mlsanityData to 14 Oct 2026

Can we Fix the Scope for Coreference? Problems and Solutions for Benchmarks beyond OntoNotes

arXiv 2112.09742 ↗First posted 17 Dec 2021cs.CLcited by 4

Not on the map. Why?

Abstract (arXiv)

Current work on automatic coreference resolution has focused on the OntoNotes benchmark dataset, due to both its size and consistency. However many aspects of the OntoNotes annotation scheme are not well understood by NLP practitioners, including the treatment of generic NPs, noun modifiers, indefinite anaphora, predication and more. These often lead to counterintuitive claims, results and system behaviors. This opinion piece aims to highlight some of the problems with the OntoNotes rendition of coreference, and to propose a way forward relying on three principles: 1. a focus on semantics, not morphosyntax; 2. cross-linguistic generalizability; and 3. a separation of identity and scope, which can resolve old problems involving temporal and modal domain consistency.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 9 of its 64 references that are in the map. First posted on arXiv 17 Dec 2021.

Builds on

9 of 64 references.

References · 9

  1. 2018AllenNLP: A Deep Semantic Natural Language Processing Platformcited by 347
  2. 2017End-to-end Neural Coreference Resolutioncited by 241
  3. 2019BERT for Coreference Resolution: Baselines and Analysiscited by 125
  4. 2019Coreference Resolution as Query-based Span Predictioncited by 91
  5. 2016Deep Reinforcement Learning for Mention-Ranking Coreference Modelscited by 63
  6. 2018Neural Coreference Resolution with Deep Biaffine Attention by Joint Mention Detection and Mention Clusteringcited by 16
  7. 2021WikiGUM: Exhaustive Entity Linking for Wikification in 12 Genrescited by 9
  8. 2019AD3: Attentive Deep Document Datercited by 6
  9. 2021Anatomy of OntoGUM--Adapting GUM to the OntoNotes Scheme to Evaluate Robustness of SOTA Coreference Algorithmscited by 3

Built on by

Cited by year

Citing papers per year: 2022: 1; 2023: 1; 2024: 1; 2025: 1.

4 papers.