Abstract
Our world is shaped by events of various complexity. This includes both small-scale local events like local farmer markets and large complex events like political and military conflicts. The latter are typically not observed directly but through the lenses of intermediaries like newspapers or social media. In other words, we do not witness the unfolding of such events directly but are confronted with narratives surrounding them. Such narratives capture different aspects of a complex event and may also differ with respect to the narrator. Thus, they provide a rich semantics concerning real-world events. In this paper, we show how narratives concerning complex events can be constructed and utilized. We provide a formal representation of narratives based on recursive nodes to represent multiple levels of detail and discuss how narratives can be bound to event-centric knowledge graphs. Additionally, we provide an algorithm based on incremental prompting techniques that mines such narratives from texts to account for different perspectives on complex events. Finally, we show the effectiveness and future research directions in a proof of concept.
Abstract (translated)
我们的世界是由各种复杂事件塑造的。这包括小型的地方事件，如当地农民市场，以及大型复杂事件，如政治和军事冲突。后者的通常不是直接观察到的，而是通过中介机构，如报纸或社交媒体，透过他们的镜头观察到的。换句话说，我们不是直接见证了这些事件的展开，而是面对着围绕这些事件的故事。这些故事捕捉了复杂事件的不同方面，而且也可能与叙述者的观点有所不同。因此，它们提供了关于现实世界事件的丰富语义。在本文中，我们展示了如何构建和利用关于复杂事件的叙述。我们根据递归节点的形式给出了叙述的正式表示，并讨论了叙述如何与事件中心化的知识图谱相联系。此外，我们还基于增量提示技术提供了算法，用于从文本中挖掘这类叙述，以反映复杂事件的不同观点。最后，我们在概念证明中展示了这种方法的有效性和未来的研究方向。
URL
https://arxiv.org/abs/2404.16405
