Answer Ranking

task ID: answerranking

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A Joint Model for Answer Sentence Ranking and Answer Extraction

Authors: nan

Publication: TIPSTER (2016)

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AbstractAnswer sentence ranking and answer extraction are two key challenges in question answering that have traditionally been treated in isolation, i.e., as independent tasks. In this article, we (1) explain …...

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MTE-NN at SemEval-2016 Task 3: Can Machine Translation Evaluation Help Community Question Answering?

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We present a system for answer ranking (SemEval-2016 Task 3, subtask A) that is a direct adaptation of a pairwise neural net- work model for machine translation evalua- tion (MTE). …...

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Tell Me Why: Using Question Answering as Distant Supervision for Answer Justification

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AbstractFor many applications of question answering (QA), being able to explain why a given model chose an answer is critical. However, the lack of labeled data for answer justifications makes …...

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Modeling Transitions of Focal Entities for Conversational Knowledge Base Question Answering

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AbstractConversational KBQA is about answering a sequence of questions related to a KB. Follow-up questions in conversational KBQA often have missing information referring to entities from the conversation history. In …...

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