Enhancing Named Entity Recognition with Large Language Models

The author explores a three-phase training strategy using GPT-4 annotations to enhance BERT model performance in Named Entity Recognition, emphasizing the synergy between distilled and original data. The study presents a scalable methodology to reduce manual annotation costs and increase efficiency in NLP tasks.