DBPal: A learned NL-interface for databases
Date
2018
Editor(s)
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Source Title
SIGMOD '18 Proceedings of the 2018 International Conference on Management of Data
Print ISSN
0730-8078
Electronic ISSN
Publisher
ACM
Volume
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Pages
1765 - 1768
Language
English
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Abstract
In this demo, we present DBPal, a novel data exploration tool with a natural language interface. DBPal leverages recent advances in deep models to make query understanding more robust in the following ways: First, DBPal uses novel machine translation models to translate natural language statements to SQL, making the translation process more robust to paraphrasing and linguistic variations. Second, to support the users in phrasing questions without knowing the database schema and the query features, DBPal provides a learned auto-completion model that suggests to users partial query extensions during query formulation and thus helps to write complex queries.