TypeSQL: Knowledge-based type-aware neural text-to-SQL generation

Tao Yu, Zifan Li, Zilin Zhang, Rui Zhang, Dragomir Radev

Research output: Chapter in Book/Report/Conference proceedingConference contribution

35 Scopus citations

Abstract

Interacting with relational databases through natural language helps users of any background easily query and analyze a vast amount of data. This requires a system that understands users' questions and converts them to SQL queries automatically. In this paper we present a novel approach, TYPESQL, which views this problem as a slot filling task. Additionally, TYPESQL utilizes type information to better understand rare entities and numbers in natural language questions. We test this idea on the WikiSQL dataset and outperform the prior state-of-the-art by 5.5% in much less time. We also show that accessing the content of databases can significantly improve the performance when users' queries are not wellformed. TYPESQL gets 82.6% accuracy, a 17.5% absolute improvement compared to the previous content-sensitive model.

Original languageEnglish (US)
Title of host publicationShort Papers
PublisherAssociation for Computational Linguistics (ACL)
Pages588-594
Number of pages7
ISBN (Electronic)9781948087292
StatePublished - 2018
Event2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2018 - New Orleans, United States
Duration: Jun 1 2018Jun 6 2018

Publication series

NameNAACL HLT 2018 - 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - Proceedings of the Conference
Volume2

Conference

Conference2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2018
CountryUnited States
CityNew Orleans
Period6/1/186/6/18

All Science Journal Classification (ASJC) codes

  • Linguistics and Language
  • Language and Linguistics
  • Computer Science Applications

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