Update Polish tokenizer for UD_Polish-PDB, which is a relatively major
change from the existing tokenizer. Unused exceptions files and
conflicting test cases removed.
Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
* Reduce stored lexemes data, move feats to lookups
* Move non-derivable lexemes features (`norm / cluster / prob`) to
`spacy-lookups-data` as lookups
* Get/set `norm` in both lookups and `LexemeC`, serialize in lookups
* Remove `cluster` and `prob` from `LexemesC`, get/set/serialize in
lookups only
* Remove serialization of lexemes data as `vocab/lexemes.bin`
* Remove `SerializedLexemeC`
* Remove `Lexeme.to_bytes/from_bytes`
* Modify normalization exception loading:
* Always create `Vocab.lookups` table `lexeme_norm` for
normalization exceptions
* Load base exceptions from `lang.norm_exceptions`, but load
language-specific exceptions from lookups
* Set `lex_attr_getter[NORM]` including new lookups table in
`BaseDefaults.create_vocab()` and when deserializing `Vocab`
* Remove all cached lexemes when deserializing vocab to override
existing normalizations with the new normalizations (as a replacement
for the previous step that replaced all lexemes data with the
deserialized data)
* Skip English normalization test
Skip English normalization test because the data is now in
`spacy-lookups-data`.
* Remove norm exceptions
Moved to spacy-lookups-data.
* Move norm exceptions test to spacy-lookups-data
* Load extra lookups from spacy-lookups-data lazily
Load extra lookups (currently for cluster and prob) lazily from the
entry point `lg_extra` as `Vocab.lookups_extra`.
* Skip creating lexeme cache on load
To improve model loading times, do not create the full lexeme cache when
loading. The lexemes will be created on demand when processing.
* Identify numeric values in Lexeme.set_attrs()
With the removal of a special case for `PROB`, also identify `float` to
avoid trying to convert it with the `StringStore`.
* Skip lexeme cache init in from_bytes
* Unskip and update lookups tests for python3.6+
* Update vocab pickle to include lookups_extra
* Update vocab serialization tests
Check strings rather than lexemes since lexemes aren't initialized
automatically, account for addition of "_SP".
* Re-skip lookups test because of python3.5
* Skip PROB/float values in Lexeme.set_attrs
* Convert is_oov from lexeme flag to lex in vectors
Instead of storing `is_oov` as a lexeme flag, `is_oov` reports whether
the lexeme has a vector.
Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
* Limiting noun_chunks for specific langauges
* Limiting noun_chunks for specific languages
Contributor Agreement
* Addressing review comments
* Removed unused fixtures and imports
* Add fa_tokenizer in test suite
* Use fa_tokenizer in test
* Undo extraneous reformatting
Co-authored-by: adrianeboyd <adrianeboyd@gmail.com>
Remove `TAG` value from Danish and Swedish tokenizer exceptions because
it may not be included in a tag map (and these settings are problematic
as tokenizer exceptions anyway).
Instead of treating `'d` in contractions like `I'd` as `would` in all
cases in the tokenizer exceptions, leave the tagging and lemmatization
up to later components.
To fix the slow tokenizer URL (#4374) and allow `token_match` to take
priority over prefixes and suffixes by default, introduce a new
tokenizer option for a token match pattern that's applied after prefixes
and suffixes but before infixes.
Modify jieba install message to instruct the user to use
`ChineseDefaults.use_jieba = False` so that it's possible to load
pkuseg-only models without jieba installed.
* Add pkuseg and serialization support for Chinese
Add support for pkuseg alongside jieba
* Specify model through `Language` meta:
* split on characters (if no word segmentation packages are installed)
```
Chinese(meta={"tokenizer": {"config": {"use_jieba": False, "use_pkuseg": False}}})
```
* jieba (remains the default tokenizer if installed)
```
Chinese()
Chinese(meta={"tokenizer": {"config": {"use_jieba": True}}}) # explicit
```
* pkuseg
```
Chinese(meta={"tokenizer": {"config": {"pkuseg_model": "default", "use_jieba": False, "use_pkuseg": True}}})
```
* The new tokenizer setting `require_pkuseg` is used to override
`use_jieba` default, which is intended for models that provide a pkuseg
model:
```
nlp_pkuseg = Chinese(meta={"tokenizer": {"config": {"pkuseg_model": "default", "require_pkuseg": True}}})
nlp = Chinese() # has `use_jieba` as `True` by default
nlp.from_bytes(nlp_pkuseg.to_bytes()) # `require_pkuseg` overrides `use_jieba` when calling the tokenizer
```
Add support for serialization of tokenizer settings and pkuseg model, if
loaded
* Add sorting for `Language.to_bytes()` serialization of `Language.meta`
so that the (emptied, but still present) tokenizer metadata is in a
consistent position in the serialized data
Extend tests to cover all three tokenizer configurations and
serialization
* Fix from_disk and tests without jieba or pkuseg
* Load cfg first and only show error if `use_pkuseg`
* Fix blank/default initialization in serialization tests
* Explicitly initialize jieba's cache on init
* Add serialization for pkuseg pre/postprocessors
* Reformat pkuseg install message
* Use inline flags in token_match patterns
Use inline flags in `token_match` patterns so that serializing does not
lose the flag information.
* Modify inline flag
* Modify inline flag
* Revert changes to priority of `token_match` so that it has priority
over all other tokenizer patterns
* Add lookahead and potentially slow lookbehind back to the default URL
pattern
* Expand character classes in URL pattern to improve matching around
lookaheads and lookbehinds related to #4882
* Revert changes to Hungarian tokenizer
* Revert (xfail) several URL tests to their status before #4374
* Update `tokenizer.explain()` and docs accordingly
* Fix german stop words
Two stop words ("einige" and "einigen") are sticking together.
Remove three nouns that may serve as stop words in a specific context (e.g. religious or news) but are not applicable for general use.
* Create Jan-711.md
* Rename `tag_map.py` to `tag_map_fine.py` to indicate that it's not the
default tag map
* Remove duplicate generic UD tag map and load `../tag_map.py` instead
* don't split on a colon. Colon is used to attach suffixes for abbreviations
* tokenize on any of LIST_HYPHENS (except a single hyphen), not just on --
* simplify infix rules by merging similar rules
* Add correct stopwords for Slovak language
* Add SNK Tags
* Disable formatting lint for TAGS
* Add example sentences for Slovak language
* Add slovak numerals in base form
* Add lex_attrs to sk init
* Add contributor agreement
* Restructure tag maps for MorphAnalysis changes
Prepare tag maps for upcoming MorphAnalysis changes that allow
arbritrary features.
* Use default tag map rather than duplicating for ca / uk / vi
* Import tag map into defaults for ga
* Modify tag maps so all morphological fields and features are strings
* Move features from `"Other"` to the top level
* Rewrite tuples as strings separated by `","`
* Rewrite morph symbols for fr lemmatizer as strings
* Export MorphAnalysis under spacy.tokens
* Modify morphology to support arbitrary features
Modify `Morphology` and `MorphAnalysis` so that arbitrary features are
supported.
* Modify `MorphAnalysisC` so that it can support arbitrary features and
multiple values per field. `MorphAnalysisC` is redesigned to contain:
* key: hash of UD FEATS string of morphological features
* array of `MorphFeatureC` structs that each contain a hash of `Field`
and `Field=Value` for a given morphological feature, which makes it
possible to:
* find features by field
* represent multiple values for a given field
* `get_field()` is renamed to `get_by_field()` and is no longer `nogil`.
Instead a new helper function `get_n_by_field()` is `nogil` and returns
`n` features by field.
* `MorphAnalysis.get()` returns all possible values for a field as a
list of individual features such as `["Tense=Pres", "Tense=Past"]`.
* `MorphAnalysis`'s `str()` and `repr()` are the UD FEATS string.
* `Morphology.feats_to_dict()` converts a UD FEATS string to a dict
where:
* Each field has one entry in the dict
* Multiple values remain separated by a separator in the value string
* `Token.morph_` returns the UD FEATS string and you can set
`Token.morph_` with a UD FEATS string or with a tag map dict.
* Modify get_by_field to use np.ndarray
Modify `get_by_field()` to use np.ndarray. Remove `max_results` from
`get_n_by_field()` and always iterate over all the fields.
* Rewrite without MorphFeatureC
* Add shortcut for existing feats strings as keys
Add shortcut for existing feats strings as keys in `Morphology.add()`.
* Check for '_' as empty analysis when adding morphs
* Extend helper converters in Morphology
Add and extend helper converters that convert and normalize between:
* UD FEATS strings (`"Case=dat,gen|Number=sing"`)
* per-field dict of feats (`{"Case": "dat,gen", "Number": "sing"}`)
* list of individual features (`["Case=dat", "Case=gen",
"Number=sing"]`)
All converters sort fields and values where applicable.
* match domains longer than `hostname.domain.tld` like `www.foo.co.uk`
* expand allowed characters in domain names while only matching
lowercase TLDs so that "this.That" isn't matched as a URL and can be
split on the period as an infix (relevant for at least English, German,
and Tatar)
* Adding Support for Yoruba
* test text
* Updated test string.
* Fixing encoding declaration.
* Adding encoding to stop_words.py
* Added contributor agreement and removed iranlowo.
* Added removed test files and removed iranlowo to keep project bare.
* Returned CONTRIBUTING.md to default state.
* Added delted conftest entries
* Tidy up and auto-format
* Revert CONTRIBUTING.md
Co-authored-by: Ines Montani <ines@ines.io>
* Enable lex_attrs on Finnish
* Copy the Danish tokenizer rules to Finnish
Specifically, don't break hyphenated compound words
* Contributor agreement
* A new file for Finnish tokenizer rules instead of including the Danish ones
- added some tests for tokenization issues
- fixed some issues with tokenization of words with hyphen infix
- rewrote the "tokenizer_exceptions.py" file (stemming from the German version)
* Switch from mecab-python3 to fugashi
mecab-python3 has been the best MeCab binding for a long time but it's
not very actively maintained, and since it's based on old SWIG code
distributed with MeCab there's a limit to how effectively it can be
maintained.
Fugashi is a new Cython-based MeCab wrapper I wrote. Since it's not
based on the old SWIG code it's easier to keep it current and make small
deviations from the MeCab C/C++ API where that makes sense.
* Change mecab-python3 to fugashi in setup.cfg
* Change "mecab tags" to "unidic tags"
The tags come from MeCab, but the tag schema is specified by Unidic, so
it's more proper to refer to it that way.
* Update conftest
* Add fugashi link to external deps list for Japanese
* Generalize handling of tokenizer special cases
Handle tokenizer special cases more generally by using the Matcher
internally to match special cases after the affix/token_match
tokenization is complete.
Instead of only matching special cases while processing balanced or
nearly balanced prefixes and suffixes, this recognizes special cases in
a wider range of contexts:
* Allows arbitrary numbers of prefixes/affixes around special cases
* Allows special cases separated by infixes
Existing tests/settings that couldn't be preserved as before:
* The emoticon '")' is no longer a supported special case
* The emoticon ':)' in "example:)" is a false positive again
When merged with #4258 (or the relevant cache bugfix), the affix and
token_match properties should be modified to flush and reload all
special cases to use the updated internal tokenization with the Matcher.
* Remove accidentally added test case
* Really remove accidentally added test
* Reload special cases when necessary
Reload special cases when affixes or token_match are modified. Skip
reloading during initialization.
* Update error code number
* Fix offset and whitespace in Matcher special cases
* Fix offset bugs when merging and splitting tokens
* Set final whitespace on final token in inserted special case
* Improve cache flushing in tokenizer
* Separate cache and specials memory (temporarily)
* Flush cache when adding special cases
* Repeated `self._cache = PreshMap()` and `self._specials = PreshMap()`
are necessary due to this bug:
https://github.com/explosion/preshed/issues/21
* Remove reinitialized PreshMaps on cache flush
* Update UD bin scripts
* Update imports for `bin/`
* Add all currently supported languages
* Update subtok merger for new Matcher validation
* Modify blinded check to look at tokens instead of lemmas (for corpora
with tokens but not lemmas like Telugu)
* Use special Matcher only for cases with affixes
* Reinsert specials cache checks during normal tokenization for special
cases as much as possible
* Additionally include specials cache checks while splitting on infixes
* Since the special Matcher needs consistent affix-only tokenization
for the special cases themselves, introduce the argument
`with_special_cases` in order to do tokenization with or without
specials cache checks
* After normal tokenization, postprocess with special cases Matcher for
special cases containing affixes
* Replace PhraseMatcher with Aho-Corasick
Replace PhraseMatcher with the Aho-Corasick algorithm over numpy arrays
of the hash values for the relevant attribute. The implementation is
based on FlashText.
The speed should be similar to the previous PhraseMatcher. It is now
possible to easily remove match IDs and matches don't go missing with
large keyword lists / vocabularies.
Fixes#4308.
* Restore support for pickling
* Fix internal keyword add/remove for numpy arrays
* Add test for #4248, clean up test
* Improve efficiency of special cases handling
* Use PhraseMatcher instead of Matcher
* Improve efficiency of merging/splitting special cases in document
* Process merge/splits in one pass without repeated token shifting
* Merge in place if no splits
* Update error message number
* Remove UD script modifications
Only used for timing/testing, should be a separate PR
* Remove final traces of UD script modifications
* Update UD bin scripts
* Update imports for `bin/`
* Add all currently supported languages
* Update subtok merger for new Matcher validation
* Modify blinded check to look at tokens instead of lemmas (for corpora
with tokens but not lemmas like Telugu)
* Add missing loop for match ID set in search loop
* Remove cruft in matching loop for partial matches
There was a bit of unnecessary code left over from FlashText in the
matching loop to handle partial token matches, which we don't have with
PhraseMatcher.
* Replace dict trie with MapStruct trie
* Fix how match ID hash is stored/added
* Update fix for match ID vocab
* Switch from map_get_unless_missing to map_get
* Switch from numpy array to Token.get_struct_attr
Access token attributes directly in Doc instead of making a copy of the
relevant values in a numpy array.
Add unsatisfactory warning for hash collision with reserved terminal
hash key. (Ideally it would change the reserved terminal hash and redo
the whole trie, but for now, I'm hoping there won't be collisions.)
* Restructure imports to export find_matches
* Implement full remove()
Remove unnecessary trie paths and free unused maps.
Parallel to Matcher, raise KeyError when attempting to remove a match ID
that has not been added.
* Switch to PhraseMatcher.find_matches
* Switch to local cdef functions for span filtering
* Switch special case reload threshold to variable
Refer to variable instead of hard-coded threshold
* Move more of special case retokenize to cdef nogil
Move as much of the special case retokenization to nogil as possible.
* Rewrap sort as stdsort for OS X
* Rewrap stdsort with specific types
* Switch to qsort
* Fix merge
* Improve cmp functions
* Fix realloc
* Fix realloc again
* Initialize span struct while retokenizing
* Temporarily skip retokenizing
* Revert "Move more of special case retokenize to cdef nogil"
This reverts commit 0b7e52c797.
* Revert "Switch to qsort"
This reverts commit a98d71a942.
* Fix specials check while caching
* Modify URL test with emoticons
The multiple suffix tests result in the emoticon `:>`, which is now
retokenized into one token as a special case after the suffixes are
split off.
* Refactor _apply_special_cases()
* Use cdef ints for span info used in multiple spots
* Modify _filter_special_spans() to prefer earlier
Parallel to #4414, modify _filter_special_spans() so that the earlier
span is preferred for overlapping spans of the same length.
* Replace MatchStruct with Entity
Replace MatchStruct with Entity since the existing Entity struct is
nearly identical.
* Replace Entity with more general SpanC
* Replace MatchStruct with SpanC
* Add error in debug-data if no dev docs are available (see #4575)
* Update azure-pipelines.yml
* Revert "Update azure-pipelines.yml"
This reverts commit ed1060cf59.
* Use latest wasabi
* Reorganise install_requires
* add dframcy to universe.json (#4580)
* Update universe.json [ci skip]
* Fix multiprocessing for as_tuples=True (#4582)
* Fix conllu script (#4579)
* force extensions to avoid clash between example scripts
* fix arg order and default file encoding
* add example config for conllu script
* newline
* move extension definitions to main function
* few more encodings fixes
* Add load_from_docbin example [ci skip]
TODO: upload the file somewhere
* Update README.md
* Add warnings about 3.8 (resolves#4593) [ci skip]
* Fixed typo: Added space between "recognize" and "various" (#4600)
* Fix DocBin.merge() example (#4599)
* Replace function registries with catalogue (#4584)
* Replace functions registries with catalogue
* Update __init__.py
* Fix test
* Revert unrelated flag [ci skip]
* Bugfix/dep matcher issue 4590 (#4601)
* add contributor agreement for prilopes
* add test for issue #4590
* fix on_match params for DependencyMacther (#4590)
* Minor updates to language example sentences (#4608)
* Add punctuation to Spanish example sentences
* Combine multilanguage examples for lang xx
* Add punctuation to nb examples
* Always realloc to a larger size
Avoid potential (unlikely) edge case and cymem error seen in #4604.
* Add error in debug-data if no dev docs are available (see #4575)
* Update debug-data for GoldCorpus / Example
* Ignore None label in misaligned NER data
* Rework Chinese language initialization
* Create a `ChineseTokenizer` class
* Modify jieba post-processing to handle whitespace correctly
* Modify non-jieba character tokenization to handle whitespace correctly
* Add a `create_tokenizer()` method to `ChineseDefaults`
* Load lexical attributes
* Update Chinese tag_map for UD v2
* Add very basic Chinese tests
* Test tokenization with and without jieba
* Test `like_num` attribute
* Fix try_jieba_import()
* Fix zh code formatting
* Update English tag_map
Update English tag_map based on this conversion table:
https://universaldependencies.org/tagset-conversion/en-penn-uposf.html
* Update German tag_map
Update German tag_map based on this conversion table:
https://universaldependencies.org/tagset-conversion/de-stts-uposf.html
* Add missing Tiger dependencies to glossary
* Add quotes to definition of TO
* Update POS/TAG tables in docs
Update POS/TAG tables for English and German docs using current
information generated from the tag_maps and GLOSSARY.
* Update warning that -PRON- is specific to English
* Revert docs to default JSON output with convert
* Revert "Revert docs to default JSON output with convert"
This reverts commit 6b78c048f1.
* Create syntax_iterators.py
Replica of spacy/lang/fr/syntax_iterators.py
* Added import statements for SYNTAX_ITERATORS
* Create gustavengstrom.md
* Added "dobj" to list of labels in noun_chunks method and a test_noun_chunks method to the Swedish language model.
* Delete README-checkpoint.md
Co-authored-by: Gustav <gustav@davcon.se>
Co-authored-by: Ines Montani <ines@ines.io>
* Move prefix and suffix detection for URL_PATTERN
Move prefix and suffix detection for `URL_PATTERN` into the tokenizer.
Remove associated lookahead and lookbehind from `URL_PATTERN`.
Fix tokenization for Hungarian given new modified handling of prefixes
and suffixes.
* Match a wider range of URI schemes
* Move test
* Allow default in Lookups.get_table
* Start with blank tables in Lookups.from_bytes
* Refactor lemmatizer to hold instance of Lookups
* Get lookups table within the lemmatization methods to make sure it references the correct table (even if the table was replaced or modified, e.g. when loading a model from disk)
* Deprecate other arguments on Lemmatizer.__init__ and expect Lookups for consistency
* Remove old and unsupported Lemmatizer.load classmethod
* Refactor language-specific lemmatizers to inherit as much as possible from base class and override only what they need
* Update tests and docs
* Fix more tests
* Fix lemmatizer
* Upgrade pytest to try and fix weird CI errors
* Try pytest 4.6.5
* Add default to util.get_entry_point
* Tidy up entry points
* Read lookups from entry points
* Remove lookup tables and related tests
* Add lookups install option
* Remove lemmatizer tests
* Remove logic to process language data files
* Update setup.cfg
