Building dialogue data that knows why people say things
Technical articles on synthetic dialogue generation, belief state modeling,
deterministic evaluation, and the infrastructure behind psychologically coherent AI training data.
We released four dialogue datasets where the cognitive ground truth — intent, goal, belief state, relationship dynamics — was computed before the text was generated, not inferred afterward. 400 conversations, 8,404 turns, 23 columns.
Most dialogue datasets give you the words. This article explains the four belief dimensions StrataSynth records per turn — trust, hostility, self-worth, resolution — how they update deterministically, and why causal ground truth changes what you can train on.
Evaluating AI-generated dialogue with another AI creates a circular system where both share the same failure modes. Here is the concrete failure it misses, and the 12 deterministic metrics we use instead.