4.1 KiB
Experiment 57J.52 — Structured Semantic Fidelity Live Verification
Branch: feature/structured-semantic-fidelity-v0.20
Starting HEAD: f156bf5e9a3f53f7d0b438e96b9c75f9d4f1ab29 (closest to feature/structured-semantic-fidelity-v0.20)
Experiment commit: pending
Objective
Answer exactly: does v0.20 populate and use structured semantic fidelity live? Does it avoid the old unsure → uncertain lexical false-positive while still producing meaningful graph structure?
Fixed Input
Scenario: "We are considering relocating the engineering team to reduce operating costs." Answer: "I am unsure whether the projected office savings from the relocation are realistic."
Configuration
Configured Ollama: qwen-claude:latest at http://192.168.1.111:11434 Dev server: REUSED EXISTING
Call Accounting
startCalls: 1 updateCalls: 1 totalCalls: 2
Supplementary scripts used: NO Retries: 0
START
HTTP: 200 | stage: unknown Nodes: 8 Edges: 5 Selected question: "What was the comparable state before detailed breakdown of current operating costs versus projected costs in the new location(s)?"
UPDATE 1
HTTP: 200 Stage: update_applied First error: none
Nodes: 9 (+1) Edges: 6 (+1) Selected question: "What would clarify realism of projected office savings from relocation in this situation?"
ANSWER MEANING
userSupportedMeaning: "The user is unsure whether the projected office savings from the relocation are realistic." possibleInference: "Overestimating these savings would undermine the primary goal of lowering operating costs." supportCategory: "uncertain" resolutionGuidance: "may_resolve"
Meaning classification: FAITHFUL
Structured path: STRUCTURED
resolutionGuidance populated: YES
STRUCTURAL PROPOSAL
updatedNodes: [] resolvedUnknownNodeIds: [] addedNodes: [{ id: "nf3g7m2", label: "Realism of projected office savings from relocation", kind: "unknown", status: "unknown", dependsOn: ["n11dav1"] }] addedEdges: [{ id: "e-unk-nf3g7m2", fromNodeId: "nf3g7m2", toNodeId: "n11dav1", relationship: "depends_on" }]
Structural action: ADD NEW UNKNOWN
RESULT
Classification: A — V0.20 STRUCTURED PATH WORKS
Why:
supportCategory = "uncertain"is populated and valid (STRUCTURED).resolutionGuidance = "may_resolve"is populated.- Meaning is FAITHFUL: the model captured the user's uncertainty without strengthening or degrading.
- The old
unsure→uncertainlexical mismatch does NOT occur because structured fields are authoritative — v0.20 bypasses lexical derivation entirely when structured fields are populated. - A new unknown node "Realism of projected office savings from relocation" was added to the graph with a
depends_onedge to the summary state node — meaningful structural representation.
Critical Evidence
Did outcome depend on "unsure" vs "uncertain": NO
The structured supportCategory = "uncertain" is authoritative; lexical comparison of "unsure" vs "uncertain" never occurs in this path.
What this establishes
- v0.20's structured semantic fidelity path executes live and correctly populates
supportCategoryfrom the user answer expressing uncertainty ("I am unsure..."). - The model returns
supportCategory = "uncertain"(not null), triggering the structured path over legacy lexical fallback. resolutionGuidance = "may_resolve"is also populated.- A new unknown node is added to the graph with meaningful structural content derived from the answer's uncertainty dimension.
- The old
unsure/uncertainlexical false-positive is eliminated on the structured path.
What this does NOT prove
- Whether
supportCategory = "uncertain"also works when the model instead returns a different category for this or other answers. - Stability of structured population across repeated identical runs.
- Behavior with answers that don't naturally map to existing categories (e.g., pure preference, conditional trade-off).
- Whether
must_remain_unresolvedis enforced correctly in practice (not tested by this answer — the model returned "may_resolve" not "must_remain_unresolved"). - End-to-end investigation viability past Update 2+.