Linguistic modeling of linked open data for question answering

Abstract

With the evolution of linked open data sources, question answering regains importance as a way to make data accessible and explorable to the public. The triple structure of RDF-data at the same time seems to predetermine question answering for being devised in its native subject-verb-object form. The devices of natural language, however, often exceed this trFiple-centered model. But RDF does not preclude this point of view. Rather, it depends on the modeling. As part of a government funded research project named Alexandria, we implemented an approach to question answering that enables the user to ask questions in ways that may involve more than binary relations.