生命机器：非典型生命性研究
Living Machines: A study of atypical animacy
摘要：
本文提出了一种新的方法来检测动画，确定一个实体是否表示为动画的文本中的任务。特别是，这项工作的重点是非典型的生命力，并检查的情况下，通常无生命的物体，特别是机器，赋予动画属性。为了解决这个问题，我们创建了第一个用于非典型生命检测的数据集，该数据集基于19世纪的英语句子，机器被表示为有生命或无生命。我们的方法建立在最近的创新语言建模，特别是BERT上下文词嵌入，以更好地捕捉细粒度的上下文属性的话。我们提出了一个完全无监督的管道，它可以很容易地适应不同的上下文，并报告其性能的一个既定的动画数据集和我们新引入的资源。我们表明，我们的方法提供了一个更准确的表征非典型的生命力，特别是当应用到高度复杂的语言使用形式。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
