Athar at QIAS2025: LLM-based question answering systems for Islamic inheritance and classical Islamic knowledge - Noureldien, Yossra; Suliman, Hassan; Attallah, Farah; Mohamed, Abdelrazig; Abdalla, Sara Siddig Ali (Association for Computational Linguistics (ACL), 2025)
The intersection of Arabic linguistic complexity and specialized reasoning presents a key challenge for Islamic question-answering systems, particularly in the under-addressed area of inheritance law. This paper presents our methodology for the QIAS2025 shared task, assessing LLM capabilities in Islamic knowledge through two subtasks: Inheritance Reasoning (ʿilm al-mawārīth) and General Islamic Assessment. A zero-shot, prompt-based approach with DeepSeek-R1 (deepseek-reasoner) addresses the former, while a three-stage RAG pipeline handles the latter. Our approaches achieved competitive results, with an accuracy of 0.704 for inheritance reasoning (10th place/15 teams) and 0.9272 for general Islamic assessment (2nd place/10 teams), demonstrating the efficacy of tailored model strategies for religious QA. These insights pave the way for more culturally and linguistically adaptive AI systems in Islamic scholarly applications.