인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Arabic Natural Language Processing (NLP) is still faced with the complexity of the language's morphology and the limited availability of quality annotated resources. In this paper, we introduce an open-domain dataset of 5,009 Modern Standard Arabic (MSA) questions labeled according to AAFAQ framework that has11 linguistic and cognitive aspects, e.g., Question Particle, Question Particle Type, Intent, Answer Type, Cognitive Level, and Temporal Context. Based on the AAFAQ Framework (Arabic Analytical Framework for Advanced Questions), the dataset is designed to support semantic and cognitive understanding for Arabic Question Classification and related tasks. The dataset's effectiveness was validated by fine-tuning state-of-the-art models. AraBERT achieved 100% accuracy on Question Particle Type classification and 94.95% on Intent classification. Integration within a generative question-answering system with Alpaca + Gemma-9B Unsloth improved evaluation metrics, including BLEU (+37.6%), ROUGE-1 (+132%), and BERTScore (+17.3%), validating the dataset's value in both classification and generation tasks. Despite its broad coverage, the dataset includes underrepresented categories, e.g., Sociology and Volunteering, to be considered in future extensions. AAFAQ is a foundation benchmark for the advancement of Arabic question comprehension, with prospective applications in education, cognitive computing, and multilingual AI system creation.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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