HIE-SQL: History Information Enhanced Network for Context-Dependent Text-to-SQL Semantic Parsing

Anonymous

Abstract: Previous works of context-dependent text-to-SQL semantic parsing leverage context-dependence information either from interaction history utterances or the previous predicted SQL queries but fail in taking advantage of both since of the mismatch between natural language and logic-form SQL. In this work, we propose a History Information Enhanced text-to-SQL model (HIE-SQL) to exploit context-dependence information from both history utterances and the last predicted SQL query. In view of the mismatch, we treat natural language and SQL as two modalities and propose a bimodal pre-trained model to bridge the gap between them. Besides, we design a schema linking graph to enhance connections from utterances and the SQL query to the database schema. We achieve new state-of-the-art results on the two context-dependent text-to-SQL benchmarks, SparC and CoSQL, at the writing time.

Paper Type: short