Framework Created for Easy RAG Performance Evaluation Using the Digital Agency's Public QA Dataset lawqa_jp
Published:Dec 25, 2025 08:53
•1 min read
•Zenn OpenAI
Analysis
This article discusses the creation of a framework for easily evaluating Retrieval-Augmented Generation (RAG) performance using the Japanese Digital Agency's publicly available QA dataset, lawqa_jp. The dataset consists of multiple-choice questions related to Japanese laws and regulations. The author highlights the limited availability of suitable Japanese datasets for RAG and positions lawqa_jp as a valuable resource. The framework aims to simplify the process of assessing RAG models on this dataset, potentially accelerating research and development in the field of legal information retrieval and question answering in Japanese. The article is relevant for data scientists and researchers working on RAG systems and natural language processing in the Japanese language.
Key Takeaways
- •lawqa_jp is a valuable resource for evaluating RAG performance in Japanese legal domain.
- •The framework simplifies the evaluation process of RAG models on lawqa_jp.
- •The dataset consists of multiple-choice questions based on Japanese laws and regulations.
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。”