Answer Finding Guided by Question Semantic Constraints

As part of the task of automated question answering from a large collection of text documents, the reduction of the search space to a smaller set of document passages that are actually searched for answers constitutes a difficult but rewarding research issue. We propose a set of precision-enhancing filters for passage retrieval based on semantic constraints detected in the submitted questions. The approach improves the performance of the underlying question answering system in terms of both answer accuracy and time performance.