Data exchange-enriched entity name resolution

A non-transitory computer-readable medium storing instructions that, when executed by one or more processors of a computer system, cause the computer system to perform operations comprising:

• receiving an input entity name associated with a plurality of data exchange events executed through a data exchange network over a temporal window;
• aggregating data exchange event data associated with the input entity name from the plurality of data exchange events, wherein the data exchange event data comprises information about participants and event characteristics associated with the data exchange events;
• providing the aggregated data exchange event data as input to a large language model configured to infer organizational characteristics for the input entity name, wherein the organizational characteristics comprise at least one inferred industry classification and at least one inferred organizational size attribute;
• transforming the at least one inferred industry classification into a vector representation in a learned industry classification space;
• retrieving a candidate set of reference entities from a database, wherein each reference entity is represented as a reference vector in the learned industry classification space;
• calculating an industry-based similarity score between the vector representation of the input entity name and each reference vector of the candidate set;
• calculating an organizational-size-based similarity score between the at least one inferred organizational size attribute of the input entity name and corresponding organizational size attributes of each reference entity in the candidate set;
• generating a combined confidence score for each reference entity in the candidate set by applying configurable weights to the industry-based similarity score and the organizational-size-based similarity score;
• and
• outputting a ranked list of reference entities ordered by the combined confidence scores, thereby improving accuracy of entity name resolution by incorporating data-exchange-derived contextual information that reduces ambiguity in matching named entities.

A system for data-exchange-enriched entity name resolution, the system comprising:

• one or more processors;
• one or more non-transitory computer-readable memories coupled to the one or more processors and storing instructions that, when executed by the one or more processors, cause the system to perform operations comprising:
• receiving an input entity name associated with a plurality of data exchange events executed through a data exchange network over a temporal window;
• aggregating data exchange event data associated with the input entity name from the plurality of data exchange events, wherein the data exchange event data comprises information about participants and event characteristics associated with the data exchange events;
• providing the aggregated data exchange event data as input to a large language model configured to infer organizational characteristics for the input entity name, wherein the organizational characteristics comprise at least one inferred industry classification and at least one inferred organizational size attribute;
• transforming the at least one inferred industry classification into a vector representation in a learned industry classification space;
• retrieving a candidate set of reference entities from a database, wherein each reference entity is represented as a reference vector in the learned industry classification space;
• calculating an industry-based similarity score between the vector representation of the input entity name and each reference vector of the candidate set;
• calculating an organizational-size-based similarity score between the at least one inferred organizational size attribute of the input entity name and corresponding organizational size attributes of each reference entity in the candidate set;
• generating a combined confidence score for each reference entity in the candidate set by applying configurable weights to the industry-based similarity score and the organizational-size-based similarity score;
• and
• outputting a ranked list of reference entities ordered by the combined confidence scores, thereby improving accuracy of entity name resolution by incorporating data-exchange-derived contextual information that reduces ambiguity in matching named entities.