Papers › BERT for Coreference Resolution: Baselines and Analysis
BERT for Coreference Resolution: Baselines and Analysis
Mandar Joshi, Omer Levy, Daniel S. Weld, Luke Zettlemoyer
We apply BERT to coreference resolution, achieving strong improvements on the OntoNotes (+3.9 F1) and GAP (+11.5 F1) benchmarks. A qualitative analysis of model predictions indicates that, compared to ELMo and BERT-base, BERT-large is particularly better at distinguishing between related but distinct entities (e.g., President and CEO). However, there is still room for improvement in modeling document-level context, conversations, and mention paraphrasing. Our code and models are publicly available.
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Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Coreference Resolution | CoNLL 2012 | c2f-coref + BERT-large | Avg F1 | 76.9 | #11 of 18 | Archive leaderboard | report |
| Coreference Resolution | OntoNotes | BERT-large | F1 | 76.9 | #15 of 26 | Archive leaderboard | report |
| Coreference Resolution | OntoNotes | BERT-base | F1 | 73.9 | #17 of 26 | Archive leaderboard | report |
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Methods
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