On Event Individuation for Document-Level Information Extraction
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Abstract (arXiv)
As information extraction (IE) systems have grown more adept at processing whole documents, the classic task of template filling has seen renewed interest as benchmark for document-level IE. In this position paper, we call into question the suitability of template filling for this purpose. We argue that the task demands definitive answers to thorny questions of event individuation -- the problem of distinguishing distinct events -- about which even human experts disagree. Through an annotation study and error analysis, we show that this raises concerns about the usefulness of template filling metrics, the quality of datasets for the task, and the ability of models to learn it. Finally, we consider possible solutions.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 17 of its 55 references that are in the map. First posted on arXiv 19 Dec 2022.
Builds on
17 of 55 references.
References · 17
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5 more
- 2022Automatic Error Analysis for Document-level Information Extractioncited by 10
- 2018Neural-Davidsonian Semantic Proto-role Labelingcited by 9
- 2021Decomposing and Recomposing Event Structurecited by 5
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Built on by
Citing papers per year: 2023: 1; 2024: 1.
2 papers.
- 2023FAMuS: Frames Across Multiple Sourcescited by 2
- 2024Are Triggers Needed for Document-Level Event Extraction?cited by 1
- 2024Are Triggers Needed for Document-Level Event Extraction?13 Nov 2024
- 2023FAMuS: Frames Across Multiple Sources9 Nov 2023