Domain-Agnostic Natural Language Processing Using Explainable Interpretation Feedback Models

A computer system, the computer system comprising:

• one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage medium, and program instructions stored on at least one of the one or more computer-readable tangible storage medium for execution by at least one of the one or more processors via at least one of the one or more computer-readable memories, wherein the computer system is capable of performing a method comprising:
• receiving a natural language query from a user;
• automatically detecting whether the received natural language query includes an implicit intent using a reasoning engine, wherein the reasoning engine comprises domain-agnostic algorithms including domain-agnostic reasoning axioms;
• in response to detecting implicit intent in the received natural language query, automatically generating a modified query including a default inference from an interpretation fact sheet;
• automatically presenting the modified query to the user and prompting the user via an interface to provide user feedback on the modified query;
• in response to receiving user feedback indicating an approval of the modified query, automatically generating a final output;
• in response to receiving user feedback indicating a rejection of the modified query, automatically determining an alternative inference and presenting a further modified query including the alternative inference to the user;
• and
• automatically storing information obtained from the feedback in a fact history repository.

A computer program product, the computer program product comprising:

• one or more computer-readable tangible storage medium and program instructions stored on at least one of the one or more computer-readable tangible storage medium, the program instructions executable by a processor capable of performing a method, the method comprising:
• receiving a natural language query from a user;
• automatically detecting whether the received natural language query includes an implicit intent using a reasoning engine, wherein the reasoning engine comprises domain-agnostic algorithms including domain-agnostic reasoning axioms;
• in response to detecting implicit intent in the received natural language query, automatically generating a modified query including a default inference from an interpretation fact sheet;
• automatically presenting the modified query to the user and prompting the user via an interface to provide user feedback on the modified query;
• in response to receiving user feedback indicating an approval of the modified query, automatically generating a final output;
• in response to receiving user feedback indicating a rejection of the modified query, automatically determining an alternative inference and presenting a further modified query including the alternative inference to the user;
• and
• automatically storing information obtained from the feedback in a fact history repository.