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This invention describes a software system that automatically finds supply chain connections between companies. It works by using machine learning to scan large amounts of text, like news articles or reports, to identify sentences that mention two companies and their supply chain relationship. This evidence is then used to build a Knowledge Graph, which is a structured database of these relationships, and assign a confidence score to each connection. The claims specifically focus on a centralized Knowledge Graph system with a user interface for querying supply chain data.
Why it matters: Filed before the widespread adoption of Transformer models and Large Language Models. Today's LLMs can significantly enhance the accuracy and efficiency of identifying supply chain relationships from unstructured text and populating Knowledge Graphs, making the core ML task much more feasible and powerful.
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