metadata
language: ja
thumbnail: https://github.com/studio-ousia/luke/raw/master/resources/luke_logo.png
tags:
- luke
- named entity recognition
- entity typing
- relation classification
- question answering
license: apache-2.0
luke-japanese
luke-japanese is the Japanese version of LUKE (Language Understanding with Knowledge-based Embeddings), a pre-trained knowledge-enhanced contextualized representation of words and entities based on transformer. LUKE treats words and entities in a given text as independent tokens, and outputs contextualized representations of them. Please refer to our GitHub repository for more details and updates.
luke-japaneseは、単語とエンティティの知識拡張型訓練済みモデルLUKEの日本 語版です。LUKE は単語とエンティティを独立したトークンとして扱い、これらの文脈を 考慮した表現を出力します。詳細については 、GitHub リポジトリを参照してください。
Experimental results on JGLUE
The performance of luke-japanese evaluated on the dev set of JGLUE is shown as follows:
| Model | MARC-ja | JSTS | JNLI | JCommonsenseQA |
|---|---|---|---|---|
| acc | Pearson/Spearman | acc | acc | |
| luke-japanese-base | 0.963 | 0.912/0.875 | 0.912 | 0.842 |
| Baselines: | ||||
| Tohoku BERT base | 0.958 | 0.899/0.859 | 0.899 | 0.808 |
| NICT BERT base | 0.958 | 0.903/0.867 | 0.902 | 0.823 |
| Waseda RoBERTa base | 0.962 | 0.901/0.865 | 0.895 | 0.840 |
| XLM RoBERTa base | 0.961 | 0.870/0.825 | 0.893 | 0.687 |
Citation
@inproceedings{yamada2020luke,
title={LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attention},
author={Ikuya Yamada and Akari Asai and Hiroyuki Shindo and Hideaki Takeda and Yuji Matsumoto},
booktitle={EMNLP},
year={2020}
}