BERT for Coreference Resolution: Baselines and Analysis
August 24, 2019 ยท Declared Dead ยท ๐ Conference on Empirical Methods in Natural Language Processing
"No code URL or promise found in abstract"
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Authors
Mandar Joshi, Omer Levy, Daniel S. Weld, Luke Zettlemoyer
arXiv ID
1908.09091
Category
cs.CL: Computation & Language
Citations
341
Venue
Conference on Empirical Methods in Natural Language Processing
Last Checked
3 months ago
Abstract
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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