* Update universe.json
added classy-classification to Spacy universe
* Update universe.json
added classy-classification to the spacy universe resources
* Update universe.json
corrected a small typo in json
* Update website/meta/universe.json
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Update website/meta/universe.json
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Update website/meta/universe.json
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Update universe.json
processed merge feedback
* Update universe.json
* updated information for Classy Classificaiton
Made a more comprehensible and easy description for Classy Classification based on feedback of Philip Vollet to prepare for sharing.
* added note about examples
* corrected for wrong formatting changes
* Update website/meta/universe.json with small typo correction
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* resolved another typo
* Update website/meta/universe.json
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* added Concise Concepts package to spaCy universe.
* updated example code Concise Concepts
* updated description for Concise Concepts
* updated PR with more visually appealing examples
SO to koaning for the suggestions.
* corrected for small json typo's in concise concepts
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Update universe.json
added classy-classification to Spacy universe
* Update universe.json
added classy-classification to the spacy universe resources
* Update universe.json
corrected a small typo in json
* Update website/meta/universe.json
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Update website/meta/universe.json
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Update website/meta/universe.json
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
* Update universe.json
processed merge feedback
* Update universe.json
* updated information for Classy Classificaiton
Made a more comprehensible and easy description for Classy Classification based on feedback of Philip Vollet to prepare for sharing.
* added note about examples
* corrected for wrong formatting changes
* Update website/meta/universe.json with small typo correction
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* resolved another typo
* Update website/meta/universe.json
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Add github actions for slow and gpu tests
* change weekly GPU tests to also run slow tests, and change the time
* only run the tests if there were commits in the past day
* remove duplicate line
* add sent start/end token attributes to the docs
* let has_annotation work with IS_SENT_END
* elif instead of if
* add has_annotation test for sent attributes
* fix typo
* remove duplicate is_sent_start entry in docs
* Setup debug data for spancat
* Add check for missing labels
* Add low-level data warning error
* Improve logic when compiling the gold train data
* Implement check for negative examples
* Remove breakpoint
* Remove ws_ents and missing entity checks
* Fix mypy errors
* Make variable name spans_key consistent
* Rename pipeline -> component for consistency
* Account for missing labels per spans_key
* Cleanup variable names for consistency
* Improve brevity of conditional statements
* Remove unused variables
* Include spans_key as an argument for _get_examples
* Add a conditional check for spans_key
* Update spancat debug data based on new API
- Instead of using _get_labels_from_model(), I'm now using
_get_labels_from_spancat() (cf. https://github.com/explosion/spaCy/pull10079)
- The way information is displayed was also changed (text -> table)
* Rename model_labels to ensure mypy works
* Update wording on warning messages
Use "span type" instead of "entity type" in wording the warning messages.
This is because Spans aren't necessarily entities.
* Update component type into a Literal
This is to make it clear that the component parameter should only accept
either 'spancat' or 'ner'.
* Update checks to include actual model span_keys
Instead of looking at everything in the data, we only check those
span_keys from the actual spancat component. Instead of doing the filter
inside the for-loop, I just made another dictionary,
data_labels_in_component to hold this value.
* Update spacy/cli/debug_data.py
* Show label counts only when verbose is True
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Fix debug data check for ents that cross sents
* Use aligned sent starts to have the same indices for the NER and sent
start annotation
* Add a temporary, insufficient hack for the case where a
sentence-initial reference token is split into multiple tokens in the
predicted doc, since `Example.get_aligned("SENT_START")` currently
aligns `True` to all the split tokens.
* Improve test example
* Use Example.get_aligned_sent_starts
* Add test for crossing entity
* Auto-format code with black
* add black requirement to dev dependencies and pin to 22.x
* ignore black dependency for comparison with setup.cfg
Co-authored-by: explosion-bot <explosion-bot@users.noreply.github.com>
Co-authored-by: svlandeg <svlandeg@github.com>
So that overriding `paths.vectors` works consistently in generated
configs, set vectors model in `paths.vectors` and always refer to this
path in `initialize.vectors`.
* Added spacy-wrap to universe
Added spacy-wrap to universe a small package for wrapping fine-tuned huggingface transformers to a spacy pipeline following the same API as spacy-transformers. (Currently limited to classification models)
* Update website/meta/universe.json
* Update website/meta/universe.json
* Update website/meta/universe.json
* Update website/meta/universe.json
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Added spacy-wrap to universe
Added spacy-wrap to universe a small package for wrapping fine-tuned huggingface transformers to a spacy pipeline following the same API as spacy-transformers. (Currently limited to classification models)
* Update website/meta/universe.json
* Update website/meta/universe.json
* Update website/meta/universe.json
* Update website/meta/universe.json
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Clarify Span.ents documentation
Ref: #10135
Retain current behaviour. Span.ents will only include entities within
said span. You can't get tokens outside of the original span.
* Reword docstrings
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Update API docs in the website
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Clarify Span.ents documentation
Ref: #10135
Retain current behaviour. Span.ents will only include entities within
said span. You can't get tokens outside of the original span.
* Reword docstrings
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* Update API docs in the website
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
* This comma has been most probably been left out unintentionally, leading to string concatenation between the two consecutive lines. This issue has been found automatically using a regular expression.
* This comma has been most probably been left out unintentionally, leading to string concatenation between the two consecutive lines. This issue has been found automatically using a regular expression.
* Fix infix as prefix in Tokenizer.explain
Update `Tokenizer.explain` to align with the `Tokenizer` algorithm:
* skip infix matches that are prefixes in the current substring
* Update tokenizer pseudocode in docs
* Improve typing hints for Matcher.__call__
* Add typing hints for DependencyMatcher
* Add typing hints to underscore extensions
* Update Doc.tensor type (requires numpy 1.21)
* Fix typing hints for Language.component decorator
* Use generic np.ndarray type in Doc to avoid numpy version update
* Fix mypy errors
* Fix cyclic import caused by Underscore typing hints
* Use Literal type from spacy.compat
* Update matcher.pyi import format
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Instead of the running the actual suggester, which may require
annotation from annotating components that is not necessarily present in
the reference docs, use the built-in 1-gram suggester.
