Towards Comprehensive Argument Analysis in Education: Dataset, Tasks, and Method Article Swipe
YOU?
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· 2025
· Open Access
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· DOI: https://doi.org/10.48550/arxiv.2505.12028
Argument mining has garnered increasing attention over the years, with the recent advancement of Large Language Models (LLMs) further propelling this trend. However, current argument relations remain relatively simplistic and foundational, struggling to capture the full scope of argument information, particularly when it comes to representing complex argument structures in real-world scenarios. To address this limitation, we propose 14 fine-grained relation types from both vertical and horizontal dimensions, thereby capturing the intricate interplay between argument components for a thorough understanding of argument structure. On this basis, we conducted extensive experiments on three tasks: argument component detection, relation prediction, and automated essay grading. Additionally, we explored the impact of writing quality on argument component detection and relation prediction, as well as the connections between discourse relations and argumentative features. The findings highlight the importance of fine-grained argumentative annotations for argumentative writing quality assessment and encourage multi-dimensional argument analysis.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2505.12028
- https://arxiv.org/pdf/2505.12028
- OA Status
- green
- OpenAlex ID
- https://openalex.org/W4417300294
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4417300294Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2505.12028Digital Object Identifier
- Title
-
Towards Comprehensive Argument Analysis in Education: Dataset, Tasks, and MethodWork title
- Type
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preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-05-17Full publication date if available
- Authors
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Yupei Ren, Xinyi Zhou, Ning Zhang, Shangqing Zhao, Mingjun Lan, Xiaopeng BaiList of authors in order
- Landing page
-
https://arxiv.org/abs/2505.12028Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2505.12028Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2505.12028Direct OA link when available
- Cited by
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0Total citation count in OpenAlex
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