Details: https://spacy.io/models/ja#ja_core_news_md
Checksum .tar.gz:
f84f9baaa5ab73a86741de6029a096fcdbe5cfa95922503e573f3aed2847fcc9
Checksum .whl:9ba3406db6ee439d362c20e554e2dac5c06d423f4b4e1ac9fcede8efc502de61
Japanese pipeline optimized for CPU. Components: tok2vec, parser, senter, ner, attribute_ruler.
| Feature | Description |
|---|---|
| Name | ja_core_news_md
|
| Version | 3.0.0
|
| spaCy | >=3.0.0,<3.1.0
|
| Model size | 41 MB |
| Default Pipeline | tok2vec, parser, ner, attribute_ruler
|
| Components | tok2vec, parser, senter, ner, attribute_ruler
|
| Vectors | 480443 keys, 20000 unique vectors (300 dimensions) |
| Sources | n/a |
| License | CC BY-SA 4.0
|
| Author | Explosion |
Label Scheme
View label scheme (47 labels for 3 components)
| Component | Labels |
|---|---|
parser
| ROOT, acl, advcl, advmod, amod, aux, case, cc, ccomp, compound, cop, csubj, dep, det, dislocated, fixed, mark, nmod, nsubj, nummod, obj, obl, punct
|
senter
| I, S
|
ner
| CARDINAL, DATE, EVENT, FAC, GPE, LANGUAGE, LAW, LOC, MONEY, MOVEMENT, NORP, ORDINAL, ORG, PERCENT, PERSON, PET_NAME, PHONE, PRODUCT, QUANTITY, TIME, TITLE_AFFIX, WORK_OF_ART
|
Accuracy
| Type | Score |
|---|---|
TOKEN_ACC
| 99.69 |
TAG_ACC
| 97.21 |
POS_ACC
| 96.39 |
DEP_UAS
| 92.22 |
DEP_LAS
| 90.23 |
ENTS_P
| 74.97 |
ENTS_R
| 68.84 |
ENTS_F
| 71.77 |
SENTS_P
| 98.80 |
SENTS_R
| 98.40 |
SENTS_F
| 98.60 |
Installation
pip install spacy
python -m spacy download ja_core_news_md