодорожной станции"},
+    {ORTH: "п. ст.", NORM: "поселок станция"},
+    {ORTH: "п. ж/д ст.", NORM: "поселок при железнодорожной станции"},
     {ORTH: "ж/д бл-ст", NORM: "железнодорожный блокпост"},
     {ORTH: "ж/д б-ка", NORM: "железнодорожная будка"},
     {ORTH: "ж/д в-ка", NORM: "железнодорожная ветка"},
@@ -280,12 +285,12 @@ for abbr in [
     {ORTH: "ж/д п.п.", NORM: "железнодорожный путевой пост"},
     {ORTH: "ж/д о.п.", NORM: "железнодорожный остановочный пункт"},
     {ORTH: "ж/д рзд.", NORM: "железнодорожный разъезд"},
-    {ORTH: "ж/д ст. ", NORM: "железнодорожная станция"},
+    {ORTH: "ж/д ст.", NORM: "железнодорожная станция"},
     {ORTH: "м-ко", NORM: "местечко"},
     {ORTH: "д.", NORM: "деревня"},
     {ORTH: "с.", NORM: "село"},
     {ORTH: "сл.", NORM: "слобода"},
-    {ORTH: "ст. ", NORM: "станция"},
+    {ORTH: "ст.", NORM: "станция"},
     {ORTH: "ст-ца", NORM: "станица"},
     {ORTH: "у.", NORM: "улус"},
     {ORTH: "х.", NORM: "хутор"},
@@ -388,8 +393,9 @@ for abbr in [
     {ORTH: "прим.", NORM: "примечание"},
     {ORTH: "прим.ред.", NORM: "примечание редакции"},
     {ORTH: "см. также", NORM: "смотри также"},
-    {ORTH: "кв.м.", NORM: "квадрантный метр"},
-    {ORTH: "м2", NORM: "квадрантный метр"},
+    {ORTH: "см.", NORM: "смотри"},
+    {ORTH: "кв.м.", NORM: "квадратный метр"},
+    {ORTH: "м2", NORM: "квадратный метр"},
     {ORTH: "б/у", NORM: "бывший в употреблении"},
     {ORTH: "сокр.", NORM: "сокращение"},
     {ORTH: "чел.", NORM: "человек"},

From caa9efad5991d574cf2bdc69fabfc6d952d5cba9 Mon Sep 17 00:00:00 2001
From: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Date: Tue, 15 Nov 2022 14:15:00 +0100
Subject: [PATCH 163/174] prevent rewriting an already raw URL (#11810)

---
 spacy/cli/project/assets.py | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/spacy/cli/project/assets.py b/spacy/cli/project/assets.py
index 61438d1a8..8f35b2d23 100644
--- a/spacy/cli/project/assets.py
+++ b/spacy/cli/project/assets.py
@@ -189,7 +189,11 @@ def convert_asset_url(url: str) -> str:
     RETURNS (str): The converted URL.
     """
     # If the asset URL is a regular GitHub URL it's likely a mistake
-    if re.match(r"(http(s?)):\/\/github.com", url) and "releases/download" not in url:
+    if (
+        re.match(r"(http(s?)):\/\/github.com", url)
+        and "releases/download" not in url
+        and "/raw/" not in url
+    ):
         converted = url.replace("github.com", "raw.githubusercontent.com")
         converted = re.sub(r"/(tree|blob)/", "/", converted)
         msg.warn(

From c0c54e44bc70ca737b421def1f6ce3c30809a54b Mon Sep 17 00:00:00 2001
From: Paul O'Leary McCann <polm@dampfkraft.com>
Date: Wed, 16 Nov 2022 17:44:42 +0900
Subject: [PATCH 164/174] Add equality definition for vectors (#11806)

* Add equality definition for vectors

This re-uses the check from sourcing components.

* Use the equality check

* Format

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
---
 spacy/language.py                         |  8 +-------
 spacy/tests/vocab_vectors/test_vectors.py | 20 ++++++++++++++++++++
 spacy/vectors.pyx                         |  9 +++++++++
 3 files changed, 30 insertions(+), 7 deletions(-)

diff --git a/spacy/language.py b/spacy/language.py
index 967af1e62..836f3abf9 100644
--- a/spacy/language.py
+++ b/spacy/language.py
@@ -706,13 +706,7 @@ class Language:
         # Check source type
         if not isinstance(source, Language):
             raise ValueError(Errors.E945.format(name=source_name, source=type(source)))
-        # Check vectors, with faster checks first
-        if (
-            self.vocab.vectors.shape != source.vocab.vectors.shape
-            or self.vocab.vectors.key2row != source.vocab.vectors.key2row
-            or self.vocab.vectors.to_bytes(exclude=["strings"])
-            != source.vocab.vectors.to_bytes(exclude=["strings"])
-        ):
+        if self.vocab.vectors != source.vocab.vectors:
             warnings.warn(Warnings.W113.format(name=source_name))
         if source_name not in source.component_names:
             raise KeyError(
diff --git a/spacy/tests/vocab_vectors/test_vectors.py b/spacy/tests/vocab_vectors/test_vectors.py
index dd2cfc596..70835816d 100644
--- a/spacy/tests/vocab_vectors/test_vectors.py
+++ b/spacy/tests/vocab_vectors/test_vectors.py
@@ -626,3 +626,23 @@ def test_floret_vectors(floret_vectors_vec_str, floret_vectors_hashvec_str):
             OPS.to_numpy(vocab_r[word].vector),
             decimal=6,
         )
+
+
+def test_equality():
+    vectors1 = Vectors(shape=(10, 10))
+    vectors2 = Vectors(shape=(10, 8))
+
+    assert vectors1 != vectors2
+
+    vectors2 = Vectors(shape=(10, 10))
+    assert vectors1 == vectors2
+
+    vectors1.add("hello", row=2)
+    assert vectors1 != vectors2
+
+    vectors2.add("hello", row=2)
+    assert vectors1 == vectors2
+
+    vectors1.resize((5, 9))
+    vectors2.resize((5, 9))
+    assert vectors1 == vectors2
diff --git a/spacy/vectors.pyx b/spacy/vectors.pyx
index 8300220c1..be0f6db09 100644
--- a/spacy/vectors.pyx
+++ b/spacy/vectors.pyx
@@ -243,6 +243,15 @@ cdef class Vectors:
         else:
             return key in self.key2row
 
+    def __eq__(self, other):
+        # Check for equality, with faster checks first
+        return (
+                self.shape == other.shape
+                and self.key2row == other.key2row
+                and self.to_bytes(exclude=["strings"])
+                  == other.to_bytes(exclude=["strings"])
+               )
+
     def resize(self, shape, inplace=False):
         """Resize the underlying vectors array. If inplace=True, the memory
         is reallocated. This may cause other references to the data to become

From 317b6ef99c0e3512466d31a8274f9fe6a2894355 Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Wed, 16 Nov 2022 14:09:10 +0100
Subject: [PATCH 165/174] Update to mypy 0.990 (#11801)

---
 requirements.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/requirements.txt b/requirements.txt
index d91a3b3d4..23bfa6f14 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -30,7 +30,7 @@ pytest-timeout>=1.3.0,<2.0.0
 mock>=2.0.0,<3.0.0
 flake8>=3.8.0,<6.0.0
 hypothesis>=3.27.0,<7.0.0
-mypy>=0.980,<0.990; platform_machine != "aarch64" and python_version >= "3.7"
+mypy>=0.990,<0.1000; platform_machine != "aarch64" and python_version >= "3.7"
 types-dataclasses>=0.1.3; python_version < "3.7"
 types-mock>=0.1.1
 types-setuptools>=57.0.0

From 75bb7ad541a94c74127b57ffd6d674841767478c Mon Sep 17 00:00:00 2001
From: Paul O'Leary McCann <polm@dampfkraft.com>
Date: Thu, 17 Nov 2022 18:25:01 +0900
Subject: [PATCH 166/174] Check textcat values for validity (#11763)

* Check textcat values for validity

* Fix error numbers

* Clean up vals reference

* Check category value validity through training

The _validate_categories is called in update, which for multilabel is
inherited from the single label component.

* Formatting
---
 spacy/errors.py                      |  2 ++
 spacy/pipeline/textcat.py            | 10 +++++++---
 spacy/pipeline/textcat_multilabel.py |  8 +++++++-
 spacy/tests/pipeline/test_textcat.py | 24 ++++++++++++++++++++++++
 4 files changed, 40 insertions(+), 4 deletions(-)

diff --git a/spacy/errors.py b/spacy/errors.py
index 278e5496a..1d29f0e17 100644
--- a/spacy/errors.py
+++ b/spacy/errors.py
@@ -544,6 +544,8 @@ class Errors(metaclass=ErrorsWithCodes):
             "during training, make sure to include it in 'annotating components'")
 
     # New errors added in v3.x
+    E851 = ("The 'textcat' component labels should only have values of 0 or 1, "
+            "but found value of '{val}'.")
     E852 = ("The tar file pulled from the remote attempted an unsafe path "
             "traversal.")
     E853 = ("Unsupported component factory name '{name}'. The character '.' is "
diff --git a/spacy/pipeline/textcat.py b/spacy/pipeline/textcat.py
index 4023c4456..a86eb99d2 100644
--- a/spacy/pipeline/textcat.py
+++ b/spacy/pipeline/textcat.py
@@ -293,7 +293,7 @@ class TextCategorizer(TrainablePipe):
         bp_scores(gradient)
         if sgd is not None:
             self.finish_update(sgd)
-        losses[self.name] += (gradient**2).sum()
+        losses[self.name] += (gradient ** 2).sum()
         return losses
 
     def _examples_to_truth(
@@ -327,7 +327,7 @@ class TextCategorizer(TrainablePipe):
         not_missing = self.model.ops.asarray(not_missing)  # type: ignore
         d_scores = scores - truths
         d_scores *= not_missing
-        mean_square_error = (d_scores**2).mean()
+        mean_square_error = (d_scores ** 2).mean()
         return float(mean_square_error), d_scores
 
     def add_label(self, label: str) -> int:
@@ -401,5 +401,9 @@ class TextCategorizer(TrainablePipe):
     def _validate_categories(self, examples: Iterable[Example]):
         """Check whether the provided examples all have single-label cats annotations."""
         for ex in examples:
-            if list(ex.reference.cats.values()).count(1.0) > 1:
+            vals = list(ex.reference.cats.values())
+            if vals.count(1.0) > 1:
                 raise ValueError(Errors.E895.format(value=ex.reference.cats))
+            for val in vals:
+                if not (val == 1.0 or val == 0.0):
+                    raise ValueError(Errors.E851.format(val=val))
diff --git a/spacy/pipeline/textcat_multilabel.py b/spacy/pipeline/textcat_multilabel.py
index eb83d9cb7..ef9bd6557 100644
--- a/spacy/pipeline/textcat_multilabel.py
+++ b/spacy/pipeline/textcat_multilabel.py
@@ -192,6 +192,8 @@ class MultiLabel_TextCategorizer(TextCategorizer):
             for label in labels:
                 self.add_label(label)
         subbatch = list(islice(get_examples(), 10))
+        self._validate_categories(subbatch)
+
         doc_sample = [eg.reference for eg in subbatch]
         label_sample, _ = self._examples_to_truth(subbatch)
         self._require_labels()
@@ -202,4 +204,8 @@ class MultiLabel_TextCategorizer(TextCategorizer):
     def _validate_categories(self, examples: Iterable[Example]):
         """This component allows any type of single- or multi-label annotations.
         This method overwrites the more strict one from 'textcat'."""
-        pass
+        # check that annotation values are valid
+        for ex in examples:
+            for val in ex.reference.cats.values():
+                if not (val == 1.0 or val == 0.0):
+                    raise ValueError(Errors.E851.format(val=val))
diff --git a/spacy/tests/pipeline/test_textcat.py b/spacy/tests/pipeline/test_textcat.py
index d359b77db..2eda9deaf 100644
--- a/spacy/tests/pipeline/test_textcat.py
+++ b/spacy/tests/pipeline/test_textcat.py
@@ -360,6 +360,30 @@ def test_label_types(name):
         nlp.initialize()
 
 
+@pytest.mark.parametrize(
+    "name,get_examples",
+    [
+        ("textcat", make_get_examples_single_label),
+        ("textcat_multilabel", make_get_examples_multi_label),
+    ],
+)
+def test_invalid_label_value(name, get_examples):
+    nlp = Language()
+    textcat = nlp.add_pipe(name)
+    example_getter = get_examples(nlp)
+
+    def invalid_examples():
+        # make one example with an invalid score
+        examples = example_getter()
+        ref = examples[0].reference
+        key = list(ref.cats.keys())[0]
+        ref.cats[key] = 2.0
+        return examples
+
+    with pytest.raises(ValueError):
+        nlp.initialize(get_examples=invalid_examples)
+
+
 @pytest.mark.parametrize("name", ["textcat", "textcat_multilabel"])
 def test_no_label(name):
     nlp = Language()

From a83463c5e07035ae5832e6790a0c0170e3746bd1 Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Fri, 18 Nov 2022 08:15:27 +0100
Subject: [PATCH 167/174] Add transformer recommendation for ca (#11819)

Model recommendation from @cayorodriguez.
---
 .../templates/quickstart_training_recommendations.yml    | 9 +++++++++
 1 file changed, 9 insertions(+)

diff --git a/spacy/cli/templates/quickstart_training_recommendations.yml b/spacy/cli/templates/quickstart_training_recommendations.yml
index 27945e27a..4f214d22d 100644
--- a/spacy/cli/templates/quickstart_training_recommendations.yml
+++ b/spacy/cli/templates/quickstart_training_recommendations.yml
@@ -37,6 +37,15 @@ bn:
     accuracy:
       name: sagorsarker/bangla-bert-base
       size_factor: 3
+ca:
+  word_vectors: null
+  transformer:
+    efficiency:
+      name: projecte-aina/roberta-base-ca-v2
+      size_factor: 3
+    accuracy:
+      name: projecte-aina/roberta-base-ca-v2
+      size_factor: 3
 da:
   word_vectors: da_core_news_lg
   transformer:

From e3173bd86d65a534f92578b85b0e5058a5c845f4 Mon Sep 17 00:00:00 2001
From: Paul O'Leary McCann <polm@dampfkraft.com>
Date: Fri, 18 Nov 2022 16:24:22 +0900
Subject: [PATCH 168/174] Remove spikex from Universe (#11825)

---
 website/meta/universe.json | 31 -------------------------------
 1 file changed, 31 deletions(-)

diff --git a/website/meta/universe.json b/website/meta/universe.json
index 661f5da12..57bf2d3e3 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -461,37 +461,6 @@
             },
             "category": ["standalone"]
         },
-        {
-            "id": "spikex",
-            "title": "SpikeX - SpaCy Pipes for Knowledge Extraction",
-            "slogan": "Use SpikeX to build knowledge extraction tools with almost-zero effort",
-            "description": "SpikeX is a collection of pipes ready to be plugged in a spaCy pipeline. It aims to help in building knowledge extraction tools with almost-zero effort.",
-            "github": "erre-quadro/spikex",
-            "pip": "spikex",
-            "code_example": [
-                "from spacy import load as spacy_load",
-                "from spikex.wikigraph import load as wg_load",
-                "from spikex.pipes import WikiPageX",
-                "",
-                "# load a spacy model and get a doc",
-                "nlp = spacy_load('en_core_web_sm')",
-                "doc = nlp('An apple a day keeps the doctor away')",
-                "# load a WikiGraph",
-                "wg = wg_load('simplewiki_core')",
-                "# get a WikiPageX and extract all pages",
-                "wikipagex = WikiPageX(wg)",
-                "doc = wikipagex(doc)",
-                "# see all pages extracted from the doc",
-                "for span in doc._.wiki_spans:",
-                "   print(span._.wiki_pages)"
-            ],
-            "category": ["pipeline", "standalone"],
-            "author": "Erre Quadro",
-            "author_links": {
-                "github": "erre-quadro",
-                "website": "https://www.errequadrosrl.com"
-            }
-        },
         {
             "id": "spacy-dbpedia-spotlight",
             "title": "DBpedia Spotlight for SpaCy",

From 89bfd06fbd89cc00ca2007bf795326538126f937 Mon Sep 17 00:00:00 2001
From: "github-actions[bot]"
 <41898282+github-actions[bot]@users.noreply.github.com>
Date: Fri, 18 Nov 2022 18:24:13 +0900
Subject: [PATCH 169/174] Auto-format code with black (#11826)

Co-authored-by: explosion-bot <explosion-bot@users.noreply.github.com>
---
 spacy/pipeline/textcat.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/spacy/pipeline/textcat.py b/spacy/pipeline/textcat.py
index a86eb99d2..9490e3cb1 100644
--- a/spacy/pipeline/textcat.py
+++ b/spacy/pipeline/textcat.py
@@ -293,7 +293,7 @@ class TextCategorizer(TrainablePipe):
         bp_scores(gradient)
         if sgd is not None:
             self.finish_update(sgd)
-        losses[self.name] += (gradient ** 2).sum()
+        losses[self.name] += (gradient**2).sum()
         return losses
 
     def _examples_to_truth(
@@ -327,7 +327,7 @@ class TextCategorizer(TrainablePipe):
         not_missing = self.model.ops.asarray(not_missing)  # type: ignore
         d_scores = scores - truths
         d_scores *= not_missing
-        mean_square_error = (d_scores ** 2).mean()
+        mean_square_error = (d_scores**2).mean()
         return float(mean_square_error), d_scores
 
     def add_label(self, label: str) -> int:

From f0d8309a289015ae44f994e8c0207cdfe41583ec Mon Sep 17 00:00:00 2001
From: Marco Edward Gorelli <33491632+MarcoGorelli@users.noreply.github.com>
Date: Mon, 21 Nov 2022 07:12:03 +0000
Subject: [PATCH 170/174] fix comparison of constants (#11834)

Co-authored-by: MarcoGorelli <>
---
 .pre-commit-config.yaml                     |  2 +-
 spacy/tests/vocab_vectors/test_vocab_api.py | 21 +++++++++++++++++++++
 spacy/vocab.pyx                             |  4 ++--
 3 files changed, 24 insertions(+), 3 deletions(-)

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index df59697b1..e2c5e98fd 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -5,7 +5,7 @@ repos:
     - id: black
       language_version: python3.7
       additional_dependencies: ['click==8.0.4']
--   repo: https://gitlab.com/pycqa/flake8
+-   repo: https://github.com/pycqa/flake8
     rev: 5.0.4
     hooks:
     - id: flake8
diff --git a/spacy/tests/vocab_vectors/test_vocab_api.py b/spacy/tests/vocab_vectors/test_vocab_api.py
index 16cf80a08..b9c386eb8 100644
--- a/spacy/tests/vocab_vectors/test_vocab_api.py
+++ b/spacy/tests/vocab_vectors/test_vocab_api.py
@@ -1,8 +1,13 @@
+import os
+
 import pytest
 from spacy.attrs import IS_ALPHA, LEMMA, ORTH
+from spacy.lang.en import English
 from spacy.parts_of_speech import NOUN, VERB
 from spacy.vocab import Vocab
 
+from ..util import make_tempdir
+
 
 @pytest.mark.issue(1868)
 def test_issue1868():
@@ -59,3 +64,19 @@ def test_vocab_api_contains(en_vocab, text):
 def test_vocab_writing_system(en_vocab):
     assert en_vocab.writing_system["direction"] == "ltr"
     assert en_vocab.writing_system["has_case"] is True
+
+
+def test_to_disk():
+    nlp = English()
+    with make_tempdir() as d:
+        nlp.vocab.to_disk(d)
+        assert "vectors" in os.listdir(d)
+        assert "lookups.bin" in os.listdir(d)
+
+
+def test_to_disk_exclude():
+    nlp = English()
+    with make_tempdir() as d:
+        nlp.vocab.to_disk(d, exclude=("vectors", "lookups"))
+        assert "vectors" not in os.listdir(d)
+        assert "lookups.bin" not in os.listdir(d)
diff --git a/spacy/vocab.pyx b/spacy/vocab.pyx
index 428cadd82..27f8e5f98 100644
--- a/spacy/vocab.pyx
+++ b/spacy/vocab.pyx
@@ -468,9 +468,9 @@ cdef class Vocab:
         setters = ["strings", "vectors"]
         if "strings" not in exclude:
             self.strings.to_disk(path / "strings.json")
-        if "vectors" not in "exclude":
+        if "vectors" not in exclude:
             self.vectors.to_disk(path, exclude=["strings"])
-        if "lookups" not in "exclude":
+        if "lookups" not in exclude:
             self.lookups.to_disk(path)
 
     def from_disk(self, path, *, exclude=tuple()):

From f1ddac187de7e67923e8ee63192787179f70fa4c Mon Sep 17 00:00:00 2001
From: Paul O'Leary McCann <polm@dampfkraft.com>
Date: Wed, 23 Nov 2022 18:51:31 +0900
Subject: [PATCH 171/174] Remove unused error object (#11837)

---
 spacy/language.py | 8 --------
 1 file changed, 8 deletions(-)

diff --git a/spacy/language.py b/spacy/language.py
index 836f3abf9..2789b6690 100644
--- a/spacy/language.py
+++ b/spacy/language.py
@@ -784,14 +784,6 @@ class Language:
                 factory_name, source, name=name
             )
         else:
-            if not self.has_factory(factory_name):
-                err = Errors.E002.format(
-                    name=factory_name,
-                    opts=", ".join(self.factory_names),
-                    method="add_pipe",
-                    lang=util.get_object_name(self),
-                    lang_code=self.lang,
-                )
             pipe_component = self.create_pipe(
                 factory_name,
                 name=name,

From 8271cfb4cd8a907ff11f12841ee1ceb171b3f528 Mon Sep 17 00:00:00 2001
From: Paul O'Leary McCann <polm@dampfkraft.com>
Date: Wed, 23 Nov 2022 19:03:18 +0900
Subject: [PATCH 172/174] Remove Learning Path spaCy (#11846)

---
 website/meta/universe.json | 11 -----------
 1 file changed, 11 deletions(-)

diff --git a/website/meta/universe.json b/website/meta/universe.json
index 57bf2d3e3..97b53e9c5 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -1993,17 +1993,6 @@
             },
             "category": ["books"]
         },
-        {
-            "type": "education",
-            "id": "learning-path-spacy",
-            "title": "Learning Path: Mastering spaCy for Natural Language Processing",
-            "slogan": "O'Reilly, 2017",
-            "description": "spaCy, a fast, user-friendly library for teaching computers to understand text, simplifies NLP techniques, such as speech tagging and syntactic dependencies, so you can easily extract information, attributes, and objects from massive amounts of text to then document, measure, and analyze. This Learning Path is a hands-on introduction to using spaCy to discover insights through natural language processing. While end-to-end natural language processing solutions can be complex, you’ll learn the linguistics, algorithms, and machine learning skills to get the job done.",
-            "url": "https://www.safaribooksonline.com/library/view/learning-path-mastering/9781491986653/",
-            "thumb": "https://i.imgur.com/9MIgMAc.jpg",
-            "author": "Aaron Kramer",
-            "category": ["courses"]
-        },
         {
             "type": "education",
             "id": "introduction-into-spacy-3",

From 5ea14af32b4203bc3087dec63091e63fe4ac95b7 Mon Sep 17 00:00:00 2001
From: Madeesh Kannan <shadeMe@users.noreply.github.com>
Date: Wed, 23 Nov 2022 17:54:58 +0100
Subject: [PATCH 173/174] Add `training.before_update` callback (#11739)

* Add `training.before_update` callback

This callback can be used to implement training paradigms like gradual (un)freezing of components (e.g: the Transformer) after a certain number of training steps to mitigate catastrophic forgetting during fine-tuning.

* Fix type annotation, default config value

* Generalize arguments passed to the callback

* Update schema

* Pass `epoch` to callback, rename `current_step` to `step`

* Add test

* Simplify test

* Replace config string with `spacy.blank`

* Apply suggestions from code review

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

* Cleanup imports

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
---
 spacy/default_config.cfg              |  2 ++
 spacy/schemas.py                      |  1 +
 spacy/tests/training/test_training.py | 40 ++++++++++++++++++++++++++-
 spacy/training/loop.py                |  6 ++++
 website/docs/api/data-formats.md      |  1 +
 5 files changed, 49 insertions(+), 1 deletion(-)

diff --git a/spacy/default_config.cfg b/spacy/default_config.cfg
index 86a72926e..694fb732f 100644
--- a/spacy/default_config.cfg
+++ b/spacy/default_config.cfg
@@ -90,6 +90,8 @@ dev_corpus = "corpora.dev"
 train_corpus = "corpora.train"
 # Optional callback before nlp object is saved to disk after training
 before_to_disk = null
+# Optional callback that is invoked at the start of each training step
+before_update = null
 
 [training.logger]
 @loggers = "spacy.ConsoleLogger.v1"
diff --git a/spacy/schemas.py b/spacy/schemas.py
index c824d76b9..e48fe1702 100644
--- a/spacy/schemas.py
+++ b/spacy/schemas.py
@@ -329,6 +329,7 @@ class ConfigSchemaTraining(BaseModel):
     frozen_components: List[str] = Field(..., title="Pipeline components that shouldn't be updated during training")
     annotating_components: List[str] = Field(..., title="Pipeline components that should set annotations during training")
     before_to_disk: Optional[Callable[["Language"], "Language"]] = Field(..., title="Optional callback to modify nlp object after training, before it's saved to disk")
+    before_update: Optional[Callable[["Language", Dict[str, Any]], None]] = Field(..., title="Optional callback that is invoked at the start of each training step")
     # fmt: on
 
     class Config:
diff --git a/spacy/tests/training/test_training.py b/spacy/tests/training/test_training.py
index 4384a796d..7933ea31f 100644
--- a/spacy/tests/training/test_training.py
+++ b/spacy/tests/training/test_training.py
@@ -2,6 +2,7 @@ import random
 
 import numpy
 import pytest
+import spacy
 import srsly
 from spacy.lang.en import English
 from spacy.tokens import Doc, DocBin
@@ -11,9 +12,10 @@ from spacy.training import offsets_to_biluo_tags
 from spacy.training.alignment_array import AlignmentArray
 from spacy.training.align import get_alignments
 from spacy.training.converters import json_to_docs
+from spacy.training.loop import train_while_improving
 from spacy.util import get_words_and_spaces, load_model_from_path, minibatch
 from spacy.util import load_config_from_str
-from thinc.api import compounding
+from thinc.api import compounding, Adam
 
 from ..util import make_tempdir
 
@@ -1112,3 +1114,39 @@ def test_retokenized_docs(doc):
         retokenizer.merge(doc1[0:2])
         retokenizer.merge(doc1[5:7])
     assert example.get_aligned("ORTH", as_string=True) == expected2
+
+
+def test_training_before_update(doc):
+    def before_update(nlp, args):
+        assert args["step"] == 0
+        assert args["epoch"] == 1
+
+        # Raise an error here as the rest of the loop
+        # will not run to completion due to uninitialized
+        # models.
+        raise ValueError("ran_before_update")
+
+    def generate_batch():
+        yield 1, [Example(doc, doc)]
+
+    nlp = spacy.blank("en")
+    nlp.add_pipe("tagger")
+    optimizer = Adam()
+    generator = train_while_improving(
+        nlp,
+        optimizer,
+        generate_batch(),
+        lambda: None,
+        dropout=0.1,
+        eval_frequency=100,
+        accumulate_gradient=10,
+        patience=10,
+        max_steps=100,
+        exclude=[],
+        annotating_components=[],
+        before_update=before_update,
+    )
+
+    with pytest.raises(ValueError, match="ran_before_update"):
+        for _ in generator:
+            pass
diff --git a/spacy/training/loop.py b/spacy/training/loop.py
index 06372cbb0..885257772 100644
--- a/spacy/training/loop.py
+++ b/spacy/training/loop.py
@@ -59,6 +59,7 @@ def train(
     batcher = T["batcher"]
     train_logger = T["logger"]
     before_to_disk = create_before_to_disk_callback(T["before_to_disk"])
+    before_update = T["before_update"]
 
     # Helper function to save checkpoints. This is a closure for convenience,
     # to avoid passing in all the args all the time.
@@ -89,6 +90,7 @@ def train(
         eval_frequency=T["eval_frequency"],
         exclude=frozen_components,
         annotating_components=annotating_components,
+        before_update=before_update,
     )
     clean_output_dir(output_path)
     stdout.write(msg.info(f"Pipeline: {nlp.pipe_names}") + "\n")
@@ -150,6 +152,7 @@ def train_while_improving(
     max_steps: int,
     exclude: List[str],
     annotating_components: List[str],
+    before_update: Optional[Callable[["Language", Dict[str, Any]], None]],
 ):
     """Train until an evaluation stops improving. Works as a generator,
     with each iteration yielding a tuple `(batch, info, is_best_checkpoint)`,
@@ -198,6 +201,9 @@ def train_while_improving(
     words_seen = 0
     start_time = timer()
     for step, (epoch, batch) in enumerate(train_data):
+        if before_update:
+            before_update_args = {"step": step, "epoch": epoch}
+            before_update(nlp, before_update_args)
         dropout = next(dropouts)  # type: ignore
         for subbatch in subdivide_batch(batch, accumulate_gradient):
             nlp.update(
diff --git a/website/docs/api/data-formats.md b/website/docs/api/data-formats.md
index ce06c4ea8..768844cf3 100644
--- a/website/docs/api/data-formats.md
+++ b/website/docs/api/data-formats.md
@@ -186,6 +186,7 @@ process that are used when you run [`spacy train`](/api/cli#train).
 | `accumulate_gradient`                                | Whether to divide the batch up into substeps. Defaults to `1`. ~~int~~                                                                                                                                                                                                                                                              |
 | `batcher`                                            | Callable that takes an iterator of [`Doc`](/api/doc) objects and yields batches of `Doc`s. Defaults to [`batch_by_words`](/api/top-level#batch_by_words). ~~Callable[[Iterator[Doc], Iterator[List[Doc]]]]~~                                                                                                                        |
 | `before_to_disk`                                     | Optional callback to modify `nlp` object right before it is saved to disk during and after training. Can be used to remove or reset config values or disable components. Defaults to `null`. ~~Optional[Callable[[Language], Language]]~~                                                                                           |
+| `before_update`                                      | Optional callback that is invoked at the start of each training step with the `nlp` object and a `Dict` containing the following entries: `step`, `epoch`. Can be used to make deferred changes to components. Defaults to `null`. ~~Optional[Callable[[Language, Dict[str, Any]], None]]~~                                         |
 | `dev_corpus`                                         | Dot notation of the config location defining the dev corpus. Defaults to `corpora.dev`. ~~str~~                                                                                                                                                                                                                                     |
 | `dropout`                                            | The dropout rate. Defaults to `0.1`. ~~float~~                                                                                                                                                                                                                                                                                      |
 | `eval_frequency`                                     | How often to evaluate during training (steps). Defaults to `200`. ~~int~~                                                                                                                                                                                                                                                           |

From 8f062b849c846ecdf59263c82632b9fbd4eca9d0 Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Thu, 24 Nov 2022 16:03:42 +0100
Subject: [PATCH 174/174] Fix Matcher cython profile=True header (#11867)

---
 spacy/matcher/matcher.pyx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/spacy/matcher/matcher.pyx b/spacy/matcher/matcher.pyx
index e1dba01a2..c4a057ca0 100644
--- a/spacy/matcher/matcher.pyx
+++ b/spacy/matcher/matcher.pyx
@@ -1,4 +1,4 @@
-# cython: infer_types=True, cython: profile=True
+# cython: infer_types=True, profile=True
 from typing import List, Iterable
 
 from libcpp.vector cimport vector