* Exceptions for single letter words ending sentence
Sentences ending in "i." (as in "... peka i."), "m." (as in "...än 2000 m."), should be tokenized as two separate tokens.
* Add test
## Description
Related issues: #2379 (should be fixed by separating model tests)
* **total execution time down from > 300 seconds to under 60 seconds** 🎉
* removed all model-specific tests that could only really be run manually anyway – those will now live in a separate test suite in the [`spacy-models`](https://github.com/explosion/spacy-models) repository and are already integrated into our new model training infrastructure
* changed all relative imports to absolute imports to prepare for moving the test suite from `/spacy/tests` to `/tests` (it'll now always test against the installed version)
* merged old regression tests into collections, e.g. `test_issue1001-1500.py` (about 90% of the regression tests are very short anyways)
* tidied up and rewrote existing tests wherever possible
### Todo
- [ ] move tests to `/tests` and adjust CI commands accordingly
- [x] move model test suite from internal repo to `spacy-models`
- [x] ~~investigate why `pipeline/test_textcat.py` is flakey~~
- [x] review old regression tests (leftover files) and see if they can be merged, simplified or deleted
- [ ] update documentation on how to run tests
### Types of change
enhancement, tests
## Checklist
<!--- Before you submit the PR, go over this checklist and make sure you can
tick off all the boxes. [] -> [x] -->
- [x] I have submitted the spaCy Contributor Agreement.
- [x] I ran the tests, and all new and existing tests passed.
- [ ] My changes don't require a change to the documentation, or if they do, I've added all required information.
* Add Romanian lemmatizer lookup table.
Adapted from http://www.lexiconista.com/datasets/lemmatization/
by replacing cedillas with commas (ș and ț).
The original dataset is licensed under the Open Database License.
* Fix one blatant issue in the Romanian lemmatizer
* Romanian examples file
* Add ro_tokenizer in conftest
* Add Romanian lemmatizer test
* Port Japanese mecab tokenizer from v1
This brings the Mecab-based Japanese tokenization introduced in #1246 to
spaCy v2. There isn't a JapaneseTagger implementation yet, but POS tag
information from Mecab is stored in a token extension. A tag map is also
included.
As a reminder, Mecab is required because Universal Dependencies are
based on Unidic tags, and Janome doesn't support Unidic.
Things to check:
1. Is this the right way to use a token extension?
2. What's the right way to implement a JapaneseTagger? The approach in
#1246 relied on `tag_from_strings` which is just gone now. I guess the
best thing is to just try training spaCy's default Tagger?
-POLM
* Add tagging/make_doc and tests
