confidence-engine/docs/archive/experiments/post-v0.8-investigation/experiment-57j2.md

Experiment 57J.2 — Minimal Clarification Answerability Diagnostics

Date: 2026-08-10 Branch: feature/relationship-fallback-v0.13 HEAD at start: 90e6623 (experiment: validate relationship fallback live)

Objective

Capture the exact graph node text and answerability diagnostics for {"scenario":"test"} — determine what produces the reported prerequisiteConceptCount, and which prerequisite regex signals actually match.

Fixed Input

{"scenario":"test"}

Live Call Result

HTTP status: 200 Live Ollama calls: 1 (qwen-claude:latest at http://192.168.1.111:11434, duration: 27,109 ms)

Graph

• centralStatement: "test"
• activeUnknownNodeId: nlgonjv

Exact Active Unknown

• id: nlgonjv
• label: "The actual scenario, problem description, or data set intended for analysis."
• description: "The actual scenario, problem description, or data set intended for analysis."
• kind: unknown
• status: unknown

Question Diagnostics

• reconstructionQuestion: "What specific situation, problem, or scenario would you like me to reconstruct and analyze?"
• reconstructionQuestionAccepted: false
• rejectionReasons: ["reconstruction_question_not_authoritative", "graph_backed_pipeline_required"]
• finalGraphBackedQuestion: null
• selectedUnknownNodeId: null
• noQuestionReason: "Compatible unresolved candidates remain, but none produced a valid graph-backed question."

Answerability Diagnostics

• independentlyAnswerable: false
• prerequisiteConceptCount: 3
• decompositionRequired: true
• selectedContainerUnknown: nlgonjv
• selectedChildUnknown: null
• decompositionReason: null

Prerequisite Regex Signal Matching

The active unknown text (label + description) normalised by the code (lowercase, non-alphanumeric → space):

the actual scenario problem description or data set intended for analysis the actual scenario problem description or data set intended for analysis

#	Rule pattern	Result	Matched text
1	\bproblem\b	MATCH	problem
2	\b(audience|customer|user|buyer|stakeholder|recipient)\b	NO MATCH	—
3	\b(demand|seek help|actively look for help)\b	NO MATCH	—
4	\b(pay|willingness to pay|price|pricing)\b	NO MATCH	—
5	\b(compare|comparison|different from|alternatives|alternative|existing alternatives|existing tools|better than)\b	NO MATCH	—
6	\b(value|viability|justified|business case|commercial)\b	NO MATCH	—
7	\b(feasibility|technical)\b	NO MATCH	—

Prerequisite regex matches: 1 of 7 (only rule 1: problem)

Count Discrepancy Analysis

The API reports prerequisiteConceptCount: 3. The prerequisite regex only matches once.

However, countIndependentAnswerDimensions() computes the final count as:

Math.max(prerequisiteConceptCount, unresolvedDependencies, conjunctionCount + 1)

For this node:

• prerequisiteConceptCount (regex): 1
• unresolvedDependencies: 0 (single unknown with no dependsOn/affects edges)
• conjunctionCount: 2 ("or" appears twice in the normalised label+description)
• Final: Math.max(1, 0, 2+1) = 3

The count of 3 is driven by conjunction detection, not prerequisite concept signals. The node's description contains "scenario, problem description, or data set" — two instances of "or", yielding conjunctionCount=2, then +1 per the formula gives 3.

Consistency Classification: B — Inconsistent diagnostics

The reported prerequisiteConceptCount=3 does not correspond to seven prerequisite concept matches. It is a composite count including conjunction-based amplification. Only 1 of 7 prerequisite regex patterns actually matched; the remaining 2 units come from conjunction counting (or × 2 → +1).

What This Experiment Established

• The {"scenario":"test"} input produces a minimal graph with centralStatement="test" and one unknown node (nlgonjv) about the missing scenario context itself.
• The active unknown label/description contains "problem" (prerequisite signal) and two instances of "or" (conjunction).
• prerequisiteConceptCount is computed as Math.max(regex_matches, unresolved_deps, conjunctions + 1) — meaning the name is misleading; it reports a maximum across three different amplification strategies, not just prerequisite concept signals.
• Reconstruction question was generated but rejected (not authoritative per pipeline design). No graph-backed question produced.

What This Experiment Does NOT Prove

• Whether other scenarios produce different decomposition paths.
• Whether conjunction-based amplification is appropriate for this node type (the unknown is about missing context, not a compound inquiry).
• Stability of the initial graph across runs.
• Whether prerequisiteConceptCount as reported should be disaggregated into its constituent signals (regex count vs conjunction count vs unresolved deps).

Production code changed: NO

Tests changed: NO

Retries: 0

Ollama calls beyond budget: 0