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Answer Determination for Natural Language Questioning

机译:自然语言提问的答案确定

摘要

Open-domain question answering is the task of finding a concise answer to a natural language question using a large domain, such as the Internet. The use of a semantic role labeling approach to the extraction of the answers to an open domain factoid (Who/When/What/Where) natural language question that contains a predicate is described. Semantic role labeling identities predicates and semantic argument phrases in the natural language question and the candidate sentences. When searching for an answer to a natural language question, the missing argument in the question is matched using semantic parses of the candidate answers. Such a technique may improve the accuracy of a question answering system and may decrease the length of answers for enabling voice interface to a question answering system.
机译:开放域问题回答是使用大型域(例如Internet)查找自然语言问题的简洁答案的任务。描述了使用语义角色标记方法来提取包含谓词的开放域事实(Who / When / What / Where / Where)自然语言问题的答案。自然语言问题和候选句子中的语义角色标记身份谓词和语义论点短语。在搜索自然语言问题的答案时,使用候选答案的语义分析来匹配问题中缺少的参数。这样的技术可以提高问答系统的准确性,并且可以减小用于使语音接口与问答系统相连接的答案的长度。

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