English

LingMess: Linguistically Informed Multi Expert Scorers for Coreference Resolution

Computation and Language 2023-02-13 v3

Abstract

While coreference resolution typically involves various linguistic challenges, recent models are based on a single pairwise scorer for all types of pairs. We present LingMess, a new coreference model that defines different categories of coreference cases and optimize multiple pairwise scorers, where each scorer learns a specific set of linguistic challenges. Our model substantially improves pairwise scores for most categories and outperforms cluster-level performance on Ontonotes and 5 additional datasets. Our model is available in https://github.com/shon-otmazgin/lingmess-coref

Keywords

Cite

@article{arxiv.2205.12644,
  title  = {LingMess: Linguistically Informed Multi Expert Scorers for Coreference Resolution},
  author = {Shon Otmazgin and Arie Cattan and Yoav Goldberg},
  journal= {arXiv preprint arXiv:2205.12644},
  year   = {2023}
}

Comments

EACL 2023

R2 v1 2026-06-24T11:28:09.928Z