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As organizations seek to automatically extract meaning and structure from vast amounts of Arabic text, one of the most fundamental and valuable NLP technologies is Named Entity Recognition Arabic. NER is the computational task of identifying and classifying key information units, known as entities, within unstructured text into predefined categories such as person names, organizations, locations, dates, and monetary values. However, performing Named entity recognition Arabic presents a distinct set of challenges not encountered in languages like English.

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