zh_core_web_md-2.3.1

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

File checksum: 927dea34e6d140c2867a7ecd3958ca6832f5199cfc37991cb0d393aa7ce791d8

Chinese multi-task CNN trained on OntoNotes. Assigns word vectors, POS tags, dependency parse and named entities. Word vectors trained using FastText CBOW on Wikipedia and OSCAR (Common Crawl).

Feature	Description
Name	zh_core_web_md
Version	2.3.1
spaCy	>=2.3.0,<2.4.0
Model size	75 MB
Pipeline	tagger, parser, ner
Vectors	500000 keys, 20000 unique vectors (300 dimensions)
Sources	OntoNotes 5 OSCAR (Common Crawl) Wikipedia (20200301)
License	MIT
Author	Explosion

Label Scheme

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
LAS	64.43
UAS	69.39
TOKEN_ACC	94.58
TAGS_ACC	90.23
ENTS_F	68.52
ENTS_P	70.20
ENTS_R	66.91

Installation

pip install spacy
python -m spacy download zh_core_web_md