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:活动基础旨在将文字组合中提及的内容与知识库(KB)中的事件联系起来。先前关于这项任务的工作主要侧重于将单一的KB事件联系起来,从而忽略事件的等级方面。文档中的事件通常被描述在不同层次的时空颗粒度(Glavas等人,2014年)。这些等级关系被用于叙述理解和系统构造的下游任务。在这项工作中,我们介绍了需要处理KB的等级事件结构的事件定位任务的扩展。我们提议的任务涉及将提及的事件标签与KB的一个子事件分类联系起来。我们提议了一种检索方法,通过辅助等级损失(Murty等人,2018年)利用事件等级结构(事件分类)。关于从维基百科和维基数据自动创建的多语种数据集,我们的实验表明等级损失在检索和重新排序基线方面的有效性(Wu等人,2020年;Pratapa,Gupta,和Mitamura,2022年)。此外,我们展示了系统在帮助在不可见事件之间进行等级发现的能力。