Commit Graph

43 Commits

Author SHA1 Message Date
svlandeg
1de61f68d6 improve speed of prediction loop 2019-06-26 13:53:10 +02:00
svlandeg
58a5b40ef6 clean up duplicate code 2019-06-24 15:19:58 +02:00
svlandeg
b58bace84b small fixes 2019-06-24 10:55:04 +02:00
svlandeg
cc9ae28a52 custom error and warning messages 2019-06-19 12:35:26 +02:00
svlandeg
791327e3c5 Merge remote-tracking branch 'upstream/master' into feature/nel-wiki 2019-06-19 09:44:05 +02:00
svlandeg
a31648d28b further code cleanup 2019-06-19 09:15:43 +02:00
svlandeg
478305cd3f small tweaks and documentation 2019-06-18 18:38:09 +02:00
svlandeg
0d177c1146 clean up code, remove old code, move to bin 2019-06-18 13:20:40 +02:00
svlandeg
ffae7d3555 sentence encoder only (removing article/mention encoder) 2019-06-18 00:05:47 +02:00
Kabir Khan
1e19f34e29 Add optional id property to EntityRuler patterns (#3591)
* 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
2019-06-16 13:29:04 +02:00
svlandeg
b312f2d0e7 redo training data to be independent of KB and entity-level instead of doc-level 2019-06-14 15:55:26 +02:00
svlandeg
78dd3e11da write entity linking pipe to file and keep vocab consistent between kb and nlp 2019-06-13 16:25:39 +02:00
svlandeg
b12001f368 small fixes 2019-06-12 22:05:53 +02:00
svlandeg
6521cfa132 speeding up training 2019-06-12 13:37:05 +02:00
svlandeg
fe1ed432ef eval on dev set, varying combo's of prior and context scores 2019-06-11 11:40:58 +02:00
svlandeg
83dc7b46fd first tests with EL pipe 2019-06-10 21:25:26 +02:00
Matthew Honnibal
a931d72459 Add merge_subtokens as parser post-process. Re #3830 2019-06-07 20:40:41 +02:00
svlandeg
7de1ee69b8 training loop in proper pipe format 2019-06-07 15:55:10 +02:00
svlandeg
0486ccabfd introduce goldparse.links 2019-06-07 13:54:45 +02:00
svlandeg
a5c061f506 storing NEL training data in GoldParse objects 2019-06-07 12:58:42 +02:00
svlandeg
61f0e2af65 code cleanup 2019-06-06 20:22:14 +02:00
svlandeg
5c723c32c3 entity vectors in the KB + serialization of them 2019-06-05 18:29:18 +02:00
svlandeg
9abbd0899f separate entity encoder to get 64D descriptions 2019-06-05 00:09:46 +02:00
svlandeg
fb37cdb2d3 implementing el pipe in pipes.pyx (not tested yet) 2019-06-03 21:32:54 +02:00
svlandeg
dd691d0053 debugging 2019-05-17 17:44:11 +02:00
Sofie
a4a6bfa4e1
Merge branch 'master' into feature/el-framework 2019-03-26 11:00:02 +01:00
svlandeg
8814b9010d entity as one field instead of both ID and name 2019-03-25 18:10:41 +01:00
Matthew Honnibal
6c783f8045 Bug fixes and options for TextCategorizer (#3472)
* Fix code for bag-of-words feature extraction

The _ml.py module had a redundant copy of a function to extract unigram
bag-of-words features, except one had a bug that set values to 0.
Another function allowed extraction of bigram features. Replace all three
with a new function that supports arbitrary ngram sizes and also allows
control of which attribute is used (e.g. ORTH, LOWER, etc).

* Support 'bow' architecture for TextCategorizer

This allows efficient ngram bag-of-words models, which are better when
the classifier needs to run quickly, especially when the texts are long.
Pass architecture="bow" to use it. The extra arguments ngram_size and
attr are also available, e.g. ngram_size=2 means unigram and bigram
features will be extracted.

* Fix size limits in train_textcat example

* Explain architectures better in docs
2019-03-23 16:44:44 +01:00
Ines Montani
06bf130890 💫 Add better and serializable sentencizer (#3471)
* Add better serializable sentencizer component

* Replace default factory

* Add tests

* Tidy up

* Pass test

* Update docs
2019-03-23 15:45:02 +01:00
svlandeg
5318ce88fa 'entity_linker' instead of 'el' 2019-03-22 13:55:10 +01:00
svlandeg
1ee0e78fd7 select candidate with highest prior probabiity 2019-03-22 11:36:45 +01:00
svlandeg
c593607ce2 minimal EL pipe 2019-03-22 11:36:45 +01:00
svlandeg
735fc2a735 annotate kb_id through ents in doc 2019-03-22 11:36:44 +01:00
svlandeg
d849eb2455 adding kb_id as field to token, el as nlp pipeline component 2019-03-22 11:34:46 +01:00
Ines Montani
cb5dbfa63a Tidy up references to n_threads and fix default 2019-03-15 16:24:26 +01:00
Ines Montani
7ba3a5d95c 💫 Make serialization methods consistent (#3385)
* Make serialization methods consistent

exclude keyword argument instead of random named keyword arguments and deprecation handling

* Update docs and add section on serialization fields
2019-03-10 19:16:45 +01:00
Ines Montani
296446a1c8
Tidy up and improve docs and docstrings (#3370)
<!--- Provide a general summary of your changes in the title. -->

## Description
* tidy up and adjust Cython code to code style
* improve docstrings and make calling `help()` nicer
* add URLs to new docs pages to docstrings wherever possible, mostly to user-facing objects
* fix various typos and inconsistencies in docs

### Types of change
enhancement, docs

## 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.
2019-03-08 11:42:26 +01:00
Matthew Honnibal
6b0008afc6 Clean up TextCategorizer slightly 2019-02-23 12:28:06 +01:00
Matthew Honnibal
ce1e4eace2 Default to former TextCategorizer model
* Keep TextCategorizer default model same as v2.0
* Add option 'architecture' that allows "simple_cnn" to switch to
simpler model.
* Add option exclusive_classes, defaulting to False. If set to True,
the model treats classes as mutually exclusive, i.e. only one class can
be true per instance.
2019-02-23 11:55:16 +01:00
Matthew Honnibal
a137e8b418 Fix Pipe.to_bytes() when model uninitialized
Closes #3289
2019-02-21 09:42:02 +01:00
Ines Montani
5651a0d052 💫 Replace {Doc,Span}.merge with Doc.retokenize (#3280)
* Add deprecation warning to Doc.merge and Span.merge

* Replace {Doc,Span}.merge with Doc.retokenize
2019-02-15 10:29:44 +01:00
Ines Montani
f146121092 💫 Make handling of [Pipe].labels consistent (#3273)
* Make handling of [Pipe].labels consistent

* Un-xfail passing test

* Update spacy/pipeline/pipes.pyx

Co-Authored-By: ines <ines@ines.io>

* Update spacy/pipeline/pipes.pyx

Co-Authored-By: ines <ines@ines.io>

* Update spacy/tests/pipeline/test_pipe_methods.py

Co-Authored-By: ines <ines@ines.io>

* Update spacy/pipeline/pipes.pyx

Co-Authored-By: ines <ines@ines.io>

* Move error message to spacy.errors

* Fix textcat labels and test

* Make EntityRuler.labels return tuple as well
2019-02-15 06:03:19 +11:00
Ines Montani
a9f8d17632
💫 Break up large pipeline.pyx (#3246)
* Break up large pipeline.pyx

* Merge some components back together

* Fix typo
2019-02-10 12:14:51 +01:00