Pseudo Relevance Feedback Using Named Entities for Question Answering

Relevance feedback has already proven its usefulness in probabilistic information retrieval (IR). In this research we explore whether a pseudo relevance feedback technique on IR can improve the Question Answering task (QA). The basis of our exploration is the use of relevant named entities from the top retrieved documents as clues of relevance. We discuss two interesting findings from these experiments: the reasons the results were not improved, and the fact that today’s metrics of IR evaluation on QA do not reflect the results obtained by a QA system.