mlsanityData to 7 Oct 2026

Example-Based Named Entity Recognition

arXiv 2008.10570 ↗First posted 24 Aug 2020cs.CL cs.IRcited by 19

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Abstract (arXiv)

We present a novel approach to named entity recognition (NER) in the presence of scarce data that we call example-based NER. Our train-free few-shot learning approach takes inspiration from question-answering to identify entity spans in a new and unseen domain. In comparison with the current state-of-the-art, the proposed method performs significantly better, especially when using a low number of support examples.

Key facts. Cited by 19 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Aug 2020.

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Citing papers per year: 2021: 5; 2022: 6; 2023: 6; 2024: 1; 2025: 1.

19 papers.

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  1. 2021What Makes Good In-Context Examples for GPT-3?cited by 1,184
  2. 2021Template-Based Named Entity Recognition Using BARTcited by 153
  3. 2021Few-shot Intent Classification and Slot Filling with Retrieved Examplescited by 35
  4. 2022InstructionNER: A Multi-Task Instruction-Based Generative Framework for Few-shot NERcited by 31
  5. 2021LightNER: A Lightweight Tuning Paradigm for Low-resource NER via Pluggable Promptingcited by 27
  6. 2022DeepKE: A Deep Learning Based Knowledge Extraction Toolkit for Knowledge Base Populationcited by 17
  7. 2023PromptNER: Prompt Locating and Typing for Named Entity Recognitioncited by 17
  8. 2021Learning from Language Description: Low-shot Named Entity Recognition via Decomposed Frameworkcited by 15
  9. 2022QaNER: Prompting Question Answering Models for Few-shot Named Entity Recognitioncited by 15
  10. 2023A Multi-Task Semantic Decomposition Framework with Task-specific Pre-training for Few-Shot NERcited by 9
  11. 2022SpanProto: A Two-stage Span-based Prototypical Network for Few-shot Named Entity Recognitioncited by 8
  12. 2022Inverse is Better! Fast and Accurate Prompt for Few-shot Slot Taggingcited by 5
7 more
  1. 2023Do not Mask Randomly: Effective Domain-adaptive Pre-training by Masking In-domain Keywordscited by 5
  2. 2023Uncertainty-aware Self-training for Low-resource Neural Sequence Labelingcited by 3
  3. 2023ContrastNER: Contrastive-based Prompt Tuning for Few-shot NERcited by 3
  4. 2024Large-Scale Label Interpretation Learning for Few-Shot Named Entity Recognitioncited by 2
  5. 2022Prompt-based Text Entailment for Low-Resource Named Entity Recognitioncited by 1
  6. 2023Text sampling strategies for predicting missing bibliographic linkscited by 1
  7. 2025FewTopNER: Integrating Few-Shot Learning with Topic Modeling and Named Entity Recognition in a Multilingual Frameworkcited by 1