相关实验视频
库尔德ABSA:库尔德语基于方面情绪分析数据集策划使用少数射击学习.
Rania Azad M San Ahmed1, Soran Ab Saeed1
1Technical College of Informatics, Sulaimani Polytechnic University, Iraq.
Data in brief
|September 24, 2025
概括
本研究介绍了库尔德语 (索拉尼方言) 的第一个基于方面情感分析 (ABSA) 数据集,使得NLP研究能够用于低资源语言. 该数据集有助于机器学习和跨语言模型开发.
科学领域:
- 自然语言处理 (NLP) 是一种自然语言处理.
- 计算语言学 计算语言学
- 情绪分析 情绪分析
背景情况:
- 基于方面的情绪分析 (ABSA) 通过识别对特定方面的情绪来增强传统的情绪分析.
- 在ABSA的研究是广泛的,但缺乏资源的低资源语言,如库尔德语.
- 库尔德语 (索拉尼方言) 在ABSA研究中仍未得到充分探索.
研究的目的:
- 介绍库尔德语索拉尼方言的第一个公开可用的ABSA数据集.
- 为解决NLP资源的关键差距,为低资源语言.
- 为库尔德语促进ABSA的研究和开发.
主要方法:
- 创建一个数据集,包含库尔德语 (索拉尼方言) 的餐厅评论中的4000多个四倍 ABSA 条目.
- 使用基于提示的几次学习模型,自动注释方面-意见-类别-情感四倍数.
- 数据集注释以手动验证的支持集为指导,由库尔德语母语使用者证实.
主要成果:
- 开发库尔德语 (索拉尼方言) 的第一个全面的ABSA数据集.
- 数据集包含了>4000个四倍 ABSA 条目在餐厅评论领域.
- 数据集使用波斯阿拉伯文字进行注释.
结论:
- 这种资源显著推进了NLP研究的低资源语言,特别是库尔德语.
- 该数据集适用于培训,微调和对机器学习和深度学习模型进行基准测试.
- 它支持跨语言模型适应和未来的库尔德语ABSA研究.
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