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ja_core_news_lg

Token Classification
spaCy
Japanese
Eval Results
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ja_core_news_lg
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---
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)<br />[UD Japanese GSD v2.6 NER](https://github.com/megagonlabs/UD_Japanese-GSD) (Megagon Labs Tokyo)<br />[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

<details>

<summary>View label scheme (47 labels for 3 components)</summary>

| 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` |

</details>

### 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 |