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3 months ago
LingMess: Linguistically Informed Multi Expert Scorers for Coreference Resolution
Shon Otmazgin Arie Cattan Yoav Goldberg

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
shon-otmazgin/fastcoref
pytorch
Benchmarks
| Benchmark | Methodology | Metrics |
|---|---|---|
| coreference-resolution-on-ontonotes | LingMess | F1: 81.4 |
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