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In this paper, we propose an Arabic Question-Answering (Q-A) system called QASAL «Question -Answering system for Arabic Language». QASAL accepts as an input a natural language question written in Modern Standard Arabic (MSA) and generates as an output the most efficient and appropriate answer. The proposed system is composed of three modules:(More)
This paper presents a cascade of morpho-syntactic tools to deal with Arabic natural language processing. It begins with the description of a large coverage formalization of the Arabic lexicon. The built electronic dictionary, named "El-DicAr", which stands for “Electronic Dictionary for Arabic”, links inflectional, morphological, and syntactic-semantic(More)
Since 2006 we have undertaken to describe the differences between 17th century English and contemporary English thanks to NLP software. Studying a corpus spanning the whole century (tales of English travellers in the Ottoman Empire in the 17th century, Mary Astell's essay A Serious Proposal to the Ladies and other literary texts) has enabled us to highlight(More)
This works deals with Arabic factoid Question Answering systems (QA). Commonly, the task of QA is divided into three phases: question analysis, answer pattern generation, and answer extraction. Each phase plays a crucial role in overall performance. In this paper, we focus on the two first phases: Question Analysis and Answer Pattern Generation. We used the(More)
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