Entity linking using subgraph matching

A computer-implemented method, comprising:

• extracting, by an extraction module, a first attribute set from an information source, wherein the first attribute set corresponds to an unknown entity, and wherein the first attribute set comprises first attributes;
• generating, by a graph generation module, an unknown entity graph comprising first nodes corresponding to the first attributes;
• retrieving, by the extraction module, a second attribute set from a database comprising known entities, wherein the second attribute set corresponds to one of the known entities, and wherein the second attribute set comprises second attributes;
• generating, by the graph generation module, a known entity graph comprising second nodes corresponding to the second attributes;
• generating, by a graph neural network model, an unknown entity graph embedding by applying the unknown entity graph to the graph neural network model;
• generating, by the graph neural network model, a known entity graph embedding by applying the known entity graph to the graph neural network model;
• generating, by an embedding similarity module, an embedding space similarity score based on the unknown entity graph embedding and the known entity graph embedding;
• determining, by a recommendation module, an overall similarity score based on the embedding space similarity score;
• and
• assigning, by the recommendation module, the information source to one of the known entities based on the overall similarity score.

An entity linking system, comprising:

• a graph generation module operable to generate:
• an unknown entity graph based on a first attribute set comprising first attributes, wherein the first attributes are extracted from an information source, wherein the first attribute set corresponds to an unknown entity, and wherein the unknown entity graph comprises first nodes corresponding to the first attributes;
• and
• a known entity graph based on a second attribute set comprising second attributes, wherein the second attributes are retrieved from a database comprising known entities, wherein the second attribute set corresponds to one of the known entities, and wherein the known entity graph comprises second nodes corresponding to the second attributes;
• a graph neural network configured to generate:
• an unknown entity graph embedding based on the unknown entity graph;
• and
• a known entity graph embedding based on the known entity graph;
• an embedding space similarity module configured to generate an embedding space similarity score based on the unknown entity graph embedding and the known entity graph embedding;
• and
• a recommendation module configured to assign the information source to one of the known entities based on the embedding space similarity score.