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Named Entity Recognition (NER) task has become essential to improve the performance of many NLP tasks. Its aim is to endeavor a solution to boost accurately the identification of extracted named entities. This paper presents a novel solution for Arabic Named Entity Recognition (ANER) problem. The solution is an integration approach between two machine(More)
Arabic is a language of rich and complex morphology. The nature and peculiarity of Arabic make its morphological and phonological rules confusing for second language learners (SLLs). The conjugation of Arabic verbs is central to the formulation of an Arabic sentence because of its richness of form and meaning. In this paper, we address issues related to the(More)
This paper addresses issues related to generating feedback messages to errors related to Arabic verbs made by second language learners (SLLs). The proposed approach allows for individualization. When a SLL of Arabic writes a wrong verb, it performs analysis of the input and distinguishes between different lexical error types. The proposed system issues the(More)
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