An Efficient Passage Ranking Technique For a QA System

Question answering (QA) systems provide an intuitive way of requesting concise information from a givendata source. An important stage of such a system is the passage ranking stage, which ranks the possibleanswers based on their relevance to the question. There has been a lot of previous work on passageranking, employing lexical, semantic or syntactic methods, but to our knowledge there has been no methodthat comprehensively combines all 3 features. In this paper, we present a passage ranking technique thatleverages lexical, semantic and syntactic features together to rank the answers efficiently and effectively.This paper highlights the differences and improvements of the proposed technique over existing state-ofthe-art techniques like SSTK and IBM Model. The passage ranking technique has been evaluated withTREC QA dataset and is observed to give a significant 26.5% improvement in MRR over the existing stateof-the-art SSTK technique.