Event grounding aims at linking mention references in text corpora to events from a knowledge base (KB). Previous work on this task focused primarily on linking to a single KB event, thereby overlooking the hierarchical aspects of events. Events in documents are typically described at various levels of spatio-temporal granularity (Glavas et al. 2014). These hierarchical relations are utilized in downstream tasks of narrative understanding and schema construction. In this work, we present an extension to the event grounding task that requires tackling hierarchical event structures from the KB. Our proposed task involves linking a mention reference to a set of event labels from a subevent hierarchy in the KB. We propose a retrieval methodology that leverages event hierarchy through an auxiliary hierarchical loss (Murty et al. 2018). On an automatically created multilingual dataset from Wikipedia and Wikidata, our experiments demonstrate the effectiveness of the hierarchical loss against retrieve and re-rank baselines (Wu et al. 2020; Pratapa, Gupta, and Mitamura 2022). Furthermore, we demonstrate the systems' ability to aid hierarchical discovery among unseen events.

翻译：事件锚定旨在将文本语料中的提及指称链接至知识库（KB）中的事件。以往相关工作主要聚焦于链接至单个知识库事件，从而忽视了事件的层级特性。文档中的事件通常以不同程度的时空粒度进行描述（Glavas等，2014）。这些层级关系被应用于叙事理解与模式构建等下游任务中。本研究提出一种需要处理知识库中层级事件结构的事件锚定任务扩展。我们提出的任务要求将提及指称链接至知识库子事件层级中的一组事件标签。我们提出一种通过辅助层级损失（Murty等，2018）来利用事件层级的检索方法。在基于维基百科和维基数据自动创建的多语言数据集上，我们的实验证明了层级损失相对于检索再排序基线方法（Wu等，2020；Pratapa、Gupta和Mitamura，2022）的有效性。此外，我们还展示了系统在辅助发现未知事件层级关系方面的能力。