mlsanityData to 14 Oct 2026

NeuroNER: an easy-to-use program for named-entity recognition based on neural networks

arXiv 1705.05487 ↗First posted 16 May 2017cs.CL cs.NE stat.MLcited by 25

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Abstract (arXiv)

Named-entity recognition (NER) aims at identifying entities of interest in a text. Artificial neural networks (ANNs) have recently been shown to outperform existing NER systems. However, ANNs remain challenging to use for non-expert users. In this paper, we present NeuroNER, an easy-to-use named-entity recognition tool based on ANNs. Users can annotate entities using a graphical web-based user interface (BRAT): the annotations are then used to train an ANN, which in turn predict entities' locations and categories in new texts. NeuroNER makes this annotation-training-prediction flow smooth and accessible to anyone.

Key facts. Cited by 25 papers in the map (data through 14 Oct 2026). First posted on arXiv 16 May 2017.

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Citing papers per year: 2021: 5; 2022: 7; 2023: 5; 2024: 5; 2025: 3.

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  1. 2024Natural Language Processing for the Legal Domain: A Survey of Tasks, Datasets, Models, and Challengescited by 42
  2. 2023GeoLM: Empowering Language Models for Geospatially Grounded Language Understandingcited by 37
  3. 2021How Good Is NLP? A Sober Look at NLP Tasks through the Lens of Social Impactcited by 18
  4. 2022Location reference recognition from texts: A survey and comparisoncited by 17
  5. 2025MapQA: Open-domain Geospatial Question Answering on Map Datacited by 15
  6. 2021Lights, Camera, Action! A Framework to Improve NLP Accuracy over OCR documentscited by 11
  7. 2022The Leaf Clinical Trials Corpus: a new resource for query generation from clinical trial eligibility criteriacited by 10
  8. 2024GeoReasoner: Reasoning On Geospatially Grounded Context For Natural Language Understandingcited by 10
  9. 2022Computer Science Named Entity Recognition in the Open Research Knowledge Graphcited by 9
  10. 2023In the Name of Fairness: Assessing the Bias in Clinical Record De-identificationcited by 9
  11. 2024HunFlair2 in a cross-corpus evaluation of biomedical named entity recognition and normalization toolscited by 8
  12. 2023Leave no Place Behind: Improved Geolocation in Humanitarian Documentscited by 5
13 more
  1. 2025RedactOR: An LLM-Powered Framework for Automatic Clinical Data De-Identificationcited by 5
  2. 2021Event-based clinical findings extraction from radiology reports with pre-trained language modelcited by 3
  3. 2022Examining Large Pre-Trained Language Models for Machine Translation: What You Don't Know About Itcited by 3
  4. 2022Exploring the Value of Pre-trained Language Models for Clinical Named Entity Recognitioncited by 3
  5. 2023Korean Named Entity Recognition Based on Language-Specific Featurescited by 3
  6. 2021An Analysis Of Protected Health Information Leakage In Deep-Learning Based De-Identification Algorithmscited by 2
  7. 2022Boosting Entity Mention Detection for Targetted Twitter Streams with Global Contextual Embeddingscited by 2
  8. 2025Improving the Performance of Radiology Report De-identification with Large-Scale Training and Benchmarking Against Cloud Vendor Methodscited by 2
  9. 2021Performance of Automatic De-identification Across Different Note Typescited by 0
  10. 2022The NLP Sandbox: an efficient model-to-data system to enable federated and unbiased evaluation of clinical NLP modelscited by 0
  11. 2023Towards End-User Development for IoT: A Case Study on Semantic Parsing of Cooking Recipes for Programming Kitchen Devicescited by 0
  12. 2024Information Extraction: An application to the domain of hyper-local financial data on developing countriescited by 0
  13. 2024A Brief History of Named Entity Recognitioncited by 0