* Perserve flags in EntityRuler
The EntityRuler (explosion/spaCy#3526) does not preserve
overwrite flags (or `ent_id_sep`) when serialized. This
commit adds support for serialization/deserialization preserving
overwrite and ent_id_sep flags.
* add signed contributor agreement
* flake8 cleanup
mostly blank line issues.
* mark test from the issue as needing a model
The test from the issue needs some language model for serialization
but the test wasn't originally marked correctly.
* remove unneeded model loading
The model didn't need to be loaded, and I replaced it with
a change that doesn't require it (using existings fixtures)
* change tempdir handling to be compatible with python 2.7
* Adds code to handle item saved before this change.
This code chanes how the save files are handled and how the bytes
are stored as well. This code adds check to dispatch correctly
if it encounters bytes or files saved in the old format (and tests
for those cases).
* use util function for tempdir management
Updated after PR comments: this code now uses the make_tempdir function from util
instead of doing it by hand.
* initial LT lang support
* Added more stopwords. Started setting up some basic test environment (not complete)
* Initial morph rules for LT lang
* Closes#1 Adds tokenizer exceptions for Lithuanian
* Closes#5 Punctuation rules. Closes#6 Lexical Attributes
* test: add native examples to basic tests
* feat: add tag map for lt lang
* fix: remove undefined tag attribute 'Definite'
* feat: add lemmatizer for lt lang
* refactor: add new instances to lt lang morph rules; use tags from tag map
* refactor: add morph rules to lt lang defaults
* refactor: only keep nouns, verbs, adverbs and adjectives in lt lang lemmatizer lookup
* refactor: add capitalized words to lt lang lemmatizer
* refactor: add more num words to lt lang lex attrs
* refactor: update lt lang stop word set
* refactor: add new instances to lt lang tokenizer exceptions
* refactor: remove comments form lt lang init file
* refactor: use function instead of lambda in lt lex lang getter
* refactor: remove conversion to dict in lt init when dict is already provided
* chore: rename lt 'test_basic' to 'test_text'
* feat: add more lt text tests
* feat: add lemmatizer tests
* refactor: remove unused imports, add newline to end of file
* chore: add contributor agreement
* chore: change 'en' to 'lt' in lt example description
* fix: add missing encoding info
* style: add newline to end of file
* refactor: use python2 compatible syntax
* style: reformat code using black
* Adding support for entity_id in EntityRuler pipeline component
* Adding Spacy Contributor aggreement
* Updating EntityRuler to use string.format instead of f strings
* Update Entity Ruler to support an 'id' attribute per pattern that explicitly identifies an entity.
* Fixing tests
* Remove custom extension entity_id and use built in ent_id token attribute.
* Changing entity_id to ent_id for consistent naming
* entity_ids => ent_ids
* Removing kb, cleaning up tests, making util functions private, use rsplit instead of split
* Add check for empty input file to CLI pretrain
* Raise error if JSONL is not a dict or contains neither `tokens` nor `text` key
* Skip empty values for correct pretrain keys and log a counter as warning
* Add tests for CLI pretrain core function make_docs.
* Add a short hint for the `tokens` key to the CLI pretrain docs
* Add success message to CLI pretrain
* Update model loading to fix the tests
* Skip empty values and do not create docs out of it
* Add custom __dir__ to Underscore (see #3707)
* Make sure custom extension methods keep their docstrings (see #3707)
* Improve tests
* Prepend note on partial to docstring (see #3707)
* Remove print statement
* Handle cases where docstring is None
<!--- Provide a general summary of your changes in the title. -->
## Description
<!--- Use this section to describe your changes. If your changes required
testing, include information about the testing environment and the tests you
ran. If your test fixes a bug reported in an issue, don't forget to include the
issue number. If your PR is still a work in progress, that's totally fine – just
include a note to let us know. -->
Fix a bug in the test of JapaneseTokenizer.
This PR may require @polm's review.
### Types of change
<!-- What type of change does your PR cover? Is it a bug fix, an enhancement
or new feature, or a change to the documentation? -->
Bug fix
## 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.
- [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
* fix(util): fix decaying function output
* fix(util): better test and adhere to code standards
* fix(util): correct variable name, pytestify test, update website text
v2.1 introduced a regression when deserializing the parser after
parser.add_label() had been called. The code around the class mapping is
pretty confusing currently, as it was written to accommodate backwards
model compatibility. It needs to be revised when the models are next
retrained.
Closes#3433
spaCy v2.1 switched to the built-in re module, where v2.0 had been using
the third-party regex library. When the tokenizer was deserialized on
Python2.7, the `re.compile()` function was called with expressions that
featured escaped unicode codepoints that were not in Python2.7's unicode
database.
Problems occurred when we had a range between two of these unknown
codepoints, like this:
```
'[\\uAA77-\\uAA79]'
```
On Python2.7, the unknown codepoints are not unescaped correctly,
resulting in arbitrary out-of-range characters being matched by the
expression.
This problem does not occur if we instead have a range between two
unicode literals, rather than the escape sequences. To fix the bug, we
therefore add a new compat function that unescapes unicode sequences
using the `ast.literal_eval()` function. Care is taken to ensure we
do not also escape non-unicode sequences.
Closes#3356.
- [x] I have submitted the spaCy Contributor Agreement.
- [x] I ran the tests, and all new and existing tests passed.
- [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
* merging conllu/conll and conllubio scripts
* tabs to spaces
* removing conllubio2json from converters/__init__.py
* Move not-really-CLI tests to misc
* Add converter test using no-ud data
* Fix test I broke
* removing include_biluo parameter
* fixing read_conllx
* remove include_biluo from convert.py
* label in span not writable anymore
* more explicit unit test and error message for readonly label
* bit more explanation (view)
* error msg tailored to specific case
* fix None case
Closes#2091.
## Description
With the new `vocab.writing_system` property introduced in #3390 (exposed via the language defaults), I was able to finally fix this (I think!). Based on the `Doc`, dispaCy now detects whether it's a RTL or LTR language and adjusts the visualization accordingly. Wherever possible, I've also added `direction` and `lang` attributes.
Entity visualization now looks like this:
<img width="318" alt="Screenshot 2019-03-11 at 16 06 51" src="https://user-images.githubusercontent.com/13643239/54136866-d97afd80-441c-11e9-8c27-3d46994cc833.png">
And dependencies like this (ignore the most likely incorrect tags and dependencies):
<img width="621" alt="Screenshot 2019-03-11 at 16 51 59" src="https://user-images.githubusercontent.com/13643239/54137771-8b66f980-441e-11e9-8460-0682b95eef2a.png">
### Types of change
enhancement, bug fix
## 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.
- [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
* Add xfail test for vocab.writing_system
* Add vocab.writing_system property
* Set Language.Defaults.writing_system
* Set default writing system
* Remove xfail on test_vocab_writing_system
Closes#2203. Closes#3268.
Lemmas set from outside the `Morphology` class were being overwritten. The result was especially confusing when deserialising, as it meant some lemmas could change when storing and retrieving a `Doc` object.
This PR applies two fixes:
1) When we go to set the lemma in the `Morphology` class, first check whether a lemma is already set. If so, don't overwrite.
2) When we load with `doc.from_array()`, take care to apply the `TAG` field first. This allows other fields to overwrite the `TAG` implied properties, if they're provided explicitly (e.g. the `LEMMA`).
## 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.
- [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
* Make serialization methods consistent
exclude keyword argument instead of random named keyword arguments and deprecation handling
* Update docs and add section on serialization fields
* Use default return instead of else
* Add Doc.is_nered to indicate if entities have been set
* Add properties in Doc.to_json if they were set, not if they're available
This way, if a processed Doc exports "pos": None, it means that the tag was explicitly unset. If it exports "ents": [], it means that entity annotations are available but that this document doesn't contain any entities. Before, this would have been unclear and problematic for training.
* Improve handling of missing NER tags
GoldParse can accept missing NER tags, if entities is provided
in BILUO format (rather than as spans). Missing tags can be provided
as None values.
Fix bug that occurred when first tag was a None value. Closes#2603.
* Document specification of missing NER tags.
