LTNER: Large Language Model Tagging for Named Entity Recognition with Contextualized Entity Marking

Understand

The use of LLMs for natural language processing has become a popular trend in the past two years, driven by their formidable capacity for context comprehension and learning, which has inspired a wave of research from academics and industry professionals.

• However, for certain NLP tasks, such as NER, the performance of LLMs still falls short when compared to supervised learning methods.
• In our research, we developed a NER processing framework called LTNER that incorporates a revolutionary Contextualized Entity Marking Gen Method.
• By leveraging the cost-effective GPT-3.5 coupled with context learning that does not require additional training, we significantly improved the accuracy of LLMs in handling NER tasks.