SQLucid: Grounding Natural Language Database Queries with Interactive Explanations
This work addresses the challenge for non-expert users in high-stakes domains by providing an interactive system to understand and refine database queries, representing an incremental advancement over existing interfaces.
The paper tackles the problem of limited accuracy and reliability in natural language interfaces for databases by introducing SQLucid, a user interface that integrates visual correspondence, intermediate results, and editable explanations, resulting in significant improvements in task completion accuracy and user confidence as validated through user studies and experiments.
Though recent advances in machine learning have led to significant improvements in natural language interfaces for databases, the accuracy and reliability of these systems remain limited, especially in high-stakes domains. This paper introduces SQLucid, a novel user interface that bridges the gap between non-expert users and complex database querying processes. SQLucid addresses existing limitations by integrating visual correspondence, intermediate query results, and editable step-by-step SQL explanations in natural language to facilitate user understanding and engagement. This unique blend of features empowers users to understand and refine SQL queries easily and precisely. Two user studies and one quantitative experiment were conducted to validate SQLucid's effectiveness, showing significant improvement in task completion accuracy and user confidence compared to existing interfaces. Our code is available at https://github.com/magic-YuanTian/SQLucid.