A Framework for Easily Evaluating RAG Performance with the Digital Agency's Public QA Dataset lawqa_jp
Published:Dec 25, 2025 08:53
•1 min read
•Zenn OpenAI
Analysis
This article introduces a framework for evaluating Retrieval-Augmented Generation (RAG) performance using the lawqa_jp dataset released by Japan's Digital Agency. The dataset consists of multiple-choice questions related to Japanese laws, making it a valuable resource for training and evaluating RAG models in the legal domain. The article highlights the limited availability of Japanese datasets suitable for RAG and positions lawqa_jp as a significant contribution. The framework aims to simplify the evaluation process, potentially encouraging wider adoption and improvement of RAG models for legal applications. It's a practical approach to leveraging a newly available resource for advancing NLP in a specific domain.
Key Takeaways
- •lawqa_jp dataset from the Digital Agency is a valuable resource for RAG in the legal domain.
- •The framework simplifies the evaluation of RAG models using this dataset.
- •Limited availability of Japanese datasets for RAG makes this contribution significant.
Reference
“本データセットは、総務省のポータルサイト e-Gov などで公開されている法令文書などを参照した質問・回答ペアをまとめたデータセットであり、全ての質問が a ~ d の4択式の問題で構成されています。”