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Using Wikipedia and Semantic Resources to Find Answer Types and Appropriate Answer Candidate Sets in Question Answering

机译:使用维基百科和语义资源来查找答案类型和适当的答案候选集合答案应答

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This paper proposes a new idea that uses Wikipedia categories as answer types and defines candidate sets inside Wikipedia. The focus of a given question is searched in the hierarchy of Wikipedia main pages. Our searching strategy combines head-noun matching and synonym matching provided in semantic resources. The set of answer candidates is determined by the entry hierarchy in Wikipedia and the hyponymy hierarchy in WordNet. The experimental results show that the approach can find candidate sets in a smaller size but achieve better performance especially for ARTIFACT and ORGANIZATION types, where the performance is better than state-of-the-art Chinese factoid QA systems.
机译:本文提出了一种新的想法,它使用Wikipedia类别作为答案类型,并在维基百科内定义候选集。在维基百科主要页面的层次结构中搜索给定问题的重点。我们的搜索策略结合了语义资源中提供的头名词匹配和同义词匹配。该组答案候选者由Wikipedia中的条目层次结构和Wordnet中的Shop onamy层次结构决定。实验结果表明,该方法可以在较小尺寸的尺寸下找到候选集,但尤其是对于伪像和组织类型来实现更好的性能,在那里性能优于最先进的中国因子QA系统。

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