arXiv cs.CL· Jaeyoung Lee, Geonyeong Son, Misuk Kim·· 2 天前AI 评分16
ESG-Kor：面向 ESG 信息抽取的韩语数据集及实用案例
ESG-Kor: A Korean Dataset for ESG-related Information Extraction and Practical Use Cases
AI 导读
研究者构建了韩语数据集 ESG-Kor，从韩国企业可持续发展报告中抽取环境、社会与治理（ESG）信息，共含 118,946 句，并按 ESG 评估机构的客观规则人工标注。该数据集用多个韩语预训练语言模型验证分类性能，取得显著效果，并进一步将 ESG 分类模型扩展至中小企业文档，展示基于 ESG 关键议题的信息抽取与深度分析等实用场景。
正文 · 原文
Abstract:With the expansion of pre-trained language model usage in recent years, the importance of datasets for performing tasks in specialized domains has significantly increased. Therefore, we have built a Korean dataset called ESG-Kor to automatically extract Environmental, Social, and Governance (ESG) information, which has recently gained importance. ESG-Kor is a dataset consisting of a total of 118,946 sentences that extracted information on each ESG component from Korean companies' sustainability reports and manually labeled it according to objective rules provided by ESG evaluation agencies. To verify the effectiveness and applicability of the ESG-Kor dataset, classification performance was confirmed using several Korean pre-trained language models, and significant performance was obtained. Additionally, by extending the ESG classification model to documents of small and medium enterprises and extracting information based on ESG key issues and in-depth analysis, we demonstrated potential and practical use cases in the ESG field.
| Comments: | Published in Findings of EMNLP 2024 |
| Subjects: | Computation and Language (cs.CL); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2610.21368 [cs.CL] |
| (or arXiv:2610.21368v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2610.21368 arXiv-issued DOI via DataCite (pending registration) |
|
| Journal reference: | Findings of the Association for Computational Linguistics: EMNLP 2024, pp. 6627-6643, 2024 |
Submission history
From: Jaeyoung Lee [view email]
[v1]
Thu, 15 Oct 2026 06:48:21 UTC (1,565 KB)
来源：arXiv cs.CL · arxiv.org