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As an important form of complex questions, definition question attracts much attention from QA researchers. For many of the definition question answering systems, it is a core step to rank the candidate answer sentences, so that the top-k in the ranked list can be extracted. We integrate these evidences as features into a whole framework, and propose a novel method to learning weights of these features to rank the candidate answer sentences.
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