Enhancing property and type detection for a QA system over linked data

摘要

In this paper we discuss the detection of concepts for question answering systems using Linked Data. The emphasis will be put on the detection of types and properties. We will present different methods that are currently being used for these tasks and the improvements proposed to improve the performance of QA systems. Both modules have been trained by analyzing a large subset of Wikipedia pages which have a correspondent in the DBpedia [1] knowledge base. The paper also presents the preliminary test results for both modules which show that the proposed methods have a good performance and should be integrated in the next version of our QA system over Linked Data.