Paper: Modern Natural Language Interfaces To Databases: Composing Statistical Parsing With Semantic Tractability

ACL ID C04-1021
Title Modern Natural Language Interfaces To Databases: Composing Statistical Parsing With Semantic Tractability
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2004
Authors

Natural Language Interfaces to Databases (NLIs) can benefit from the advances in statis- tical parsing over the last fifteen years or so. However, statistical parsers require training on a massive, labeled corpus, and manually cre- ating such a corpus for each database is pro- hibitively expensive. To address this quandary, this paper reports on the PRECISE NLI, which uses a statistical parser as a “plug in”. The pa- per shows how a strong semantic model cou- pled with “light re-training” enables PRECISE to overcome parser errors, and correctly map from parsed questions to the corresponding SQL queries. We discuss the issues in using statistical parsers to build database-independent NLIs, and report on experimental results with the benchmark ATIS data set where PRECISE achieves 94%...