BERT for Coreference Resolution: Baselines and Analysis
Computation and Language
2019-12-24 v4
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.
Keywords
Cite
@article{arxiv.1908.09091,
title = {BERT for Coreference Resolution: Baselines and Analysis},
author = {Mandar Joshi and Omer Levy and Daniel S. Weld and Luke Zettlemoyer},
journal= {arXiv preprint arXiv:1908.09091},
year = {2019}
}
Comments
Fix test set numbers for e2e-coref on GAP