Semantic Markup

Semantic markup aims to enrich digital documents with structured metadata describing their meaning and relationships, improving accessibility, interoperability, and analysis. Current research focuses on automatically generating and applying semantic markup using machine learning models, including neural networks (like CNNs and BERT) and large language models (LLMs), often incorporating techniques like in-context learning and chain-of-thought prompting. This work has significant implications for diverse fields, enabling improved data management, enhanced document processing for tasks like graphic design and mathematical reasoning, and more effective information retrieval and recommendation systems.