Data to 14 Oct 2026

A Survey on Recent Advances in Named Entity Recognition from Deep Learning models

arXiv 1910.11470 ↗First posted 25 Oct 2019cs.CL cs.LGcited by 117

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Abstract (arXiv)

Named Entity Recognition (NER) is a key component in NLP systems for question answering, information retrieval, relation extraction, etc. NER systems have been studied and developed widely for decades, but accurate systems using deep neural networks (NN) have only been introduced in the last few years. We present a comprehensive survey of deep neural network architectures for NER, and contrast them with previous approaches to NER based on feature engineering and other supervised or semi-supervised learning algorithms. Our results highlight the improvements achieved by neural networks, and show how incorporating some of the lessons learned from past work on feature-based NER systems can yield further improvements.

Key facts. Cited by 117 papers in the map (data through 14 Oct 2026). First posted on arXiv 25 Oct 2019.

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Citing papers per year: 2021: 25; 2022: 31; 2023: 30; 2024: 16; 2025: 12; 2026: 3.

117 papers.

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2021MasakhaNER: Named Entity Recognition for African Languagescited by 155
2023Similarity of Neural Network Models: A Survey of Functional and Representational Measurescited by 131
2023LLMs Accelerate Annotation for Medical Information Extractioncited by 77
2021Named Entity Recognition and Classification on Historical Documents: A Surveycited by 47
2023A Comprehensive Evaluation of Large Language Models on Benchmark Biomedical Text Processing Taskscited by 36
2023Open, Closed, or Small Language Models for Text Classification?cited by 34
2023Zero-shot cross-lingual transfer language selection using linguistic similaritycited by 28
2024ADELIE: Aligning Large Language Models on Information Extractioncited by 24
2022A Survey of Adversarial Defences and Robustness in NLPcited by 23
2021DeepSTL -- From English Requirements to Signal Temporal Logiccited by 22
2023Evaluation of ChatGPT on Biomedical Tasks: A Zero-Shot Comparison with Fine-Tuned Generative Transformerscited by 22
2021Learning from Miscellaneous Other-Class Words for Few-shot Named Entity Recognitioncited by 21

38 more

2021NER-BERT: A Pre-trained Model for Low-Resource Entity Taggingcited by 21
2022L3Cube-MahaNER: A Marathi Named Entity Recognition Dataset and BERT modelscited by 21
2022ATCO2 corpus: A Large-Scale Dataset for Research on Automatic Speech Recognition and Natural Language Understanding of Air Traffic Control Communicationscited by 19
2022CROP: Zero-shot Cross-lingual Named Entity Recognition with Multilingual Labeled Sequence Translationcited by 17
2021Spark NLP: Natural Language Understanding at Scalecited by 16
2024IL-TUR: Benchmark for Indian Legal Text Understanding and Reasoningcited by 16
2021CHOLAN: A Modular Approach for Neural Entity Linking on Wikipedia and Wikidatacited by 14
2023Data Augmentations for Improved (Large) Language Model Generalizationcited by 14
2021Crowdsourcing Learning as Domain Adaptation: A Case Study on Named Entity Recognitioncited by 13
2021BERTraffic: BERT-based Joint Speaker Role and Speaker Change Detection for Air Traffic Control Communicationscited by 13
2022E-NER -- An Annotated Named Entity Recognition Corpus of Legal Textcited by 13
2021On the Use of External Data for Spoken Named Entity Recognitioncited by 12
2021Probing Pre-trained Auto-regressive Language Models for Named Entity Typing and Recognitioncited by 10
2024Which Demographics do LLMs Default to During Annotation?cited by 10
2025BYOKG-RAG: Multi-Strategy Graph Retrieval for Knowledge Graph Question Answeringcited by 10
2023In the Name of Fairness: Assessing the Bias in Clinical Record De-identificationcited by 9
2021Causal Effect Variational Autoencoder with Uniform Treatmentcited by 8
2022Towards a Broad Coverage Named Entity Resource: A Data-Efficient Approach for Many Diverse Languagescited by 8
2023A Survey on Arabic Named Entity Recognition: Past, Recent Advances, and Future Trendscited by 8
2025A Survey on Retrieval And Structuring Augmented Generation with Large Language Modelscited by 8
2021Reddit Entity Linking Datasetcited by 7
2023Zero- and Few-Shots Knowledge Graph Triplet Extraction with Large Language Modelscited by 7
2022TRIE++: Towards End-to-End Information Extraction from Visually Rich Documentscited by 6
2022AUC Maximization for Low-Resource Named Entity Recognitioncited by 6
2022Quant 4.0: Engineering Quantitative Investment with Automated, Explainable and Knowledge-driven Artificial Intelligencecited by 6
2023A Human Subject Study of Named Entity Recognition (NER) in Conversational Music Recommendation Queriescited by 6
2025Do LLMs Surpass Encoders for Biomedical NER?cited by 6
2023Leave no Place Behind: Improved Geolocation in Humanitarian Documentscited by 5
2023Making Large Language Models Better Knowledge Miners for Online Marketing with Progressive Prompting Augmentationcited by 5
2024Different Tastes of Entities: Investigating Human Label Variation in Named Entity Annotationscited by 5
2025Hybrid OCR-LLM Framework for Enterprise-Scale Document Information Extraction Under Copy-heavy Taskcited by 5
2023A Survey on Semantic Processing Techniquescited by 4
2023GestaltMML: Enhancing Rare Genetic Disease Diagnosis through Multimodal Machine Learning Combining Facial Images and Clinical Textcited by 4
2021Show, Write, and Retrieve: Entity-aware Article Generation and Retrievalcited by 3
2022Trigger-GNN: A Trigger-Based Graph Neural Network for Nested Named Entity Recognitioncited by 3
2023Depression Detection Using Digital Traces on Social Media: A Knowledge-aware Deep Learning Approachcited by 3
2023A Virtual Simulation-Pilot Agent for Training of Air Traffic Controllerscited by 3
2023A Confidence-based Partial Label Learning Model for Crowd-Annotated Named Entity Recognitioncited by 3

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