LingMess: Linguistically Informed Multi Expert Scorers for Coreference Resolution
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
Benchmarks
| Benchmark | Methodology | Metrics |
|---|---|---|
| coreference-resolution-on-ontonotes | LingMess | F1: 81.4 |
Build AI with AI
From idea to launch — accelerate your AI development with free AI co-coding, out-of-the-box environment and best price of GPUs.