Checksum .tar.gz:
6ae3d5a56229e3b5fb287ca1f8fa23451a55e52897c59f5b0814d9be5bd71d0f
Checksum .whl:9daae015e8a5be9e4914cd9ac722d5f9a0d1d41b6f19c5b1c961cc576582103a
Details: https://spacy.io/models/zh#zh_core_web_md
Chinese pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter, ner, attribute_ruler.
Feature | Description |
---|---|
Name | zh_core_web_md
|
Version | 3.5.0
|
spaCy | >=3.5.0,<3.6.0
|
Default Pipeline | tok2vec , tagger , parser , attribute_ruler , ner
|
Components | tok2vec , tagger , parser , senter , attribute_ruler , ner
|
Vectors | 500000 keys, 20000 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 |
Model size | 74 MB |
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
| 90.04 |
SENTS_P
| 78.89 |
SENTS_R
| 72.80 |
SENTS_F
| 75.72 |
DEP_UAS
| 70.50 |
DEP_LAS
| 65.22 |
ENTS_P
| 71.88 |
ENTS_R
| 67.90 |
ENTS_F
| 69.83 |
Installation
pip install spacy
python -m spacy download zh_core_web_md