Automatic Translation of Competency Questions into SPARQL-OWL Queries

Abstract

The process of ontology authoring is inseparably connected with the quality assurance phase. One can verify the maturity and correctness of a given ontology by evaluating how many competency questions give correct answers. Competency questions are defined as a set of questions expressed in natural language that the finished ontology should be able to answer to correctly. Although this method can easily indicate what is the development status of an ontology, one has to translate competency questions from natural language into an ontology query language. This task is very hard and time consuming. To overcome this problem, my PhD thesis focuses on methods for automatically checking answerability of competency questions for a given ontology and proposing SPARQL-OWL query (OWL-aware SPARQL query) for each question where it is possible to create the query. Because the task of automatic translation from competency questions to SPARQL-OWL queries is a novel one, besides a method, we have proposed a new benchmark to evaluate such translation.