Fighting Against the Repetitive Training and Sample Dependency Problem in Few-Shot Named Entity Recognition

Fighting Against the Repetitive Training and Sample Dependency Problem in Few-Shot Named Entity Recognition

Few-shot named entity recognition (NER) systems recognize entities using a few labeled training examples. The general pipeline consists of a span detector to identify entity spans in text and an entity-type classifier to assign types to entities. Current span detectors rely on extensive manual label...

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Bibliographic Details
Main Authors: Chang Tian, Wenpeng Yin, Dan Li, Marie-Francine Moens
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Artificial intelligence
data mining
feature extraction
few-shot learning
named entity recognition
natural language processing
Online Access:https://ieeexplore.ieee.org/document/10463035/

Internet

https://ieeexplore.ieee.org/document/10463035/

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