In the landscape of AI and data science, the convergence of large language models (LLMs), knowledge graphs (KGs), and the Semantic Web ushers in a new era of intelligent systems. These technologies transform how machines understand and process human language while redefining the way knowledge is extracted, structured, and utilized. LLMs are enhanced by the structured data of KGs and the frameworks of the Semantic Web. Together, they revolutionize data processing, enabling deeper semantic understanding, and unlocking powerful new capabilities in AI-driven decision-making, search, and automation. This collaboration marks a leap forward in building systems that can reason, learn, and interact more like humans. LLMs, Knowledge Graphs, and the Semantic Web: Revolutionizing Data Processing, Knowledge Extraction, and AI Capabilities explores the relationship between LLMs and KGs as a part of the Semantic Web, showing how their integration can revolutionize data processing, knowledge extraction, and AI capabilities. It serves as a reference for Semantic Web technologies applied in LLMs and IoT. This book covers topics such as database technologies, metaverse, and intelligent systems, and is a useful resource for computer engineers, data scientists, academicians, researchers, and computer scientists.