zh_core_web_sm-3.3.0

Checksum .tar.gz: db5c5c9f75d6249fb7aabf51659d7e2667db520618c5d38d63cab5d639280c17
Checksum .whl: ea854aad175da45e65024136316fbffb9583e49133d1ab042107217d5f809998

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	3.3.0
spaCy	>=3.3.0.dev0,<3.4.0
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
Model size	46 MB

Label Scheme

View label scheme (99 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
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	97.88
TOKEN_P	94.58
TOKEN_R	91.36
TOKEN_F	92.94
TAG_ACC	89.27
SENTS_P	78.37
SENTS_R	72.67
SENTS_F	75.41
DEP_UAS	69.38
DEP_LAS	64.00
ENTS_P	72.49
ENTS_R	65.26
ENTS_F	68.69

Installation

pip install spacy
python -m spacy download zh_core_web_sm