Semantic model for improving the performance of natural language interfaces to databases

Abstract

Despite the fact that since the late 60s many Natural Language Interfaces to Databases (NLIDBs) have been developed, up to now many problems continue, which prevent the translation process from natural language to SQL to be totally successful. Some of the main problems that have been encountered relate to 1) achieving domain independence, 2) the use of words or phrases of different syntactic categories for referring to tables and columns, and 3) semantic ellipsis. This paper introduces a new method for modeling databases that includes relevant information for improving the performance of NLIDBs. This method will be useful for solving many problems found in the translation from natural language to SQL, using a database model that contains linguistic information that provides more semantic information than that found in conventional database models (such as the extended entity-relationship model) and those used in previous NLIDBs. © 2011 Springer-Verlag.