从数据查询到数据调查：重新思考数据库的自然语言接口
From Data Querying to Data Investigations: Rethinking Natural Language Interfaces for Databases
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中文总结 AI 辅助
本文针对传统数据库自然语言接口仅支持单条SQL查询的局限，提出数据调查新范式，构建原型系统D²，结合新基准验证其在需证据决策的数据调查任务中优于传统单查询问答。
中文摘要 AI 辅助
数据库的自然语言（NL）接口一直针对错误的问题进行优化。主流的文本转SQL范式假设用户提出的问题可通过单条SQL查询得到回答，但实际中用户需要协助解决数据问题，这要求通过多条SQL查询序列搜索数据库，并对中间结果进行推理，而非仅运行单条SQL查询。因此本文提出一种面向数据的NL接口新范式，称为数据调查（data investigations）。我们推出首个数据调查系统原型D²，它体现了这一愿景：通过自主搜索、推理和收集数据来解决数据问题。利用基于谋杀之谜（Murder Mystery）数据集构建的新基准，我们展示了D²在需要基于证据做出决策的数据调查任务中的潜力，其能力超出了传统单查询问答的范畴。
英文摘要
Natural language (NL) interfaces to databases have been optimized for the wrong problem. The dominant Text-to-SQL paradigm assumes that users ask questions that can be answered by single SQL queries. In practice, however, users seek assistance with solving data problems. This requires searching a database by sequences of SQL queries while reasoning over intermediate results instead of just running one SQL query. This paper therefore introduces a new paradigm for NL interfaces to data, which we call data investigations. We present D^2, a first prototype of a data investigation system that embodies this vision by autonomously searching, reasoning over, and collecting data to solve data problems. Using a newly constructed benchmark based on the Murder Mystery dataset, we demonstrate the potential of D^2 for tasks that require data investigations with evidence-backed decisions, extending beyond the capabilities of traditional single-query question answering.
发表机构
- TU Darmstadt（达姆施塔特工业大学）
- MIT Darmstadt（达姆施塔特理工学院）
- DFKI（德国人工智能研究中心）
机构由 AI 辅助整理，请以论文原文为准。
