What Gets Echoed? Understanding the “Pointers” in Explanations of Persuasive Arguments
What Gets Echoed? Understanding the “Pointers” in Explanations of Persuasive Arguments
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DOI：
10.18653/v1/d19-1289
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发表时间：
2019-11
期刊：
影响因子：
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通讯作者：
D. Atkinson;K. Srinivasan;Chenhao Tan
中科院分区：
文献类型：
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作者：
D. Atkinson;K. Srinivasan;Chenhao Tan
人工智能是日常生活的核心，也是人工智能社区越来越感兴趣的话题。为了研究提供自然语言解释的过程，我们利用/r/ChangeMyView子Reddit的动态来构建一个数据集，其中包含36 K自然发生的解释，说明为什么论点具有说服力。我们提出了一个新的词级预测任务，以调查解释如何选择性地重用，或回声，从被解释的信息（以下简称为“巨大”）。我们开发的功能，以捕捉一个字的属性在巨人，并表明，我们提出的功能不仅有相对较强的预测能力的回声的一个字的解释，但也增强了神经方法生成的解释。特别是，虽然一个词本身的非上下文属性对停用词更有价值，但一个巨人的组成部分之间的相互作用在预测实词的呼应方面至关重要。我们还发现了一个单词被重复的有趣模式。例如，虽然名词一般不太可能被呼应，但主语和宾语根据它们的来源，在解释中更有可能被呼应。
Explanations are central to everyday life, and are a topic of growing interest in the AI community. To investigate the process of providing natural language explanations, we leverage the dynamics of the /r/ChangeMyView subreddit to build a dataset with 36K naturally occurring explanations of why an argument is persuasive. We propose a novel word-level prediction task to investigate how explanations selectively reuse, or echo, information from what is being explained (henceforth, explanandum). We develop features to capture the properties of a word in the explanandum, and show that our proposed features not only have relatively strong predictive power on the echoing of a word in an explanation, but also enhance neural methods of generating explanations. In particular, while the non-contextual properties of a word itself are more valuable for stopwords, the interaction between the constituent parts of an explanandum is crucial in predicting the echoing of content words. We also find intriguing patterns of a word being echoed. For example, although nouns are generally less likely to be echoed, subjects and objects can, depending on their source, be more likely to be echoed in the explanations.