Identifying entity attribute relations
Topics: AI Mode, Brand Context, Data Mining, E-E-A-T, Knowledge Graph, LLMO / GEO, Probably in use
This Google patent describes a method and system developed by Google for identifying entity-attribute relationships within large text corpora. The system uses a classification model that combines multiple types of embeddings — path embeddings from sentences, distributional representations of entities and attributes, and attribute distributional embeddings derived from known entity-attribute pairs — to determine whether a candidate attribute truly belongs to a given entity. By leveraging knowledge about similar entities and their shared attributes, the system can discover entity-attribute relationships that would not be apparent from sentence context alone, improving accuracy over prior approaches. A feedforward neural network makes the final determination by processing a concatenated vector of all these embeddings.
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