Hierarchical Event Grounding
Jiefu Ou, Adithya Pratapa, Rishubh Gupta, Teruko Mitamura
Abstract
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 (Glavaš 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. 1
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 58d9b0b9-ea03-4206-90e0-62796c470f00Builds on5
- Unsupervised Cross-lingual Representation Learning at ScaleAlexis Conneau, Kartikay Khandelwal, Naman Goyal, Vishrav Chaudhary et al.ACL 2020 · 539 citations
- Scalable Zero-shot Entity Linking with Dense Entity RetrievalLedell Wu, Fabio Petroni, Martin Josifoski, Sebastian Riedel et al.EMNLP 2020 · 336 citations
- Hierarchical Entity Typing via Multi-level Learning to RankTongfei Chen, Yunmo Chen, Benjamin Van DurmeACL 2020 · 51 citations
- ESTER: A Machine Reading Comprehension Dataset for Reasoning about Event Semantic RelationsRujun Han, I-Hung Hsu, Jiao Sun, Julia Baylon et al.EMNLP 2021 · 30 citations
- Modeling Fine-Grained Entity Types with Box EmbeddingsYasumasa Onoe, Michael Boratko, Andrew McCallum, Greg DurrettACL 2021
Related papers
- Beyond Grounding: Extracting Fine-Grained Event Hierarchies across ModalitiesHammad A. Ayyubi, Christopher Thomas, Lovish Chum, Rahul Lokesh et al.AAAI 2024 · 2 citations
- Learning Constraints and Descriptive Segmentation for Subevent DetectionHaoyu Wang, Hongming Zhang, Muhao Chen, Dan RothEMNLP 2021 · 15 citations
- Cross-document Event Coreference Search: Task, Dataset and ModelingAlon Eirew, Avi Caciularu, Ido DaganEMNLP 2022 · 3 citations
- Joint Constrained Learning for Event-Event Relation ExtractionHaoyu Wang, Muhao Chen, Hongming Zhang, Dan RothEMNLP 2020 · 105 citations
- Weakly-Supervised Temporal Article GroundingLong Chen, Yulei Niu, Brian Chen, Xudong Lin et al.EMNLP 2022 · 11 citations
