zh_data_dev_spacy_trf_1

Chinese spacy model, based on the spacy stock zh_core_web_trf transformer-based model, used for regular day to day data engineering.

Chinese transformer pipeline (Transformer(name='bert-base-chinese', piece_encoder='bert-wordpiece', stride=152, type='bert', width=768, window=208, vocab_size=21128)). Components: transformer, tagger, parser, ner, attribute_ruler.

Feature	Description
Name	zh_core_web_trf
Version	3.7.2
spaCy	>=3.7.0,<3.8.0
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	91.75
SENTS_P	70.92
SENTS_R	67.57
SENTS_F	69.21
DEP_UAS	75.72
DEP_LAS	71.45
ENTS_P	76.09
ENTS_R	72.18
ENTS_F	74.08