论文标题
使用凝视对参考和非参考的IT进行分类
Classifying Referential and Non-referential It Using Gaze
论文作者
论文摘要
在处理文本时，人类和机器必须在代词的不同用途之间消除歧义，包括非参考，名义上的放置或条款的放纵。在本文中，我们使用眼神跟踪数据来了解人类如何执行这种歧义。我们使用这些知识来改善其自动分类。我们表明，通过使用凝视数据和Pos-Tagger，我们能够显着胜过公共基线，并在其三个类别之间进行分类，其准确性与基于语言的方法相当。此外，特定凝视特征的歧视能力为人类处理代词的方式提供了信息，据我们所知，该代词尚未使用自然阅读任务中的数据进行探索。
When processing a text, humans and machines must disambiguate between different uses of the pronoun it, including non-referential, nominal anaphoric or clause anaphoric ones. In this paper, we use eye-tracking data to learn how humans perform this disambiguation. We use this knowledge to improve the automatic classification of it. We show that by using gaze data and a POS-tagger we are able to significantly outperform a common baseline and classify between three categories of it with an accuracy comparable to that of linguisticbased approaches. In addition, the discriminatory power of specific gaze features informs the way humans process the pronoun, which, to the best of our knowledge, has not been explored using data from a natural reading task.
