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This invention describes a software system designed to understand unstructured text, such as patient notes. It works by identifying important phrases, connecting them to established concepts in a knowledge base, and then building a structured representation of the text. When a user asks for information about a specific concept, the system uses this representation to retrieve and present the relevant phrases from the original text. The claims specify that this representation links concepts to their neighbors and treats each concept as a node.
Why it matters: Filed before the widespread capabilities of large language models (LLMs) were apparent. Modern LLMs, developed significantly after 2017, can now perform the core functions of concept extraction, model generation, and contextual understanding with far greater accuracy and efficiency, making this system much more viable.
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