# Lost in Recursion: Mining Rich Event Semantics in Knowledge Graphs

arXiv: https://arxiv.org/abs/2404.16405 · HTML: https://mlsanity.com/paper/2404.16405/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 15 of its 55 references that are in the map.
- First posted on arXiv 25 Apr 2024.

## Builds on (most cited first, 15 of 15)

- [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://mlsanity.com/paper/1908.10084/) (2019)
- [EventKG: A Multilingual Event-Centric Temporal Knowledge Graph](https://mlsanity.com/paper/1804.04526/) (2018)
- [The Future is not One-dimensional: Complex Event Schema Induction by Graph Modeling for Event Prediction](https://mlsanity.com/paper/2104.06344/) (2021)
- [Media Cloud: Massive Open Source Collection of Global News on the Open Web](https://mlsanity.com/paper/2104.03702/) (2021)
- [Open-Domain Hierarchical Event Schema Induction by Incremental Prompting and Verification](https://mlsanity.com/paper/2307.01972/) (2023)
- [A Survey on Event-based News Narrative Extraction](https://mlsanity.com/paper/2302.08351/) (2023)
- [Conflicts, Villains, Resolutions: Towards models of Narrative Media Framing](https://mlsanity.com/paper/2306.02052/) (2023)
- [Searching News Articles Using an Event Knowledge Graph Leveraged by Wikidata](https://mlsanity.com/paper/1904.05557/) (2019)
- [Event Linking: Grounding Event Mentions to Wikipedia](https://mlsanity.com/paper/2112.07888/) (2021)
- [CORE-GPT: Combining Open Access research and large language models for credible, trustworthy question answering](https://mlsanity.com/paper/2307.04683/) (2023)
- [Viewpoint Discovery and Understanding in Social Networks](https://mlsanity.com/paper/1810.11047/) (2018)
- [News Article Retrieval in Context for Event-centric Narrative Creation](https://mlsanity.com/paper/2106.16053/) (2021)
- [Narrative Maps: An Algorithmic Approach to Represent and Extract Information Narratives](https://mlsanity.com/paper/2009.04508/) (2020)
- [It's the Same Old Story! Enriching Event-Centric Knowledge Graphs by Narrative Aspects](https://mlsanity.com/paper/2205.03876/) (2022)
- [OEKG: The Open Event Knowledge Graph](https://mlsanity.com/paper/2302.14688/) (2023)

## Built on by (most cited first, 1 of 1)

- [A Conceptual Model for Attributions in Event-Centric Knowledge Graphs](https://mlsanity.com/paper/2503.03563/) (2025)

## Abstract (arXiv)

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.