Semantic question answering system over linked data using relational patterns

Abstract

Question answering is the task of answering questions in natural language. Linked Data project and Semantic Web community made it possible for us to query structured knowledge bases like DBpedia and YAGO. Only expert users, however, with the knowledge of RDF and ontology definitions can build correct SPARQL queries for querying knowledge bases formally. In this paper, we present a method for mapping natural language questions to ontology-based structured queries to retrieve direct answers from open knowledge bases (linked data). Our tool is based on translating natural language questions into RDF triple patterns using the dependency tree of the question text. In addition, our method uses relational patterns extracted from the Web. We tested our tool using questions from QALD-2, Question Answering over Linked Data challenge track and found promising preliminary results. © 2013 ACM.