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3 months ago

LingMess: Linguistically Informed Multi Expert Scorers for Coreference Resolution

Shon Otmazgin Arie Cattan Yoav Goldberg

LingMess: Linguistically Informed Multi Expert Scorers for Coreference Resolution

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

Code Repositories

shon-otmazgin/lingmess-coref
Official
pytorch
Mentioned in GitHub

Benchmarks

BenchmarkMethodologyMetrics
coreference-resolution-on-ontonotesLingMess
F1: 81.4

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LingMess: Linguistically Informed Multi Expert Scorers for Coreference Resolution | Papers | HyperAI