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

• URL: http://arxiv.org/abs/2203.07376v1
• Date: Mon, 14 Mar 2022 11:58:37 GMT
• Title: HIE-SQL: History Information Enhanced Network for Context-Dependent Text-to-SQL Semantic Parsing
• Authors: Yanzhao Zheng, Haibin Wang, Baohua Dong, Xingjun Wang, Changshan Li
• Abstract summary: We propose a History Information Enhanced text-to-the-art model (HIE-) to exploit context-dependence information from both history utterances and the last predictedsql query. We show our methods improve the performance of HIE- by a significant margin, which achieves new state-of-the-art results on the two context-dependent text-to-the-art benchmarks.
• Score: 1.343950231082215
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Recently, context-dependent text-to-SQL semantic parsing which translates natural language into SQL in an interaction process has attracted a lot of attention. Previous works 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 show our history information enhanced methods improve the performance of HIE-SQL by a significant margin, which achieves new state-of-the-art results on the two context-dependent text-to-SQL benchmarks, the SparC and CoSQL datasets, at the writing time.

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