Prepare Training Corpus

Make the corpus reproducible before any expensive labeling or training call.

Define the contract

Write down:

• the population and approved data sources;
• the unit of an example and the group that must never cross splits;
• target split sizes and distributions;
• input, output, abstention, and identifier schemas;
• required positive, negative, ambiguous, and boundary cases;
• leakage rules for prompts, labels, canonical IDs, and teacher-only metadata.

Separate deterministic scenario generation from teacher labeling. Materialize and validate the entire candidate pool without model calls first.

Materialize deterministically