Description
This model is designed to be used in conjunction with the en_torah_ner model. See the README there for how to integrate them.
The model takes citations as input and tags the parts of the citation as entities. This is very useful for parsing the citation.
Technical details
Feature | Description |
---|---|
Name | en_subref_ner |
Version | 1.0.0 |
spaCy | >=3.4.1,<3.5.0 |
Default Pipeline | tok2vec , ner |
Components | tok2vec , ner |
Vectors | 218765 keys, 218765 unique vectors (50 dimensions) |
Sources | n/a |
License | GPLv3 |
Author | Sefaria |
Label Scheme
View label scheme (7 labels for 1 components)
Component | Labels |
---|---|
ner |
DH , dir-ibid , ibid , non-cts , number , range-symbol , title |
Accuracy
Type | Score |
---|---|
ENTS_F |
97.98 |
ENTS_P |
97.59 |
ENTS_R |
98.38 |
TOK2VEC_LOSS |
5193.13 |
NER_LOSS |
1103.44 |
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Inference Providers
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This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.
Evaluation results
- NER Precisionself-reported0.976
- NER Recallself-reported0.984
- NER F Scoreself-reported0.980