EHR-SeqSQL : A Sequential Text-to-SQL Dataset For Interactively Exploring Electronic Health Records
Jaehee Ryu, Seonhee Cho, Gyubok Lee, Edward Choi · 2024
In this paper, we introduce EHR-SeqSQL, a novel sequential text-to-SQL dataset for Electronic Health Record (EHR) databases.EHR-SeqSQL is designed to address critical yet underexplored aspects in text-to-SQL parsing: interactivity, compositionality, and efficiency.To the best of our knowledge, EHR-SeqSQL is not only the largest but also the first medical text-to-SQL dataset benchmark to include sequential and contextual questions.We provide a data split and the new test set designed to assess compositional generalization ability.Our experiments demonstrate the superiority of a multiturn approach over a single-turn approach in learning compositionality.Additionally, our dataset integrates specially crafted tokens into SQL queries to improve execution efficiency.With EHR-SeqSQL, we aim to bridge the gap between practical needs and academic research in the text-to-SQL domain.