NL2SQL+: An Extended Framework for SQL Generation With On-Demand Embedded ML Functions
The empirical findings indicate that factorizing ML-aware SQL generation into four distinct stages—query routing, structured intent extraction, model or function selection, and template-guided SQL synthesis—enhances semantic controllability and token efficiency when formulating predictive natural language queries over database-native ML systems.