github explosion/spacy-models ja_core_news_lg-3.4.0

Downloads Downloads (wheel)

Checksum .tar.gz: 43a17a6d35b1e5b5726dbe6a2ae630be3c4499be68c5a5b6fb5ad2a51ece409c
Checksum .whl: aeadec83e6f3149cf6681d6ad45a6f17f408a82914e8f16c50909e848844569b

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

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

Feature Description
Name ja_core_news_lg
Version 3.4.0
spaCy >=3.4.0,<3.5.0
Default Pipeline tok2vec, morphologizer, parser, attribute_ruler, ner
Components tok2vec, morphologizer, parser, senter, attribute_ruler, ner
Vectors 480443 keys, 480443 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 529 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 99.69
TOKEN_P 97.65
TOKEN_R 97.90
TOKEN_F 97.77
POS_ACC 97.37
MORPH_ACC 0.00
MORPH_MICRO_P 34.01
MORPH_MICRO_R 98.04
MORPH_MICRO_F 50.51
SENTS_P 99.41
SENTS_R 99.21
SENTS_F 99.31
DEP_UAS 92.17
DEP_LAS 90.91
TAG_ACC 97.12
LEMMA_ACC 96.71
ENTS_P 74.36
ENTS_R 69.69
ENTS_F 71.95

Installation

pip install spacy
python -m spacy download ja_core_news_lg

Don't miss a new spacy-models release

NewReleases is sending notifications on new releases.