Whats New? Identifying the Unfolding of New Events in Narratives
This work addresses a novel challenge in narrative understanding for computational applications like reasoning, though it is incremental as it builds on existing event extraction methods.
The paper tackles the problem of automatically identifying new events in narratives by defining events as subject-predicate-object triplets and categorizing them based on discourse context and commonsense inference, resulting in a publicly available annotated dataset and baseline models for this task.
Narratives include a rich source of events unfolding over time and context. Automatic understanding of these events provides 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 study 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.