查看文章

Retrieving topically-relevant text passages in documents has been studied many times, but finding non-factoid, multiple sentence answers to web queries is a different task that is becoming increasingly important for applications such as mobile search. As the first stage of developing retrieval models for "answer passages", we describe the process of creating a test collection of questions and multiple-sentence answers based on the TREC GOV2 queries and documents. This annotation shows that most of the description-length TREC queries do in fact have passage-level answers. We then examine the effectiveness of current passage retrieval models in terms of finding passages that contain answers. We show that the existing methods are not effective for this task, and also observe that the relative performance of these methods in retrieving answers does not correspond to their performance in retrieving relevant …