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Leveraging Community-Built Knowledge for Type Coercion in Question Answering

机译:在问答中利用社区构建的知识进行类型强制

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Watson, the winner of the Jeopardy! challenge, is a state-of-the-art open-domain Question Answering system that tackles the fundamental issue of answer typing by using a novel type coercion (TyCor) framework, where candidate answers are initially produced without considering type information, and subsequent stages check whether the candidate can be coerced into the expected answer type. In this paper, we provide a high-level overview of the TyCor framework and discuss how it is integrated in Watson, focusing on and evaluating three TyCor components that leverage the community built semi-structured and structured knowledge resources — DBpedia (in conjunction with the YAGO ontology), Wikipedia Categories and Lists. These resources complement each other well in terms of precision and granularity of type information, and through links to Wikipedia, provide coverage for a large set of instances.
机译:沃森(Jackson)的获胜者!挑战是最先进的开放域问答系统,它通过使用新型类型强制(TyCor)框架解决答案键入的基本问题,该框架最初会在不考虑类型信息的情况下生成候选答案,并随后进行后续阶段检查候选人是否可以被强制转换为预期的答案类型。在本文中,我们提供了TyCor框架的高级概述,并讨论了如何将其集成到Watson中,重点研究并评估了三个TyCor组件,这些组件利用了社区构建的半结构化和结构化知识资源-DBpedia(与YAGO本体),维基百科类别和列表。这些资源在类型信息的精度和粒度方面相互补充,并且通过链接到Wikipedia,为大量实例提供了覆盖范围。

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