Determining Relative Argument Specificity and Stance for Complex Argumentative Structures
Determining Relative Argument Specificity and Stance for Complex Argumentative Structures
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DOI：
10.18653/v1/p19-1456
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发表时间：
2019-06
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影响因子：
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通讯作者：
Esin Durmus;Faisal Ladhak;Claire Cardie
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文献类型：
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作者：
Esin Durmus;Faisal Ladhak;Claire Cardie
用于自动论点生成和辩论的系统需要以下能力：（1）确定论点中所采用的任何主张的立场，以及（2）评估每个主张相对于论点上下文的特异性。然而，现有的工作对理解主张的特异性和立场，一直局限于研究的论证结构是相对较浅的，最经常的是由一个单一的主张，直接支持或反对的论点。在本文中，我们处理这些任务的背景下，复杂的参数上的一组不同的主题。特别是，我们的数据集由741个有争议的主题的人工策划的论点树组成，涵盖95，312个独特的主张;论点线通常是深度2到6。我们发现，随着一对索赔之间的距离增加沿着的论点路径，确定一对索赔的相对特异性变得更容易，并确定他们的相对立场变得更难。
Systems for automatic argument generation and debate require the ability to (1) determine the stance of any claims employed in the argument and (2) assess the specificity of each claim relative to the argument context. Existing work on understanding claim specificity and stance, however, has been limited to the study of argumentative structures that are relatively shallow, most often consisting of a single claim that directly supports or opposes the argument thesis. In this paper, we tackle these tasks in the context of complex arguments on a diverse set of topics. In particular, our dataset consists of manually curated argument trees for 741 controversial topics covering 95,312 unique claims; lines of argument are generally of depth 2 to 6. We find that as the distance between a pair of claims increases along the argument path, determining the relative specificity of a pair of claims becomes easier and determining their relative stance becomes harder.