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Actionable Clause Detection from Non-imperative Sentences in Howto Instructions: A Step for Actionable Information Extraction

机译:从HowTo指令中的非命令句子中的可操作子阶段检测:可操作信息提取的步骤

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Constructing a sophisticated experiential knowledge base for solving daily problems is essential for many intelligent human centric applications. A key issue is to convert natural language instructions into a form that can be searched semantically or processed by computer programs. This paper presents a methodology for automatically detecting actionable clauses in how-to instructions. In particular, this paper focuses on processing non-imperative clauses to elicit implicit instructions or commands. Based on some dominant linguistic styles in how-to instructions, we formulate the problem of detecting actionable clauses using linguistic features including syntactic and modal characteristics. The experimental results show that the features we have extracted are very promising in detecting actionable non-imperative clauses. This algorithm makes it possible to extract complete action sequences to a structural format for problem solving tasks.
机译:构建用于解决日常问题的复杂的经验知识库对于许多智能人为中心的应用是必不可少的。一个关键问题是将自然语言指令转换为可以在语义上搜索或由计算机程序处理的形式。本文介绍了一种自动检测如何在如何达指令中的可操作条款的方法。特别是,本文侧重于处理非命令条款以引出隐式指示或命令。基于一些主导语言样式在如何指导中,我们使用语言特征制定检测可操作条款的问题,包括句法和模态特征。实验结果表明,我们提取的特征在检测可操作的非势在条款方面非常有前途。该算法使得可以将完整的动作序列提取到结构格式以进行解决问题解决任务。

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