Named Entity Recognition Based on Multi-Class Label Prompt Selection and Core Entity Replacement
At present, researchers are showing a marked interest in the topic of few-shot named entity recognition (NER). Previous studies have demonstrated that prompt-based learning methods can effectively improve the performance of few-shot NER models and can reduce the need for annotated data. However, the...
Saved in:
| Main Authors: | Di Wu, Yao Chen, Mingyue Yan |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/11/6171 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Chinese Few-Shot Named-Entity Recognition Model Based on Multi-Label Prompts and Boundary Information
by: Cong Zhou, et al.
Published: (2025-05-01) -
Improving Few-Shot Named Entity Recognition with Causal Interventions
by: Zhen Yang, et al.
Published: (2024-12-01) -
A Nested Named Entity Recognition Model Robust in Few-Shot Learning Environments Using Label Description Information
by: Hyunsun Hwang, et al.
Published: (2025-07-01) -
Few-shot Named Entity Recognition for Medical Text
by: QIN Jian, et al.
Published: (2021-08-01) -
Few-Shot Named Entity Recognition Based on the Collaborative Graph Attention Network
by: Haoran Niu, et al.
Published: (2025-01-01)