Papers › Entity, Relation, and Event Extraction with Contextualized Span Representations
Entity, Relation, and Event Extraction with Contextualized Span Representations
David Wadden, Ulme Wennberg, Yi Luan, Hannaneh Hajishirzi
We examine the capabilities of a unified, multi-task framework for three information extraction tasks: named entity recognition, relation extraction, and event extraction. Our framework (called DyGIE++) accomplishes all tasks by enumerating, refining, and scoring text spans designed to capture local (within-sentence) and global (cross-sentence) context. Our framework achieves state-of-the-art results across all tasks, on four datasets from a variety of domains. We perform experiments comparing different techniques to construct span representations. Contextualized embeddings like BERT perform well at capturing relationships among entities in the same or adjacent sentences, while dynamic span graph updates model long-range cross-sentence relationships. For instance, propagating span representations via predicted coreference links can enable the model to disambiguate challenging entity mentions. Our code is publicly available at https://github.com/dwadden/dygiepp and can be easily adapted for new tasks or datasets.
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Tasks
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Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Joint Entity and Relation Extraction | SciERC | DyGIE++ | Cross Sentence | Yes | #6 of 11 | Archive leaderboard | report |
| Joint Entity and Relation Extraction | SciERC | DyGIE++ | Entity F1 | 67.50 | #6 of 11 | Archive leaderboard | report |
| Joint Entity and Relation Extraction | SciERC | DyGIE++ | Relation F1 | 48.40 | #6 of 11 | Archive leaderboard | report |
| Relation Extraction | ACE 2005 | DYGIE++ | Cross Sentence | Yes | #9 of 30 | Archive leaderboard | report |
| Relation Extraction | ACE 2005 | DYGIE++ | NER Micro F1 | 88.6 | #9 of 30 | Archive leaderboard | report |
| Relation Extraction | ACE 2005 | DYGIE++ | RE Micro F1 | 63.4 | #9 of 30 | Archive leaderboard | report |
| Relation Extraction | ACE 2005 | DYGIE++ | Sentence Encoder | BERT base | #9 of 30 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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