Details: https://spacy.io/models/ja#ja_core_news_lg
Japanese pipeline optimized for CPU. Components: tok2vec, parser, senter, ner, attribute_ruler.
Feature | Description |
---|---|
Name | ja_core_news_lg |
Version | 3.1.0 |
spaCy | >=3.1.0,<3.2.0 |
Default Pipeline | tok2vec , parser , attribute_ruler , ner |
Components | tok2vec , parser , senter , attribute_ruler , ner |
Vectors | 480443 keys, 480443 unique vectors (300 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 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 |
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 |
97.22 |
POS_ACC |
96.40 |
MORPH_ACC |
0.00 |
DEP_UAS |
91.81 |
DEP_LAS |
89.98 |
ENTS_P |
76.10 |
ENTS_R |
70.75 |
ENTS_F |
73.33 |
SENTS_P |
98.61 |
SENTS_R |
98.80 |
SENTS_F |
98.70 |