Hierarchical Event Grounding


  • Jiefu Ou Carnegie Mellon University
  • Adithya Pratapa Carnegie Mellon University
  • Rishubh Gupta Carnegie Mellon University
  • Teruko Mitamura Carnegie Mellon University




SNLP: Information Extraction


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. 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. 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. Furthermore, we demonstrate the systems' ability to aid hierarchical discovery among unseen events. Code is available at https://github.com/JefferyO/Hierarchical-Event-Grounding




How to Cite

Ou, J., Pratapa, A., Gupta, R., & Mitamura, T. (2023). Hierarchical Event Grounding. Proceedings of the AAAI Conference on Artificial Intelligence, 37(11), 13437-13445. https://doi.org/10.1609/aaai.v37i11.26576



AAAI Technical Track on Speech & Natural Language Processing