mlsanityData to 7 Oct 2026

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

arXiv 2302.03512 ↗First posted 7 Feb 2023cs.CLcited by 8

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Abstract (arXiv)

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

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 62 of its 150 references that are in the map. First posted on arXiv 7 Feb 2023.

Builds on

62 of 150 references.

References · 62

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 2; 2024: 3; 2025: 1; 2026: 2.

8 papers.

  1. 2023TREA: Tree-Structure Reasoning Schema for Conversational Recommendationcited by 15
  2. 2023AraMUS: Pushing the Limits of Data and Model Scale for Arabic Natural Language Processingcited by 7
  3. 2024A Literature Review of Literature Reviews in Pattern Analysis and Machine Intelligencecited by 3
  4. 2024Improving Pseudo Labels with Global-Local Denoising Framework for Cross-lingual Named Entity Recognitioncited by 2
  5. 2024RexUniNLU: Recursive Method with Explicit Schema Instructor for Universal NLUcited by 0
  6. 2025ESNERA: Empirical and semantic named entity alignment for named entity dataset mergingcited by 0
  7. 2026Unsupervised Multidomain Approaches to Named Entity Recognition with Small Datasetscited by 0
  8. 2026A Comprehensive Analysis of Arabic Natural Language Processing Research: Trends, Topic Evolution, and Research Gaps -- A Bibliometric and Topic-Based Studycited by 0