NLP Questions Answering Using DBpedia and YAGO

Abstract

In this paper, we present results of employing DBpedia and YAGO as lexical databases for answering questions formulated in the natural language. The proposed solution has been evaluated for answering class 1 and class 2 questions (out of 5 classes defined by Moldovan for TREC conference). Our method uses dependency trees generated from the user query. The trees are browsed for paths leading from the root of the tree to the question subject. We call those paths fibers and they represent the user intention. The question analysis consists of three stages: query analysis, query breakdown and information retrieval. The aim of those stages is the detection of the entities of interest and its attributes, indicating the users’ domain of interest. The user query is then converted into a SPARQL query and sent to the DBpedia and YAGO databases. The baseline and the extended methods are presented and the quality of the solution is evaluated and discussed.