Multi-Level Deep Learning Model

A method of creating a true/false classifier comprising the steps of:

• prompting a Large Language Model for a factual statement about a first subject and a first object,
• prompting said Large Language Model for a counterfactual statement about a second subject and a second object,
• using a Natural Language Processing method on said factual statement to determine a first relationship between said first subject and said first object,
• using said Natural Language Processing method on said counterfactual statement to determine a second relationship between said second subject and said second object,
• creating a first Vectorized Triplet comprising:
• a vectorized first subject, comprising the aggregated output of a Vector Dictionary for said first subject,
• a vectorized first object, comprising the aggregated output of said Vector Dictionary for said first object, and
• a vectorized first relationship, comprising the aggregated output of said Vector Dictionary for said first relationship,
• creating a second Vectorized Triplet comprising
• a vectorized second subject, comprising the aggregated output of a Vector Dictionary for said second subject
• a vectorized second object, comprising the aggregated output of said Vector Dictionary for said second object, and
• a vectorized second relationship, comprising the aggregated output of said Vector Dictionary for said second relationship,
• finding a first nearest neighbor to said vectorized first relationship by searching a Relationship Dictionary using a distance metric,
• replacing said vectorized first relationship with that of said first nearest neighbor,
• finding a second nearest neighbor to said vectorized second relationship by searching said Relationship Dictionary using said distance metric, and
• replacing said vectorized second relationship with that of said second nearest neighbor.