mirror of
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0b4b4f1819
* 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 |
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| .. | ||
| ner_example_data | ||
| conllu.py | ||
| ner_multitask_objective.py | ||
| pretrain_kb.py | ||
| pretrain_textcat.py | ||
| rehearsal.py | ||
| train_entity_linker.py | ||
| train_intent_parser.py | ||
| train_ner.py | ||
| train_new_entity_type.py | ||
| train_parser.py | ||
| train_tagger.py | ||
| train_textcat.py | ||
| training-data.json | ||
| vocab-data.jsonl | ||