Hybrid language model and deterministic processing for uncertainty analysis

A method comprising:

• receiving a plurality of artifacts relating to an entity;
• retrieving a plurality of categories for assessing a level of uncertainty associated with the entity;
• for each category of the plurality of categories:
• inputting, into a generative model, the plurality of artifacts to extract a plurality of data points relating to the category and to standardize the plurality of data points according to a plurality of criteria, wherein the plurality of artifacts comprises multiple languages or evolving terminology;
• inputting the standardized plurality of data points into a rule-based model to cause the rule-based model to output a rating for the category;
• and
• inputting the rating, the standardized plurality of data points, and an intended recipient into the generative model to prompt the generative model to generate, according to a predefined structure, an assessment of the rating for the category and the standardized plurality of data points, wherein the generative model adapts a communication style and a technical depth of the assessment based on the intended recipient of the assessment;
• and
• outputting, to a corresponding intended recipient, a corresponding summary, a corresponding rating, and a corresponding standardized plurality of data points for each category of the plurality of categories.

A system comprising:

• a storage device;
• and
• one or more processors communicatively coupled to the storage device storing instructions thereon that cause the one or more processors to:
• receive a plurality of artifacts relating to an entity;
• receive a plurality of categories for assessing a level of uncertainty associated with the entity;
• for each category of the plurality of categories:
• prompt a generative model to retrieve, from the plurality of artifacts, a plurality of data points relating to the category and to standardize the plurality of data points according to a plurality of criteria;
• input the standardized plurality of data points into a rule-based model to cause the rule-based model to output a rating for the category;
• and
• input the rating, the standardized plurality of data points, and an intended recipient into the generative model to prompt the generative model to generate, according to a predefined structure, an assessment of the rating for the category and the standardized plurality of data points, wherein the generative model adapts a communication style and a technical depth of the assessment based on the intended recipient of the assessment;
• and
• output, to a corresponding intended recipient, a corresponding summary, a corresponding rating, and a corresponding standardized plurality of data points for each category of the plurality of categories.