Details: https://spacy.io/models/ja#ja_core_news_lg
Checksum .tar.gz:
ea479d9905dce0e456465b8089d174e100b81fd919490e5fb4ddac60b4857457
Checksum .whl:224d1b211f686818f1e3117c2b610f7a652492609bd12511c2ca94fb7d381b20
Japanese pipeline optimized for CPU. Components: tok2vec, parser, senter, ner, attribute_ruler.
| Feature | Description |
|---|---|
| Name | ja_core_news_lg
|
| Version | 3.0.0
|
| spaCy | >=3.0.0,<3.1.0
|
| Model size | 531 MB |
| Default Pipeline | tok2vec, parser, ner, attribute_ruler
|
| Components | tok2vec, parser, senter, ner, attribute_ruler
|
| Vectors | 480443 keys, 480443 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
| 91.83 |
DEP_LAS
| 89.93 |
ENTS_P
| 73.92 |
ENTS_R
| 69.86 |
ENTS_F
| 71.83 |
SENTS_P
| 98.01 |
SENTS_R
| 98.40 |
SENTS_F
| 98.21 |
Installation
pip install spacy
python -m spacy download ja_core_news_lg