experiment: probe explicit hard constraint semantic fidelity

2026-08-09 14:13:48 +01:00
parent 23bfe5f756
commit 85ee4bed30
3 changed files with 220 additions and 0 deletions
@@ -201,3 +201,13 @@ Tested whether deterministic derivation refinement from commit `3e78d57` (refine
 5. Follow-up question correctly targets the emergent conditional/threshold unknown.

 **Key observation**: The LLM does not auto-populate `supportCategory` — it is consistently null in `answerMeaning`. The deterministic derivation layer in `readDiagnostics` (and the inline pipeline) is the sole mechanism by which meaning profile category gets determined. This confirms the design: LLM produces raw meaning; deterministic logic categorizes it. No regression detected. Full results in `docs/experiment-56d.md`. Branch: `feature/reasoning-fidelity-v0.8`. Status pending Rob's review.
+
+### Experiment 56J Summary — Regression D Explicit Hard Constraint Semantic Probe
+
+Tested whether the configured live Ollama model (`qwen-claude:latest` at `http://192.168.1.111:11434`) preserves explicit hard-constraint meaning from user answer "It's a hard constraint. I don't want any increase in risk." — Regression D from `docs/reasoning-refinement-requirements.md`.
+
+One live Ollama call (19,343 ms) returned `userSupportedMeaning: "Avoiding additional risk is a hard constraint, and no increase in risk is acceptable."` with `possibleInference: null`.
+
+**Classification: PASS.** The model preserved the explicit hard-constraint status without weakening it into preference/trade-off language and did not add unsupported interpretation. `possibleInference` is null, which is appropriate for a direct unambiguous answer.
+
+This experiment does not prove fidelity for other regression cases (E, F), consistency across multiple runs, or behavior in production reasoning paths. Branch: `feature/reasoning-fidelity-v0.8`. Files: `tests/reconstruction/semantic-regression-d-explicit-hard-constraint.test.js` and `docs/experiment-56j.md`. Status pending Rob's review.