github explosion/spacy-models ja_core_news_md-3.5.0

Downloads Downloads (wheel)

Checksum .tar.gz: dd0f49e126e65dea9d36e029cd1590e87cc692dd013c872e5768df5b0e3e1754
Checksum .whl: 4d24b2118902b57d62271e12c28a6071e1c08dd653523da336bbb824b3e8b3bf

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

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

Feature Description
Name ja_core_news_md
Version 3.5.0
spaCy >=3.5.0,<3.6.0
Default Pipeline tok2vec, morphologizer, parser, attribute_ruler, ner
Components tok2vec, morphologizer, parser, senter, attribute_ruler, ner
Vectors 480443 keys, 20000 unique vectors (300 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)
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 (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 97.65
TOKEN_R 97.90
TOKEN_F 97.77
POS_ACC 97.22
MORPH_ACC 0.00
MORPH_MICRO_P 34.01
MORPH_MICRO_R 98.04
MORPH_MICRO_F 50.51
SENTS_P 97.08
SENTS_R 98.42
SENTS_F 97.75
DEP_UAS 92.04
DEP_LAS 90.74
TAG_ACC 97.12
LEMMA_ACC 96.71
ENTS_P 71.21
ENTS_R 65.66
ENTS_F 68.32

Installation

pip install spacy
python -m spacy download ja_core_news_md

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