From Questions to Queries: An AI-powered Multi-Agent Framework for Spatial Text-to-SQL

ArXi:2510.21045v3 Announce Type: replace The complexity of SQL and the spatial semantics of PostGIS create barriers for non-experts working with spatial data. Although large language models can translate natural language into SQL, spatial Text-to-SQL is error-prone than general Text-to-SQL because it must resolve geographic intent, schema ambiguity, geometry-bearing tables and columns, spatial function choice, and coordinate reference system and measurement assumptions. We