JERAJournal of Electronic Research and Application2208-35022208-3510Bio-Byword Scientific Publishing Pty. Ltd.10.26689/jera.v8i5.8402ArticleA Novel Optimization Scheme for Named Entity Recognition with Pre-trained Language Modelshttps://artdesignp.com/journal/JERA/8/5/10.26689/jera.v8i5.8402LiShuanglong,ZhangXulong,WangJianzong2024852024-09-30Named Entity Recognition (NER) is crucial for extracting structured information from text. While traditional methods rely on rules, Conditional Random Fields (CRFs), or deep learning, the advent of large-scale Pre-trained Language Models (PLMs) offers new possibilities. PLMs excel at contextual learning, potentially simplifying many natural language processing tasks. However, their application to NER remains underexplored. This paper investigates leveraging the GPT-3 PLM for NER without fine-tuning. We propose a novel scheme that utilizes carefully crafted templates and context examples selected based on semantic similarity. Our experimental results demonstrate the feasibility of this approach, suggesting a promising direction for harnessing PLMs in NER.

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