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Tokenization is a necessary and non-trivial step in natural language processing. In the case of Arabic, where a single word can comprise up to four independent tokens, morphological knowledge needs to be incorporated into the tokenizer. In this paper we describe a rule-based tokenizer that handles tokenization as a full-rounded process with a preprocessing stage (white space normalizer), and a post-processing stage (token filter). We also show how it handles multiword expressions, and how ambiguity is resolved.
Mohammed Attia (Mon,) studied this question.
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