From Data Querying to Data Investigations: Rethinking Natural Language Interfaces for Databases

2026-09-03

AI Summary

本文针对用户实际解决数据问题的需求，提出了一种新的自然语言接口范式——数据调查，并通过D^2系统原型展示其在处理复杂数据查询任务上的潜力。

Abstract

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.

Problem

• Natural Language Interfaces
• Databases
• Data Investigations
• Text-to-SQL

Innovation

• data investigations
• autonomous searching and reasoning
• multiple SQL queries