* 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
* 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
* Adjust Table API and add docs
* Add attributes and update description [ci skip]
* Use strings.get_string_id instead of hash_string
* Fix table method calls
* Make orth arg in Lemmatizer.lookup optional
Fall back to string, which is now handled by Table.__contains__ out-of-the-box
* Fix method name
* Auto-format
Add Kannada, Tamil, and Telugu unicode blocks to uncased character
classes so that period is recognized as a suffix during tokenization.
(I'm sure a few symbols in the code blocks should not be ALPHA, but this
is mainly relevant for suffix detection and seems to be an improvement
in practice.)
Before this patch, half-width spaces between words were simply lost in
Japanese text. This wasn't immediately noticeable because much Japanese
text never uses spaces at all.
* Improve load_language_data helper
* WIP: Add Lookups implementation
* Start moving lemma data over to JSON
* WIP: move data over for more languages
* Convert more languages
* Fix lemmatizer fixtures in tests
* Finish conversion
* Auto-format JSON files
* Fix test for now
* Make sure tables are stored on instance
* Update docstrings
* Update docstrings and errors
* Update test
* Add Lookups.__len__
* Add serialization methods
* Add Lookups.remove_table
* Use msgpack for serialization to disk
* Fix file exists check
* Try using OrderedDict for everything
* Update .flake8 [ci skip]
* Try fixing serialization
* Update test_lookups.py
* Update test_serialize_vocab_strings.py
* Lookups / Tables now work
This implements the stubs in the Lookups/Table classes. Currently this
is in Cython but with no type declarations, so that could be improved.
* Add lookups to setup.py
* Actually add lookups pyx
The previous commit added the old py file...
* Lookups work-in-progress
* Move from pyx back to py
* Add string based lookups, fix serialization
* Update tests, language/lemmatizer to work with string lookups
There are some outstanding issues here:
- a pickling-related test fails due to the bloom filter
- some custom lemmatizers (fr/nl at least) have issues
More generally, there's a question of how to deal with the case where
you have a string but want to use the lookup table. Currently the table
allows access by string or id, but that's getting pretty awkward.
* Change lemmatizer lookup method to pass (orth, string)
* Fix token lookup
* Fix French lookup
* Fix lt lemmatizer test
* Fix Dutch lemmatizer
* Fix lemmatizer lookup test
This was using a normal dict instead of a Table, so checks for the
string instead of an integer key failed.
* Make uk/nl/ru lemmatizer lookup methods consistent
The mentioned tokenizers all have their own implementation of the
`lookup` method, which accesses a `Lookups` table. The way that was
called in `token.pyx` was changed so this should be updated to have the
same arguments as `lookup` in `lemmatizer.py` (specificially (orth/id,
string)).
Prior to this change tests weren't failing, but there would probably be
issues with normal use of a model. More tests should proably be added.
Additionally, the language-specific `lookup` implementations seem like
they might not be needed, since they handle things like lower-casing
that aren't actually language specific.
* Make recently added Greek method compatible
* Remove redundant class/method
Leftovers from a merge not cleaned up adequately.