# Example-Based Named Entity Recognition

arXiv: https://arxiv.org/abs/2008.10570 · HTML: https://mlsanity.com/paper/2008.10570/

## Key facts

- Cited by 19 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Aug 2020.

## Built on by (most cited first, 19 of 19)

- [What Makes Good In-Context Examples for GPT-3?](https://mlsanity.com/paper/2101.06804/) (2021)
- [Template-Based Named Entity Recognition Using BART](https://mlsanity.com/paper/2106.01760/) (2021)
- [Few-shot Intent Classification and Slot Filling with Retrieved Examples](https://mlsanity.com/paper/2104.05763/) (2021)
- [InstructionNER: A Multi-Task Instruction-Based Generative Framework for Few-shot NER](https://mlsanity.com/paper/2203.03903/) (2022)
- [LightNER: A Lightweight Tuning Paradigm for Low-resource NER via Pluggable Prompting](https://mlsanity.com/paper/2109.00720/) (2021)
- [DeepKE: A Deep Learning Based Knowledge Extraction Toolkit for Knowledge Base Population](https://mlsanity.com/paper/2201.03335/) (2022)
- [PromptNER: Prompt Locating and Typing for Named Entity Recognition](https://mlsanity.com/paper/2305.17104/) (2023)
- [Learning from Language Description: Low-shot Named Entity Recognition via Decomposed Framework](https://mlsanity.com/paper/2109.05357/) (2021)
- [QaNER: Prompting Question Answering Models for Few-shot Named Entity Recognition](https://mlsanity.com/paper/2203.01543/) (2022)
- [A Multi-Task Semantic Decomposition Framework with Task-specific Pre-training for Few-Shot NER](https://mlsanity.com/paper/2308.14533/) (2023)
- [SpanProto: A Two-stage Span-based Prototypical Network for Few-shot Named Entity Recognition](https://mlsanity.com/paper/2210.09049/) (2022)
- [Inverse is Better! Fast and Accurate Prompt for Few-shot Slot Tagging](https://mlsanity.com/paper/2204.00885/) (2022)
- [Do not Mask Randomly: Effective Domain-adaptive Pre-training by Masking In-domain Keywords](https://mlsanity.com/paper/2307.07160/) (2023)
- [Uncertainty-aware Self-training for Low-resource Neural Sequence Labeling](https://mlsanity.com/paper/2302.08659/) (2023)
- [ContrastNER: Contrastive-based Prompt Tuning for Few-shot NER](https://mlsanity.com/paper/2305.17951/) (2023)
- [Large-Scale Label Interpretation Learning for Few-Shot Named Entity Recognition](https://mlsanity.com/paper/2403.14222/) (2024)
- [Prompt-based Text Entailment for Low-Resource Named Entity Recognition](https://mlsanity.com/paper/2211.03039/) (2022)
- [Text sampling strategies for predicting missing bibliographic links](https://mlsanity.com/paper/2301.01673/) (2023)
- [FewTopNER: Integrating Few-Shot Learning with Topic Modeling and Named Entity Recognition in a Multilingual Framework](https://mlsanity.com/paper/2502.02391/) (2025)

## 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.