github explosion/spacy-models ja_core_news_sm-3.0.0

Downloads Downloads (wheel)

Details: https://spacy.io/models/ja#ja_core_news_sm

Checksum .tar.gz: d51001977ff2cec7c9c9e470449cc0efc200f0f7198fbcf64757609594d5df72
Checksum .whl: 36f63525fe1197dca030ed3e2b78230d1647ddbe54d3cd18118cb3743255648a

Japanese pipeline optimized for CPU. Components: tok2vec, parser, senter, ner, attribute_ruler.

Feature Description
Name ja_core_news_sm
Version 3.0.0
spaCy >=3.0.0,<3.1.0
Model size 12 MB
Default Pipeline tok2vec, parser, ner, attribute_ruler
Components tok2vec, parser, senter, ner, attribute_ruler
Vectors 0 keys, 0 unique vectors (0 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 91.80
DEP_LAS 89.83
ENTS_P 71.72
ENTS_R 57.98
ENTS_F 64.12
SENTS_P 99.40
SENTS_R 99.20
SENTS_F 99.30

Installation

pip install spacy
python -m spacy download ja_core_news_sm

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