Modular subsequent generations of dedicated intermediate representations

A method comprising:

• receiving first natural language text requesting automatic generation of text, the first natural language text comprising a plurality of features of the text;
• for each feature in the plurality of features:
• generating a prompt for a corresponding feature;
• sending the prompt to a large language model (LLM) receiving, from the LLM, a generated intermediate representation;
• merging the generated intermediate representations for the plurality of features into an combined intermediate representation;
• and
• passing the combined intermediate representation to a programmatic component, which validates the combined intermediate representation and converts the combined intermediate representation into a final representation.

A non-transitory machine-readable medium storing instructions which, when executed by one or more processors, cause the one or more processors to perform operations comprising:

• receiving first natural language text requesting automatic generation of text, the first natural language text comprising a plurality of features of the text;
• for each feature in the plurality of features:
• generating a prompt for a corresponding feature;
• sending the prompt to a large language model (LLM) receiving, from the LLM, a generated intermediate representation;
• merging the generated intermediate representations for the plurality of features into an combined intermediate representation;
• and
• passing the combined intermediate representation to a programmatic component, which validates the combined intermediate representation and converts the combined intermediate representation into a final representation.