README.md

metadata

tags:
  - spacy
  - token-classification
language:
  - zh
license: mit
model-index:
  - name: zh_core_web_sm
    results:
      - task:
          name: NER
          type: token-classification
        metrics:
          - name: NER Precision
            type: precision
            value: 0.7203462148
          - name: NER Recall
            type: recall
            value: 0.6493406593
          - name: NER F Score
            type: f_score
            value: 0.6830029475
      - task:
          name: TAG
          type: token-classification
        metrics:
          - name: TAG (XPOS) Accuracy
            type: accuracy
            value: 0.8933253054
      - task:
          name: UNLABELED_DEPENDENCIES
          type: token-classification
        metrics:
          - name: Unlabeled Attachment Score (UAS)
            type: f_score
            value: 0.6960047338
      - task:
          name: LABELED_DEPENDENCIES
          type: token-classification
        metrics:
          - name: Labeled Attachment Score (LAS)
            type: f_score
            value: 0.640776699
      - task:
          name: SENTS
          type: token-classification
        metrics:
          - name: Sentences F-Score
            type: f_score
            value: 0.7514211886

Details: https://spacy.io/models/zh#zh_core_web_sm

Chinese pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter, ner, attribute_ruler.

Feature	Description
Name	zh_core_web_sm
Version	3.7.0
spaCy	>=3.7.0,<3.8.0
Default Pipeline	tok2vec, tagger, parser, attribute_ruler, ner
Components	tok2vec, tagger, parser, senter, attribute_ruler, ner
Vectors	0 keys, 0 unique vectors (0 dimensions)
Sources	OntoNotes 5 (Ralph Weischedel, Martha Palmer, Mitchell Marcus, Eduard Hovy, Sameer Pradhan, Lance Ramshaw, Nianwen Xue, Ann Taylor, Jeff Kaufman, Michelle Franchini, Mohammed El-Bachouti, Robert Belvin, Ann Houston) CoreNLP Universal Dependencies Converter (Stanford NLP Group)
License	MIT
Author	Explosion

Label Scheme

View label scheme (100 labels for 3 components)

Component	Labels
tagger	AD, AS, BA, CC, CD, CS, DEC, DEG, DER, DEV, DT, ETC, FW, IJ, INF, JJ, LB, LC, M, MSP, NN, NR, NT, OD, ON, P, PN, PU, SB, SP, URL, VA, VC, VE, VV, X, _SP
parser	ROOT, acl, advcl:loc, advmod, advmod:dvp, advmod:loc, advmod:rcomp, amod, amod:ordmod, appos, aux:asp, aux:ba, aux:modal, aux:prtmod, auxpass, case, cc, ccomp, compound:nn, compound:vc, conj, cop, dep, det, discourse, dobj, etc, mark, mark:clf, name, neg, nmod, nmod:assmod, nmod:poss, nmod:prep, nmod:range, nmod:tmod, nmod:topic, nsubj, nsubj:xsubj, nsubjpass, nummod, parataxis:prnmod, punct, xcomp
ner	CARDINAL, DATE, EVENT, FAC, GPE, LANGUAGE, LAW, LOC, MONEY, NORP, ORDINAL, ORG, PERCENT, PERSON, PRODUCT, QUANTITY, TIME, WORK_OF_ART

Accuracy

Type	Score
TOKEN_ACC	95.85
TOKEN_P	94.58
TOKEN_R	91.36
TOKEN_F	92.94
TAG_ACC	89.33
SENTS_P	77.85
SENTS_R	72.62
SENTS_F	75.14
DEP_UAS	69.60
DEP_LAS	64.08
ENTS_P	72.03
ENTS_R	64.93
ENTS_F	68.30