Checksum .tar.gz:
856f0e15da5d2151626222b10d3b224d315079ae121e8ed940a3d1bfc3a4a314
Checksum .whl:65693016b7cf33ffa845af3523a9c9b8d9aabae85dfc2e46731513a5e03def04
Details: https://spacy.io/models/ja#ja_core_news_sm
Japanese pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, senter, ner, attribute_ruler.
Feature | Description |
---|---|
Name | ja_core_news_sm
|
Version | 3.8.0
|
spaCy | >=3.8.0,<3.9.0
|
Default Pipeline | tok2vec , morphologizer , parser , attribute_ruler , ner
|
Components | tok2vec , morphologizer , parser , senter , attribute_ruler , ner
|
Vectors | 0 keys, 0 unique vectors (0 dimensions) |
Sources | UD Japanese GSD v2.8 (Omura, Mai; Miyao, Yusuke; Kanayama, Hiroshi; Matsuda, Hiroshi; Wakasa, Aya; Yamashita, Kayo; Asahara, Masayuki; Tanaka, Takaaki; Murawaki, Yugo; Matsumoto, Yuji; Mori, Shinsuke; Uematsu, Sumire; McDonald, Ryan; Nivre, Joakim; Zeman, Daniel) UD Japanese GSD v2.8 NER (Megagon Labs Tokyo) |
License | CC BY-SA 4.0
|
Author | Explosion |
Model size | 11 MB |
Label Scheme
View label scheme (65 labels for 3 components)
Component | Labels |
---|---|
morphologizer
| POS=NOUN , POS=ADP , POS=VERB , POS=SCONJ , POS=AUX , POS=PUNCT , POS=PART , POS=DET , POS=NUM , POS=ADV , POS=PRON , POS=ADJ , POS=PROPN , POS=CCONJ , POS=SYM , POS=NOUN|Polarity=Neg , POS=AUX|Polarity=Neg , POS=SPACE , POS=INTJ , POS=SCONJ|Polarity=Neg
|
parser
| ROOT , acl , advcl , advmod , amod , aux , case , cc , ccomp , compound , cop , csubj , dep , det , dislocated , fixed , mark , nmod , nsubj , nummod , obj , obl , punct
|
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
| 99.37 |
TOKEN_P
| 97.61 |
TOKEN_R
| 97.87 |
TOKEN_F
| 97.74 |
POS_ACC
| 96.23 |
MORPH_ACC
| 0.00 |
MORPH_MICRO_P
| 34.01 |
MORPH_MICRO_R
| 98.04 |
MORPH_MICRO_F
| 50.51 |
SENTS_P
| 99.02 |
SENTS_R
| 99.21 |
SENTS_F
| 99.11 |
DEP_UAS
| 92.01 |
DEP_LAS
| 90.54 |
TAG_ACC
| 97.12 |
LEMMA_ACC
| 96.68 |
ENTS_P
| 67.43 |
ENTS_R
| 55.47 |
ENTS_F
| 60.87 |
Installation
pip install spacy
python -m spacy download ja_core_news_sm