Semantic representations for knowledge modeling of a Natural Language Interface to Databases using ontologies

Despite the large number of Natural Language Interfaces to Databases (NLIDB) that have been implemented, they do not guarantee to provide a correct response in 100% of the queries. In this paper, we present a way of semantic modelling the elements that integrate the knowledge of a NLIDB with the aim of increasing the number of correctly-answered queries. We design semantic representations in order to: a) model any relational database schema and its relationship with the natural language and b) add metadata to natural language words to enable our NLIDB to interpret natural language queries that contain superlatives. We configured our NLIDB in a relational database that we migrated from Geobase and used the Geoquery250 corpus to evaluate its performance. We compare its performance with the interfaces ELF, Freya and NLP-Reduce. The results indicate that our proposal allowed our NLIDB to obtain the best performance.