Multiple lines of research have developed Natural Language (NL) interfaces for formulating database queries. We build upon this work, but focus on presenting a highly detailed form of the answers in NL. The answers that we present are importantly based on the provenance of tuples in the query result, detailing not only the results but also their explanations. We develop a novel method for transforming provenance information to NL, by leveraging the original NL query structure. Furthermore, since provenance information is typically large and complex, we present two solutions for its effective presentation as NL text: one that is based on provenance factorization, with novel desiderata relevant to the NL case and one that is based on summarization. We have implemented our solution in an end-to-end system supporting questions, answers and provenance, all expressed in NL. Our experiments, including a user study, indicate the quality of our solution and its scalability.

中文翻译：

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解释自然语言查询结果

多个研究领域已经开发出用于表述数据库查询的自然语言（NL）接口。我们以这项工作为基础，但专注于呈现NL中答案的高度详细的形式。我们提供的答案重要地是基于查询结果中元组的来源，不仅详细说明了结果，还详细说明了它们的解释。。我们利用原始的NL查询结构，开发了一种将来源信息转换为NL的新颖方法。此外，由于出处信息通常很大且很复杂，因此我们提供两种解决方案来有效地将其表示为NL文本：一种基于出处分解，具有与NL案例相关的新颖设计，另一种基于总结。我们已在支持问题，答案和出处的端到端系统中实施了我们的解决方案，所有这些都以NL表示。我们的实验（包括用户研究）表明了我们解决方案的质量及其可扩展性。