NovelCR: A Large-Scale Bilingual Dataset Tailored for Long-Span Coreference Resolution
Coreference resolution (CR) links pronouns and noun phrases to their referent entities, serving as a key step in deep text understanding.Presently available CR datasets are either small in scale or restrict coreference resolution to a limited text span.In this paper, we present NovelCR, a large-scale bilingual benchmark designed for long-span coreference resolution.NovelCR features extensive annotations, including 148k mentions in NovelCR-en and 311k mentions in NovelCR-zh.Moreover, the dataset is notably rich in long-span coreference pairs, with 85% of pairs in NovelCR-en and 83% in NovelCR-zh spanning across three or more sentences.Experiments on NovelCR reveal a large gap between state-of-the-art baselines and human performance, highlighting that NovelCR remains an open issue.The NovelCR dataset is publicly available at:
Authors
- MeiHan Tong
- Shuai Wang (ORCID: https://orcid.org/0000-0002-5073-3371)
Publication Details
- Published
- 2025-01-01
- DOI
- https://doi.org/10.18653/v1/2025.findings-acl.268
- Primary Topic
- Speech Recognition and Synthesis
- Type
- article
- Field-Weighted Citation Impact
- 0.00