Coreference Resolution for Vietnamese Narrative Texts
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866908340243660800 |
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| author | Tran, Hieu-Dai Nguyen, Duc-Vu Nguyen, Ngan Luu-Thuy |
| author_facet | Tran, Hieu-Dai Nguyen, Duc-Vu Nguyen, Ngan Luu-Thuy |
| contents | Coreference resolution is a vital task in natural language processing (NLP) that involves identifying and linking different expressions in a text that refer to the same entity. This task is particularly challenging for Vietnamese, a low-resource language with limited annotated datasets. To address these challenges, we developed a comprehensive annotated dataset using narrative texts from VnExpress, a widely-read Vietnamese online news platform. We established detailed guidelines for annotating entities, focusing on ensuring consistency and accuracy. Additionally, we evaluated the performance of large language models (LLMs), specifically GPT-3.5-Turbo and GPT-4, on this dataset. Our results demonstrate that GPT-4 significantly outperforms GPT-3.5-Turbo in terms of both accuracy and response consistency, making it a more reliable tool for coreference resolution in Vietnamese. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_19606 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Coreference Resolution for Vietnamese Narrative Texts Tran, Hieu-Dai Nguyen, Duc-Vu Nguyen, Ngan Luu-Thuy Computation and Language Coreference resolution is a vital task in natural language processing (NLP) that involves identifying and linking different expressions in a text that refer to the same entity. This task is particularly challenging for Vietnamese, a low-resource language with limited annotated datasets. To address these challenges, we developed a comprehensive annotated dataset using narrative texts from VnExpress, a widely-read Vietnamese online news platform. We established detailed guidelines for annotating entities, focusing on ensuring consistency and accuracy. Additionally, we evaluated the performance of large language models (LLMs), specifically GPT-3.5-Turbo and GPT-4, on this dataset. Our results demonstrate that GPT-4 significantly outperforms GPT-3.5-Turbo in terms of both accuracy and response consistency, making it a more reliable tool for coreference resolution in Vietnamese. |
| title | Coreference Resolution for Vietnamese Narrative Texts |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2504.19606 |