ja_core_news_sm-2.3.2
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since this release
Details: https://spacy.io/models/ja#ja_core_news_sm
File checksum:
ab346bf623f59965d4813a5b9c8d19d19ccbf37e5e0f3b99684f9b5990c1be11
Japanese multi-task CNN trained on UD_Japanese-GSD v2.6-NE. Assigns context-specific token vectors, POS tags, dependency parses and named entities.
| Feature | Description |
|---|---|
| Name | ja_core_news_sm |
| Version | 2.3.2 |
| spaCy | >=2.3.0,<2.4.0 |
| Model size | 7 MB |
| Pipeline | 聽parser, ner |
| Vectors | 0 keys, 0 unique vectors (0 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-NE (Megagon Labs Tokyo) SudachiPy (Works Applications) SudachiDict (Works Applications) |
| License | CC BY-SA 4.0 |
| Author | Explosion and Megagon Labs Tokyo |
Label Scheme
| Component | Labels |
|---|---|
parser |
聽ROOT, acl, advcl, advmod, amod, aux, case, cc, ccomp, compound, cop, csubj, dep, det, dislocated, fixed, mark, nmod, nsubj, nummod, obj, obl, punct |
ner |
聽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 |
|---|---|
LAS |
聽86.93 |
UAS |
聽88.65 |
TOKEN_ACC |
聽97.67 |
ENTS_F |
聽61.04 |
ENTS_P |
聽65.40 |
ENTS_R |
聽57.22 |
Installation
pip install spacy
python -m spacy download ja_core_news_sm