Knowledge Graph

Knowledge graphs (KGs) are structured representations of information, aiming to organize data into interconnected entities and relationships to facilitate knowledge discovery and reasoning. Current research heavily focuses on integrating KGs with large language models (LLMs) to enhance question answering, knowledge graph completion, and other knowledge-intensive tasks, often employing retrieval-augmented generation (RAG) and graph neural network architectures. This integration improves the accuracy and efficiency of various applications, ranging from legal article recommendation and medical diagnosis to supporting legislative processes and scholarly research. The resulting advancements have significant implications for diverse fields requiring complex information processing and reasoning.