* Allow copying the user_data with as_doc + unit test
* add option to docs
* add typing
* import fix
* workaround to avoid bool clashing ...
* bint instead of bool
* Updates/bugfixes for NER/IOB converters
* Converter formats `ner` and `iob` use autodetect to choose a converter if
possible
* `iob2json` is reverted to handle sentence-per-line data like
`word1|pos1|ent1 word2|pos2|ent2`
* Fix bug in `merge_sentences()` so the second sentence in each batch isn't
skipped
* `conll_ner2json` is made more general so it can handle more formats with
whitespace-separated columns
* Supports all formats where the first column is the token and the final
column is the IOB tag; if present, the second column is the POS tag
* As in CoNLL 2003 NER, blank lines separate sentences, `-DOCSTART- -X- O O`
separates documents
* Add option for segmenting sentences (new flag `-s`)
* Parser-based sentence segmentation with a provided model, otherwise with
sentencizer (new option `-b` to specify model)
* Can group sentences into documents with `n_sents` as long as sentence
segmentation is available
* Only applies automatic segmentation when there are no existing delimiters
in the data
* Provide info about settings applied during conversion with warnings and
suggestions if settings conflict or might not be not optimal.
* Add tests for common formats
* Add '(default)' back to docs for -c auto
* Add document count back to output
* Revert changes to converter output message
* Use explicit tabs in convert CLI test data
* Adjust/add messages for n_sents=1 default
* Add sample NER data to training examples
* Update README
* Add links in docs to example NER data
* Define msg within converters
* Fix typo in rule-based matching docs
* Improve token pattern checking without validation
Add more detailed token pattern checks without full JSON pattern validation and
provide more detailed error messages.
Addresses #4070 (also related: #4063, #4100).
* Check whether top-level attributes in patterns and attr for PhraseMatcher are
in token pattern schema
* Check whether attribute value types are supported in general (as opposed to
per attribute with full validation)
* Report various internal error types (OverflowError, AttributeError, KeyError)
as ValueError with standard error messages
* Check for tagger/parser in PhraseMatcher pipeline for attributes TAG, POS,
LEMMA, and DEP
* Add error messages with relevant details on how to use validate=True or nlp()
instead of nlp.make_doc()
* Support attr=TEXT for PhraseMatcher
* Add NORM to schema
* Expand tests for pattern validation, Matcher, PhraseMatcher, and EntityRuler
* Remove unnecessary .keys()
* Rephrase error messages
* Add another type check to Matcher
Add another type check to Matcher for more understandable error messages
in some rare cases.
* Support phrase_matcher_attr=TEXT for EntityRuler
* Don't use spacy.errors in examples and bin scripts
* Fix error code
* Auto-format
Also try get Azure pipelines to finally start a build :(
* Update errors.py
Co-authored-by: Ines Montani <ines@ines.io>
Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
* add `words`
* update name of entity list to `ner`
I think it might be a bit more consistent to have `ner` named `entities`
or `ents` (and `ents` is actually set somewhere to `None`, which is a
bit confusing), but it looks like renaming it would be a non-trivial
decision.
