Narratives include a rich source of events unfolding over time and context. Automatic understanding of these events may provide a summarised comprehension of the narrative for further computation (such as reasoning). In this paper, we study the Information Status (IS) of the events and propose a novel challenging task: the automatic identification of new events in a narrative. We define an event as a triplet of subject, predicate, and object. The event is categorized as new with respect to the discourse context and whether it can be inferred through commonsense reasoning. We annotated a publicly available corpus of narratives with the new events at sentence level using human annotators. We present the annotation protocol and a study aiming at validating the quality of the annotation and the difficulty of the task. We publish the annotated dataset, annotation materials, and machine learning baseline models for the task of new event extraction for narrative understanding.
翻译:叙事包括一个丰富的时间和背景事件来源。对这些事件的自动理解可以提供对叙事的概括理解,供进一步计算(例如推理)。我们在本文件中研究事件的信息状况(IS),并提出新的具有挑战性的任务:在叙事中自动确定新的事件。我们把事件定义为一个三重主题、前提和对象。该事件被归类为与谈话背景有关的新事件,以及是否可以通过常识推理加以推断。我们用人类注解员在句子上附加了一套公开的叙事,说明新的事件。我们提出注解协议和一项旨在验证注解质量和任务难度的研究。我们出版了一个附加说明的数据集、注解材料和机器学习基线模型,用于执行新事件提取任务,以了解叙事。