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

@@ -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"]

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}

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()
+)

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)

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

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"

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())

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).                                                                             |