ja-ner-ja

Japanese Named Entity Recognition model built with spaCy.

Labels

Label Precision Recall F1
PERSON 0.950 0.949 0.949
DATE_OF_BIRTH 0.872 0.872 0.872
ADDRESS 0.904 0.967 0.934
ORGANIZATION 0.929 0.828 0.876
BANK_ACCOUNT 0.947 0.857 0.900

Architecture

  • Pipeline: tok2vec → ner
  • spaCy version: >=3.8.13,<3.9.0

Install

pip install https://huggingface.co/0xhikae/ja-ner-ja/resolve/main/ja_ner_ja-0.2.0-py3-none-any.whl

Usage

import spacy
nlp = spacy.load("ja_ner_ja")
doc = nlp("田中太郎は東京都渋谷区に住んでいます。")
for ent in doc.ents:
    print(ent.text, ent.label_)
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Evaluation results