spacy/zh_core_web_lg

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

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

Feature	Description
Name	zh_core_web_lg
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	500000 keys, 500000 unique vectors (300 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) Explosion fastText Vectors (cbow, OSCAR Common Crawl + Wikipedia) (Explosion)
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	90.33
SENTS_P	78.05
SENTS_R	72.63
SENTS_F	75.24
DEP_UAS	70.86
DEP_LAS	65.71
ENTS_P	73.55
ENTS_R	69.25
ENTS_F	71.34