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.

翻译：我们的世界由各种复杂程度的事件所塑造，这既包括本地农贸市场等小型局部事件，也包括政治和军事冲突等大型复杂事件。后者通常不是直接观察到的，而是通过报纸或社交媒体等中介的透镜被感知。换言之，我们并非直接目睹这些事件的展开，而是面对围绕它们的叙事。此类叙事捕捉了复杂事件的不同方面，并可能因叙述者而异。因此，它们为现实世界的事件提供了丰富的语义。在本文中，我们展示了如何构建和利用有关复杂事件的叙事。我们基于递归节点提供了一种叙事的正式表示，以表示多个细节层次，并讨论了如何将叙事绑定到以事件为中心的知识图谱上。此外，我们提出了一种基于增量提示技术的算法，该算法从文本中挖掘此类叙事，以解释对复杂事件的不同视角。最后，我们在概念验证中展示了其有效性及未来的研究方向。