Checksum .tar.gz:
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Details: https://spacy.io/models/ja#ja_core_news_md
Japanese pipeline optimized for CPU. Components: tok2vec, parser, senter, ner, attribute_ruler.
| Feature | Description |
|---|---|
| Name | ja_core_news_md
|
| Version | 3.1.0
|
| spaCy | >=3.1.0,<3.2.0
|
| Default Pipeline | tok2vec, parser, attribute_ruler, ner
|
| Components | tok2vec, parser, senter, attribute_ruler, ner
|
| Vectors | 480443 keys, 20000 unique vectors (300 dimensions) |
| Sources | UD Japanese GSD v2.6 (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 v2.6 NER (Megagon Labs Tokyo) chiVe: Japanese Word Embedding with Sudachi & NWJC (chive-1.1-mc90-500k) (Works Applications) |
| License | CC BY-SA 4.0
|
| Author | Explosion |
| Model size | 40 MB |
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
| 97.22 |
POS_ACC
| 96.40 |
MORPH_ACC
| 0.00 |
DEP_UAS
| 91.93 |
DEP_LAS
| 90.06 |
ENTS_P
| 75.28 |
ENTS_R
| 68.84 |
ENTS_F
| 71.91 |
SENTS_P
| 99.40 |
SENTS_R
| 99.20 |
SENTS_F
| 99.30 |
Installation
pip install spacy
python -m spacy download ja_core_news_md