Spacy Models for Biomedical Text.
Feature | Description |
---|---|
Name | en_Radiology_ner_bc5cdr_md |
Version | 0.5.1 |
spaCy | >=3.4.1,<3.5.0 |
Default Pipeline | tok2vec , tagger , attribute_ruler , lemmatizer , parser , ner |
Components | tok2vec , tagger , attribute_ruler , lemmatizer , parser , ner |
Vectors | 4087446 keys, 50000 unique vectors (200 dimensions) |
Sources | BC5CDR OntoNotes 5 Common Crawl GENIA 1.0 |
License | CC BY-SA 3.0 |
Author | Allen Institute for Artificial Intelligence |
Label Scheme
View label scheme (102 labels for 3 components)
Component | Labels |
---|---|
tagger |
$ , '' , , , -LRB- , -RRB- , . , : , ADD , AFX , CC , CD , DT , EX , FW , HYPH , IN , JJ , JJR , JJS , LS , MD , NFP , NN , NNP , NNPS , NNS , PDT , POS , PRP , PRP$ , RB , RBR , RBS , RP , SYM , TO , UH , VB , VBD , VBG , VBN , VBP , VBZ , WDT , WP , WP$ , WRB , XX , ```` |
parser |
ROOT , acl , acl:relcl , acomp , advcl , advmod , amod , amod@nmod , appos , attr , aux , auxpass , case , cc , cc:preconj , ccomp , compound , compound:prt , conj , cop , csubj , dative , dep , det , det:predet , dobj , expl , intj , mark , meta , mwe , neg , nmod , nmod:npmod , nmod:poss , nmod:tmod , nsubj , nsubjpass , nummod , parataxis , pcomp , pobj , preconj , predet , prep , punct , quantmod , xcomp |
ner |
ABST_RECOVER , CHEMICAL , DISEASE , DX , EXIST_WORSEN |
Accuracy
Type | Score |
---|---|
TAG_ACC |
0.00 |
LEMMA_ACC |
0.00 |
DEP_UAS |
0.00 |
DEP_LAS |
0.00 |
DEP_LAS_PER_TYPE |
0.00 |
SENTS_P |
0.00 |
SENTS_R |
0.00 |
SENTS_F |
0.00 |
ENTS_F |
85.68 |
ENTS_P |
87.95 |
ENTS_R |
83.53 |
NER_LOSS |
201857.49 |
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Evaluation results
- NER Precisionself-reported0.880
- NER Recallself-reported0.835
- NER F Scoreself-reported0.857
- TAG (XPOS) Accuracyself-reported0.000
- Lemma Accuracyself-reported0.000
- Unlabeled Attachment Score (UAS)self-reported0.000
- Labeled Attachment Score (LAS)self-reported0.000
- Sentences F-Scoreself-reported0.000