Lightweight natural language database interfaces

Abstract

Most natural language database interfaces suffer from the translation knowledge portability problem, and are vulnerable to ill-formed questions because of their deep analysis. To alleviate those problems, this paper proposes a lightweight approach to natural language interfaces, where translation knowledge is semi-automatically acquired and user questions are only syntactically analyzed. For the acquisition of translation knowledge, first, a target database is reverse-engineered into a physical database schema on which domain experts annotate linguistic descriptions to produce a pER (physically-derived Entity-Relationship) schema. Next, from the pER schema, initial translation knowledge is automatically extracted. Then, it is extended with synonyms from lexical databases. In the stage of question answering, this semi-automatically constructed translation knowledge is then used to resolve translation ambiguities.