论文标题
活机：非典型动画研究
Living Machines: A study of atypical animacy
论文作者
论文摘要
本文提出了一种新的动画检测方法，即确定实体是否表示为动画的任务。特别是，这项工作集中在非典型动画上，并研究了通常将无生命的对象（特别是机器）赋予动画属性的情况。为了解决这个问题，我们根据19世纪的英语句子创建了第一个用于非典型动画检测的数据集，其机器表示为动画或无生命。我们的方法基于语言建模的最新创新，特别是bert上下文化的单词嵌入，以更好地捕获单词的细粒度上下文属性。我们提出了一条完全无监督的管道，可以轻松地适应不同的上下文，并在既定的动画数据集和我们新引入的资源上报告其性能。我们表明，我们的方法提供了非典型动画的更准确表征，尤其是应用于高度复杂的语言使用形式时。
This paper proposes a new approach to animacy detection, the task of determining whether an entity is represented as animate in a text. In particular, this work is focused on atypical animacy and examines the scenario in which typically inanimate objects, specifically machines, are given animate attributes. To address it, we have created the first dataset for atypical animacy detection, based on nineteenth-century sentences in English, with machines represented as either animate or inanimate. Our method builds on recent innovations in language modeling, specifically BERT contextualized word embeddings, to better capture fine-grained contextual properties of words. We present a fully unsupervised pipeline, which can be easily adapted to different contexts, and report its performance on an established animacy dataset and our newly introduced resource. We show that our method provides a substantially more accurate characterization of atypical animacy, especially when applied to highly complex forms of language use.
