# 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)

---

## 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