BiomedSQL: Text-to-SQL for Scientific Reasoning on Biomedical Knowledge Bases.

ABSTRACT: Biomedical researchers increasingly rely on large-scale structured databases for complex analytical tasks. However, current text-to-SQL systems often struggle to map qualitative scientific questions into executable SQL, particularly when implicit domain reasoning is required. We introduce BiomedSQL, the first benchmark explicitly designed to evaluate scientific reasoning in text-to-SQL generation over a real-world biomedical knowledge base. BiomedSQL comprises 68,000 question/SQL query/answer triples generated from templates and grounded in a harmonized BigQuery knowledge base that integrates gene-disease associations, causal inference from omics data, and drug approval records. Each question requires models to infer domain-specific criteria, such as genome-wide significance thresho

SUBMITTER: Koretsky MJ 

PROVIDER: S-EPMC12478439 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature