--- tags: - spacy - token-classification language: - ja license: CC-BY-SA-4.0 model-index: - name: ja_core_news_lg results: - tasks: name: NER type: token-classification metrics: - name: Precision type: precision value: 0.760989011 - name: Recall type: recall value: 0.7075351213 - name: F Score type: f_score value: 0.7332892124 - 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: 0.9860557769 - name: Recall type: recall value: 0.9880239521 - name: F Score type: f_score value: 0.9870388833 - tasks: name: UNLABELED_DEPENDENCIES type: token-classification metrics: - name: Accuracy type: accuracy value: 0.9181002928 - tasks: name: LABELED_DEPENDENCIES type: token-classification metrics: - name: Accuracy type: accuracy value: 0.9181002928 --- ### 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](https://github.com/UniversalDependencies/UD_Japanese-GSD) (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](https://github.com/megagonlabs/UD_Japanese-GSD) (Megagon Labs Tokyo)
[chiVe: Japanese Word Embedding with Sudachi & NWJC (chive-1.1-mc90-500k)](https://github.com/WorksApplications/chiVe) (Works Applications) | | **License** | `CC BY-SA 4.0` | | **Author** | [Explosion](https://explosion.ai) | ### 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 |