MirathQA:用于评估汉巴利伊斯兰遗产推理任务的大型语言模型的数据集
Ameera Almasoud1, Sharefah Al-Ghamdi1, Reem Alqifari1
1Department of Information Technology, College of Information and Computer Sciences, King Saud University, Riyadh, Saudi Arabia.
Data in brief
|March 4, 2026
概括
MirathQA是一个新的数据集,用于评估伊斯兰遗产法上的阿拉伯大语言模型 (LLM). 它包含了来自真实案例的1394个问题,有助于AI开发复杂的法律推理.
科学领域:
- 计算语言学 计算语言学
- 人工智能的人工智能
- 伊斯兰法律学 伊斯兰法律学
背景情况:
- 阿拉伯大语言模型 (LLM) 在精确的算术和多步推理方面面临挑战,特别是在像伊斯兰继承法 ('ilm al-farā'iḍ/علم الفرائض) 这样的专业领域.
- 现有的阿拉伯语数据集不足以系统地评估LLM在复杂的法律规则应用,继承人识别和计算调整中的表现,例如比例缩减 ('awl/عول) 和返回 (radd/رد).
研究的目的:
- 介绍MirathQA,这是一个新的,全面的数据集,旨在对伊斯兰继承法中阿拉伯LLM能力进行基准测试,特别关注汉巴利法学派 (المذهب الحنبلي).
- 在伊斯兰法律背景下,为推进AI应用在法律推理,教育和跨学科研究方面提供资源.
主要方法:
- 策划了来自阿拉伯材料的242个现实伊斯兰遗产案例的1394个问题的数据集.
- 每个案例都包括文本描述,经过验证的解决方案,继承人份额,以及被阻止的继承人 (ḥijb/حجب) 和其他复杂性的注释.
- 开发了额外的多选项和真假问题,以评估特定的推理能力,并将数据结构化为培训 (70%),验证 (15%) 和测试 (15%) 在案例层面的分割.
主要成果:
- MirathQA数据集提供了一个强大的基准,用于评估阿拉伯语LLM在需要精确法律推理,顺序规则应用和处理特定继承场景的任务上.
- 数据集包括继承人,被阻止的继承人和计算的详细注释,方便对伊斯兰继承法的LLM绩效进行深入分析.
- 数据以CSV和Excel格式提供,确保可用于各种研究和开发需求的可访问性.
结论:
- MirathQA解决了对结构化阿拉伯语数据集的关键需求,以评估伊斯兰遗产法AI,促进系统的评估和开发.
- 这个资源对于在特定领域的法律应用中推进阿拉伯语LLM推理能力和支持教育倡议是有价值的.
- 该数据集支持人工智能,法律和计算语言学的交叉点上的跨学科研究.
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