Knowledge graph - Scientific news
A research team at the University of Cambridge has published a study in Nature Machine Intelligence introducing "Semantic Entropy Mapping" for Knowledge Graphs. This new mathematical technique allows Large Language Models (LLMs) to quantify the uncertainty of relationships within a graph, enabling the model to identify ambiguous data points and trigger human--in--the--loop verification. For the business sector, this provides a critical safety mechanism for AI--driven supply chain management and financial forecasting, as it prevents autonomous systems from acting on low--confidence or contradictory information. By mapping the "informational density" of the graph, enterprises can now prioritize data cleaning efforts on the nodes that most impact AI decision--making quality.