Generation of synthetic data for query generation

Abstract

Systems, methods, devices, and computer readable storage media described herein provide techniques for generating synthetic data for use in query generation. In an aspect, a pair comprising a natural language (NL) query and a query language (QL) query and predicted catalog information are used to prompt a large language model (LLM) to generate an augmented pair that is a variation of the pair. Synthetic data is generated comprising the augmented pair. In another aspect, an indication of feedback for a QL query generated by a LLM is received and a corrected pair is generated based on the indication and a corresponding NL query, the corrected pair comprises a corrected QL query and the NL query. The corrected QL query is a syntactically valid conversion of the NL query. The corrected pair is determined to satisfy criteria of a data store and is stored as synthetic data of the data store.