* Add "whatlies"
We're releasing it on our side officially on the 16th of April. If possible, let's announce around the same time :)
* sign contributor thing
* Added fancy gif
as the image
* Update universe.json
Spellin error and spaCy clarification.
* 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
* document token ent_kb_id
* document span kb_id
* update pipeline documentation
* prior and context weights as bool's instead
* entitylinker api documentation
* drop for both models
* finish entitylinker documentation
* small fixes
* documentation for KB
* candidate documentation
* links to api pages in code
* small fix
* frequency examples as counts for consistency
* consistent documentation about tensors returned by predict
* add entity linking to usage 101
* add entity linking infobox and KB section to 101
* entity-linking in linguistic features
* small typo corrections
* training example and docs for entity_linker
* predefined nlp and kb
* revert back to similarity encodings for simplicity (for now)
* set prior probabilities to 0 when excluded
* code clean up
* bugfix: deleting kb ID from tokens when entities were removed
* refactor train el example to use either model or vocab
* pretrain_kb example for example kb generation
* add to training docs for KB + EL example scripts
* small fixes
* error numbering
* ensure the language of vocab and nlp stay consistent across serialization
* equality with =
* avoid conflict in errors file
* add error 151
* final adjustements to the train scripts - consistency
* update of goldparse documentation
* small corrections
* push commit
* typo fix
* add candidate API to kb documentation
* update API sidebar with EntityLinker and KnowledgeBase
* remove EL from 101 docs
* remove entity linker from 101 pipelines / rephrase
* custom el model instead of existing model
* set version to 2.2 for EL functionality
* update documentation for 2 CLI scripts
* Added RONEC to spaCy Universe
* Added contributor file
* Corrected date from .github/contributors/avramandrei.md
* Convert tabs to spaces
* Remove duplicate keys
Can only have one GitHub link unfortunately
* Also add models category
* Adjust ID
This is used to generate the URL, so a simpler string is better
* Add entry for Blackstone in universe.json
Add an entry for the Blackstone project. Checked JSON is valid.
* Create ICLRandD.md
* Fix indentation (tabs to spaces)
It looks like during validation, the JSON file automatically changed spaces to tabs. This caused the diff to show *everything* as changed, which is obviously not true. This hopefully fixes that.
* Try to fix formatting for diff
* Fix diff
Co-authored-by: Ines Montani <ines@ines.io>
* Typo fix for AllenAI url
Changed incorrect home page url for AllenAI from appenai.org to allenai.org
* Sign contributor agreement
* Change date format
* Request to add Holmes to spaCy Universe
Dear spaCy team, I would be grateful if you would consider my Python library Holmes for inclusion in the spaCy Universe. Holmes transforms the syntactic structures delivered by spaCy into semantic structures that, together with various other techniques including ontological matching and word embeddings, serve as the basis for information extraction. Holmes supports several use cases including chatbot, structured search, topic matching and supervised document classification. I had the basic idea for Holmes around 15 years ago and now spaCy has made it possible to build an implementation that is stable and fast enough to actually be of use - thank you! At present Holmes supports English and German (I am based in Munich) but could easily be extended to support any other language with a spaCy model.
* Added
As discussed with Ines in https://github.com/explosion/spaCy/issues/3568 , adding a new project proposal for the community in SpaCy Universe website
GracyQL a tiny graphql wrapper aroung spacy using graphene and starlette.
## Description
Change only in universe.json file to add a new project
### Types of change
New project reference in Universe
## Checklist
- [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.
