L2S: Transforming Natural Language Questions into SQL Queries

The reliability of a question answering system is bounded by the availability of resources and linguistic tools. In this paper, we introduce a hybrid approach to transforming natural language questions into structured queries. It alleviates the lack of experts in domain observation and the deficient performance of linguistic tools. Specifically, we exploit the semantic information for mapping natural language terminologies to structured query and bipartite graph model for the matching phase. Experimental results on the Vietnam national university entrance exam dataset and the Geoqueries880 dataset achieve accuracies of 91.14% and 87.55%, respectively.