Semantic Template

Semantic templates are structured representations used to guide the generation or evaluation of text, particularly within the context of large language models (LLMs). Current research focuses on leveraging LLMs to create and utilize these templates for tasks like semi-structured document generation in public administration and biomedical entity normalization, often incorporating techniques like prompt engineering and multi-agent systems. This work aims to improve the semantic understanding and performance of LLMs, leading to more accurate and reliable applications in diverse fields requiring natural language processing. The development of robust semantic templates holds significant potential for enhancing the quality and efficiency of various LLM-based applications.