Papers › Paraphrasing vs Coreferring: Two Sides of the Same Coin

Paraphrasing vs Coreferring: Two Sides of the Same Coin

30 Apr 2020Findings of the Association for Computational Linguistics 2020arXiv:2004.14979archive 2025-07-28

Yehudit Meged, Avi Caciularu, Vered Shwartz, Ido Dagan

We study the potential synergy between two different NLP tasks, both confronting predicate lexical variability: identifying predicate paraphrases, and event coreference resolution. First, we used annotations from an event coreference dataset as distant supervision to re-score heuristically-extracted predicate paraphrases. The new scoring gained more than 18 points in average precision upon their ranking by the original scoring method. Then, we used the same re-ranking features as additional inputs to a state-of-the-art event coreference resolution model, which yielded modest but consistent improvements to the model's performance. The results suggest a promising direction to leverage data and models for each of the tasks to the benefit of the other.

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yehudit96/coreferrability officialmentioned in papermentioned on GitHub report
yehudit96/event_entity_coref_ecb_plus officialmentioned in papermentioned on GitHubpytorch report

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Coreference ResolutionEvent Coreference ResolutionEvent Cross-Document Coreference ResolutionRe-RankingVocal Bursts Valence Predictioncoreference-resolution

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