ModelRefs / Text-to-SQL — AI Glossary
Text-to-SQL — AI Glossary
Converting natural language questions into executable SQL queries, enabling non-technical users to query databases directly.
Overview
Text-to-SQL (Spider, BIRD benchmarks) requires the model to understand schema (table/column names, foreign keys), write syntactically correct SQL, and handle aggregations, joins, and subqueries. GPT-4 achieves ~85% on Spider; production deployments add schema linking, few-shot examples with domain-specific queries, and execution-feedback loops for self-correction.
Reference details
| Topic | applications |
|---|---|
| Last reviewed | 2026-06-24 |
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Frequently asked questions
What is Text-to-SQL?
Converting natural language questions into executable SQL queries, enabling non-technical users to query databases directly.
What concepts are related to Text-to-SQL?
Closely related concepts include table qa, data analyst ai, code generation.