Since training and test parts of standard datasets for Arabic NER are drawn from the same genre in relatively close temporal proximity, a named entity recognizer that simply memorizes named entities in the training set generally performs well on such test sets.
we believe that this problem can be overcome by introducing new training data that include tweets (or other social text) and performing domain adaptation.