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BERT for Coreference Resolution: Baselines and Analysis

About

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.

Mandar Joshi, Omer Levy, Daniel S. Weld, Luke Zettlemoyer• 2019

Related benchmarks

TaskDatasetResultRank
Coreference ResolutionCoNLL English 2012 (test)
MUC F1 Score83.5
114
Coreference ResolutionGAP (test)
Overall F185
53
Coreference ResolutionEnglish OntoNotes 5.0 (test)--
18
Coreference ResolutionCoNLL 2012
Average F176.9
17
Coreference ResolutionOntoNotes 5.0 (dev)
CoNLL F180.1
13
Coreference ResolutionSTM corpus five-fold cross validation (test)
MUC Precision61.6
6
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Other info

Code

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