Papers by MeiHan Tong
NovelCR: A Large-Scale Bilingual Dataset Tailored for Long-Span Coreference Resolution (2025.findings-acl)
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| Challenge: | Existing coreference resolution datasets are either small in scale or restrict coreference to a limited text span. |
| Approach: | They present a large-scale bilingual benchmark for long-span coreference resolution . they find that NovelCR is notably rich in long-spanning coreference pairs . |
| Outcome: | The proposed benchmark is rich in long-span coreference pairs and notably low baselines. |
DocEE: A Large-Scale and Fine-grained Benchmark for Document-level Event Extraction (2022.naacl-main)
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| Challenge: | Existing datasets focus on sentence-level event extraction, but document-level EE is limited due to the lack of large-scale and practical training and evaluation datasets. |
| Approach: | They propose a document-level event extraction dataset with 27,000+ events and 180,000+ arguments. |
| Outcome: | The proposed dataset includes 27,000+ events, 180,000+ arguments and large-scale manual annotations, fine-grained argument types and application-oriented settings. |
DocEE-zh: A Fine-grained Benchmark for Chinese Document-level Event Extraction (2024.findings-emnlp)
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| Challenge: | Chinese document-level event extraction is still largely unexplored. |
| Approach: | They propose a Chinese document-level event extraction dataset with over 36,000 events and 210,000 arguments. |
| Outcome: | The proposed dataset includes over 36,000 events and more than 210,000 arguments . it is an extension of the DocEE dataset, utilizing the same event schema and annotated by human experts. |