metadata
tags:
- spacy
- token-classification
language:
- ja
license: CC-BY-SA-4.0
model-index:
- name: ja_core_news_md
results:
- tasks:
name: NER
type: token-classification
metrics:
- name: Precision
type: precision
value: 0.7527932961
- name: Recall
type: recall
value: 0.6883780332
- name: F Score
type: f_score
value: 0.7191460974
- tasks:
name: POS
type: token-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9721899386
- tasks:
name: SENTER
type: token-classification
metrics:
- name: Precision
type: precision
value: 0.994
- name: Recall
type: recall
value: 0.9920159681
- name: F Score
type: f_score
value: 0.993006993
- tasks:
name: UNLABELED_DEPENDENCIES
type: token-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9192898975
- tasks:
name: LABELED_DEPENDENCIES
type: token-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9192898975
Details: https://spacy.io/models/ja#ja_core_news_md
Japanese pipeline optimized for CPU. Components: tok2vec, parser, senter, ner, attribute_ruler.
| Feature | Description |
|---|---|
| Name | ja_core_news_md |
| 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, 20000 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 |
91.93 |
DEP_LAS |
90.06 |
ENTS_P |
75.28 |
ENTS_R |
68.84 |
ENTS_F |
71.91 |
SENTS_P |
99.40 |
SENTS_R |
99.20 |
SENTS_F |
99.30 |