spacy/zh_core_web_trf

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

Chinese transformer pipeline (bert-base-chinese). Components: transformer, tagger, parser, ner, attribute_ruler.

Feature	Description
Name	zh_core_web_trf
Version	3.6.1
spaCy	>=3.6.0,<3.7.0
Default Pipeline	transformer, tagger, parser, attribute_ruler, ner
Components	transformer, tagger, parser, 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) bert-base-chinese (Hugging Face)
License	MIT
Author	Explosion

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	95.85
TOKEN_P	94.58
TOKEN_R	91.36
TOKEN_F	92.94
TAG_ACC	92.48
SENTS_P	72.67
SENTS_R	66.46
SENTS_F	69.43
DEP_UAS	77.03
DEP_LAS	73.27
ENTS_P	75.88
ENTS_R	75.86
ENTS_F	75.87