Checksum .tar.gz:
8cff76d174c22e584ad0a5db5ebd0a27dba7c3ae7af51186b3501b1491d0d797
Checksum .whl:c8e4d6b436c5c5dbec0b999dd843bbc41fb20c9080f64bfc86c12032268bdb54
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 | 3.3.0
|
spaCy | >=3.3.0.dev0,<3.4.0
|
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 |
Model size | 574 MB |
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
| 97.88 |
TOKEN_P
| 94.58 |
TOKEN_R
| 91.36 |
TOKEN_F
| 92.94 |
TAG_ACC
| 90.34 |
SENTS_P
| 78.52 |
SENTS_R
| 73.13 |
SENTS_F
| 75.73 |
DEP_UAS
| 70.86 |
DEP_LAS
| 65.70 |
ENTS_P
| 74.03 |
ENTS_R
| 69.64 |
ENTS_F
| 71.77 |
Installation
pip install spacy
python -m spacy download zh_core_web_lg