github explosion/spacy-models ja_core_news_md-3.2.0

Downloads Downloads (wheel)

Checksum .tar.gz: 46fcb4930af02a4673a8d819746b609700974221c02d9c3c7196be0b92b9a957
Checksum .whl: c851e760a3b18f48359d9c52828ced1d1bf2560063d8fcdfc161203e3eaf35eb

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 3.2.0
spaCy >=3.2.0,<3.3.0
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 (66 labels for 4 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=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
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
TOKEN_P 97.65
TOKEN_R 97.90
TOKEN_F 97.77
POS_ACC 97.13
MORPH_ACC 0.40
MORPH_MICRO_P 34.01
MORPH_MICRO_R 98.04
MORPH_MICRO_F 50.51
SENTS_P 98.62
SENTS_R 99.01
SENTS_F 98.82
DEP_UAS 92.24
DEP_LAS 90.75
TAG_ACC 97.16
LEMMA_ACC 96.59
ENTS_P 73.77
ENTS_R 67.92
ENTS_F 70.73

Installation

pip install spacy
python -m spacy download ja_core_news_md

Don't miss a new spacy-models release

NewReleases is sending notifications on new releases.