A Survey on Arabic Named Entity Recognition: Past, Recent Advances, and Future Trends

As more and Arabic texts emerged on the Internet, extracting important information from these is especially useful. a fundamental technology, Named entity recognition (NER) serves as core component in extraction while also playing critical role many other Natural Language Processing (NLP) systems, such question answering knowledge graph building. In this paper, we provide comprehensive review of development NER, recent advances deep learning pre-trained language model. Specifically, first introduce background including characteristics existing resources for NER. Then, systematically NER methods. Traditional systems focus feature engineering designing domain-specific rules. years, methods achieve significant progress by representing via continuous vector representations. With growth model, yields better performance. Finally, conclude method gap between languages, which helps outline future directions