Abstract
Work on Question Answering (QA) has argued that the relation between a question and its answer(s) can be cast in terms of logical entailment. In this talk a QA framework that takes advantage of question semantics and a computational framework for text entailment is presented. To be able to process complex questions in this framework, question decompositions need to be generated. Complex questions are decomposed by a random walk on a bipartite graph of relations established between concepts related to the question and sub-questions derived from topic-relevant passages. Decomposed questions and textual entailment significantly enhance the accuracy and comprehensiveness of extracted answers.