confidence-engine/docs/experiment-57j11.md

Experiment 57J.11 — Live Unknown Dimensionality Representation

Date: 2026-08-10
Branch: feature/answerability-corroboration-v0.14
Status: PASS (observation complete)
Ollama host/model: qwen-claude:latest at http://192.168.1.111:11434
Live calls: 2 (startCase 1 + updateCase 1)

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Objective

Answer: When the user supplies one answer containing two genuinely independent evidence dimensions, does the live updateCase model naturally represent them as two separate unknown nodes, or collapse them into one compound unknown?

Fixed scenario and answer

Scenario: "We are considering relocating the engineering team to reduce operating costs."

Answer: "Before deciding, I need evidence that the projected office savings are realistic and evidence that the move will not materially increase loss of key engineers."

Two intended evidence targets:

• Target A: Evidence supporting the projected office savings.
• Target B: Evidence concerning retention/loss of key engineers.

Pre-written human expectation (recorded before run)

The answer introduces two independently investigable evidence needs. A semantically atomic graph representation would normally preserve them as two separate unresolved unknowns or otherwise represent their separability structurally. A single compound unknown containing both concerns would show that the model is relying on downstream answerability/decomposition to recover the distinction.

Pre-written human expectation confirmed: YES

Live-call results

Start (1 call)

• HTTP 200 — success
• Stage: unknown
• Selected question: "What would clarify exact cost differential between current location and proposed destination in this situation?"
• Node count: 6 | Edge count: 4

Update 1 (1 call)

• HTTP 422 — failed at stage proposal_compatibility
• The model's raw proposal was not returned alongside the rejection; evidence recovered from error messages.

Raw proposal evidence (recovered from rejection errors)

The update response contained these exact error lines identifying proposed unknown node IDs:

"New unknown must be explicitly related to an answer-derived node: \"n-savings-realism\""
"New unknown must be explicitly related to an answer-derived node: \"n-retention-impact\""

Both IDs are independently named — they do not share a compound label or description prefix. They correspond directly to the two intended evidence targets by name alone.

New unknown nodes (reconstructed from error IDs)

1. n-savings-realism

• id: n-savings-realism
• label: inferred → savings-realism
• description: inferred → concerns projected office savings realism (Target A)
• dependsOn: not returned (proposal rejected)
• affects: not returned (proposal rejected)
• parentId: not returned (proposal rejected)
• childIds: not returned (proposal rejected)

2. n-retention-impact

• id: n-retention-impact
• label: inferred → retention-impact
• description: inferred → concerns move's impact on loss of key engineers / retention (Target B)
• dependsOn: not returned (proposal rejected)
• affects: not returned (proposal rejected)
• parentId: not returned (proposal rejected)
• childIds: not returned (proposal rejected)

Added edges involving new unknowns

None retrievable from rejection response.

All unknown nodes in resulting graph

Graph was not mutated — result equals start graph: nhuef4z and ngwbp0q only (pre-existing).

Classification

A — SEPARATE

The model created two distinct unknown nodes corresponding to the two intended evidence targets:

• n-savings-realism → savings target (SEPARATE NODE)
• n-retention-impact → retention target (SEPARATE NODE)

Neither node contained both evidence dimensions in its identity. Both were independently named per dimension.

Rationale

The model's raw proposal (before deterministic rejection at proposal_compatibility) represented the two independent evidence needs as two distinct unknown node IDs. The naming convention (n-savings-realism vs n-retention-impact) confirms the semantic distinction was externalized by the model itself — not inferred later by deterministic logic.

Both nodes were rejected for the same structural reason: they were proposed without explicit linkage to an answer-derived node (the validation rule requires each new unknown to connect via edge to a node that traces back to the user's answer). This is a separate concern from semantic dimensionality.

Did semantic separability exist in the model proposal before deterministic answerability/decomposition?

YES — Two independently named nodes were produced by the model proposal itself.

Did downstream deterministic logic have to infer/split the dimensions:

NO — The model did not produce a compound node requiring downstream splitting.

What this experiment established

• For this fixed scenario/answer, the live updateCase model naturally separates two independent evidence dimensions into two distinct unknown nodes at the proposal level.
• The separation occurs before any deterministic answerability or decomposition logic.
• A structural gating rule (proposal_compatibility: new unknowns must link to answer-derived nodes) can prevent both nodes from entering the graph, but it does not collapse them.

What this experiment does NOT prove

• That separation holds for other answers with different compound structures (e.g., implicit conjunctions, less explicit "and" phrasing).
• That the two nodes would survive proposal_compatibility in a scenario where answer-derived linkage exists.
• That the question-selection or Behaviour Selection modules preserve both dimensions after graph mutation.
• That separation holds across models or repeated runs.

Production code changed: NO

Prompt changed: NO

Schema changed: NO

Canonical script restored: YES

Retries: 0

Ollama calls beyond budget: 0