A Benchmark Arabic Dataset for Arabic Question Classification using AAFAQ Framework.

ABSTRACT: 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 T

SUBMITTER: Abdelaziz ME 

PROVIDER: S-EPMC12361461 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature