诺伊尔贝蒂克 (NOIRBETTIK):基于阅读理解的孟加拉语多选题答案数据集
Tanjim Taharat Aurpa1, Md Shahriar Hossain Apu2, Farzana Akter2
1Department of Data Science and Engineering, Bangabandhu Sheikh Mujibur Rahman Digital, University, Bangladesh.
Data in brief
|March 19, 2025
概括
创建了一个新的孟加拉语数据集,NOIRBETTIK,用于自动阅读理解和多选择题 (MCQ) 答案. 本资源支持孟加拉语学习者教育技术的进步.
科学领域:
- 自然语言处理自然语言处理.
- 教育技术的教育技术
- 计算语言学 计算语言学
背景情况:
- 随着COVID-19大流行,在线教育加速发展,自动化学习和评估工具的需求增加.
- 多选题 (MCQ) 对于评估数字学习环境中的理解能力至关重要.
- 现有的孟加拉语资源用于基于上下文的NLP任务,特别是阅读理解,很少.
研究的目的:
- 介绍NOIRBETTIK,一种新的,人为的数据集,用于基于阅读理解的MCQ在孟加拉语中回答.
- 解决NLP和教育应用的高质量的孟加拉语数据集的关键缺口.
- 促进开发先进的自动化系统,用于孟加拉语的学习和评估.
主要方法:
- 数据集的创建包括采购正宗的孟加拉文材料 (书籍,文章,传记).
- 段落与多选项问题配对,每个问题都有四个替代方案.
- 数据集的创建和注释过程被仔细记录下来,并与现有资源进行了比较.
主要成果:
- 诺伊尔贝蒂克数据集包括更长的段落和与情境相关的MCQ.
- 这是一个独特的,人为生成的资源,专门为孟加拉语阅读理解任务设计.
- 数据集的结构和创建方法是详细的,确保透明度和可用性.
结论:
- NOIRBETTIK的发布为孟加拉语NLP研究提供了宝贵的资源.
- 这一数据集可以显著提高孟加拉语学生的阅读理解系统.
- 诺伊尔贝蒂克准备为孟加拉语社区推动教育技术的创新.
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