Reciprocal ranked fusion retrieval augmented generation hybrid artificial intelligence system

A computing device of a computing system, the computing device comprises:

• an interface;
• local memory;
• and
• processing module operably coupled to the interface and the local memory, wherein the local memory stores operational instructions that, when executed by the processing module, causes the computing device to:
• generate a neural network representation of a query by applying an identigen entigen processing approach that disambiguates a plurality of words of the query, wherein the processing module generates the neural network representation of the query by:
• determining a set of identigens for each word of the query to produce a plurality of sets of identigens, wherein a set of identigens of the plurality of sets of identigens represents one or more different meanings of a word of the query, wherein each identigen of the set of identigens includes a meaning identifier and an instance identifier, wherein each meaning identifier associated with a particular set of identigens represents a different meaning of one or more different meanings of a corresponding word of the query;
• generate a symbolic architecture representation of the query by further applying the identigen entigen processing approach to the neural network representation of the query, wherein the symbolic architecture representation of the query represents a most likely meaning interpretation of the query, wherein the processing module generates the symbolic architecture representation of the query by:
• interpreting, based on identigen pairing rules of a first knowledge database, pairs of sequentially adjacent identigens of adjacent sets of identigens of the plurality of sets of identigens to determine a most likely meaning interpretation of the query and produce a query entigen group, wherein the query entigen group represents the most likely meaning interpretation of the query, wherein each entigen of the query entigen group corresponds to a selected identigen of one of the plurality of sets of identigens having a selected meaning identifier of the one or more different meanings of a corresponding word of the query that represents a most likely meaning interpretation of the corresponding word, wherein each selected identigen corresponding to the query entigen group favorably pairs with at least one corresponding sequentially adjacent identigen of an adjacent set of identigens in accordance with the identigen pairing rules, wherein each entigen of the query entigen group represents a single conceivable and perceivable thing in space and time that is independent of language and is indicative of a corresponding selected identigen associated with the query entigen group, wherein the first knowledge database includes a plurality of records that link entigens having a connected meaning for a multitude of topic records that includes a record corresponding to a topic of the query;
• and
• generate a prompt for a large language model (LLM) artificial intelligence (AI) system utilizing the symbolic architecture representation of the query, wherein the processing module generates the prompt for the LLM AI system by:
• generating the prompt to include a representation of the query entigen group.

A non-transitory computer readable memory comprises:

• first memory element that stores operational instructions that, when executed by a processing module, causes the processing module to:
• generate a neural network representation of a query by applying an identigen entigen processing approach that disambiguates a plurality of words of the query, wherein the processing module generates the neural network representation of the query by:
• determining a set of identigens for each word of the query to produce a plurality of sets of identigens, wherein a set of identigens of the plurality of sets of identigens represents one or more different meanings of a word of the query, wherein each identigen of the set of identigens includes a meaning identifier and an instance identifier, wherein each meaning identifier associated with a particular set of identigens represents a different meaning of one or more different meanings of a corresponding word of the query;
• second memory element that stores operational instructions that, when executed by the processing module, causes the processing module to:
• generate a symbolic architecture representation of the query by further applying the identigen entigen processing approach to the neural network representation of the query, wherein the symbolic architecture representation of the query represents a most likely meaning interpretation of the query, wherein the processing module generates the symbolic architecture representation of the query by:
• interpreting, based on identigen pairing rules of a first knowledge database, pairs of sequentially adjacent identigens of adjacent sets of identigens of the plurality of sets of identigens to determine a most likely meaning interpretation of the query and produce a query entigen group, wherein the query entigen group represents the most likely meaning interpretation of the query, wherein each entigen of the query entigen group corresponds to a selected identigen of one of the plurality of sets of identigens having a selected meaning identifier of the one or more different meanings of a corresponding word of the query that represents a most likely meaning interpretation of the corresponding word, wherein each selected identigen corresponding to the query entigen group favorably pairs with at least one corresponding sequentially adjacent identigen of an adjacent set of identigens in accordance with the identigen pairing rules, wherein each entigen of the query entigen group represents a single conceivable and perceivable thing in space and time that is independent of language and is indicative of a corresponding selected identigen associated with the query entigen group, wherein the first knowledge database includes a plurality of records that link entigens having a connected meaning for a multitude of topic records that includes a record corresponding to a topic of the query;
• and
• a third memory element that stores operational instructions that, when executed by the processing module, causes the processing module to:
• generate a prompt for a large language model (LLM) artificial intelligence (AI) system utilizing the symbolic architecture representation of the query, wherein the processing module generates the prompt for the LLM AI system by:
• generating the prompt to include a representation of the query entigen group.