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:

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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
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article

NovelCR: A Large-Scale Bilingual Dataset Tailored for Long-Span Coreference Resolution

MeiHan Tong, Shuai Wang
Speech Recognition and Synthesis
article

NovelCR: A Large-Scale Bilingual Dataset Tailored for Long-Span Coreference Resolution

MeiHan Tong, Shuai Wang
article en

Abstract

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:

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Openalex Percentile: Top 90%
Speech Recognition and Synthesis
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