lopozz/UA4RAG-it

UA4RAG（用于RAG的无答案数据集）是一个用于训练和评估语言模型在生成和识别无法根据参考文本回答的事实性问题和提供适当的非答案的数据集。在检索增强生成（RAG）系统中，检索到的上下文往往与用户查询不相关。这个数据集解决了训练模型识别证据不足并避免生成无支持回答的关键挑战，从而提高了基于RAG的系统可靠性。每个示例包括一个参考文档（上下文）、一个仅使用该上下文无法回答的事实性问题和一个解释为什么无法根据给定文本回答问题的答案。

UA4RAG (UnAnswerable for RAG) is a collection of datasets designed to train and evaluate language models on generating and recognizing unanswerable factual questions and appropriate non-answers given a reference text. In retrieval-augmented generation (RAG) systems, retrieved contexts are often tangential to user queries. This dataset addresses the critical challenge of training models to recognize when sufficient evidence is absent and to refrain from generating unsupported responses—improving the reliability of RAG-based systems. Each example contains a reference document (context), a question that is factually unanswerable using only that context, and an answer that explicitly acknowledges the missing information and explains why the question cannot be answered from the given text.