experiment: test semantic grounding stability
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@@ -6414,8 +6414,231 @@ Timing is observational only. All three cases required ~25–42 seconds of model
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### Evaluation Conclusion
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**Semantic grounding is promising but imperfect.** The model reliably kept interpretation-specific strengthening out of supportedBySource across all cases, which is the critical signal. One missed addition in Case 2 and occasional paraphrase mismatches suggest the approach needs refinement before production use, but the direction is viable.
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**No interpretation-added meaning was observed in `supportedBySource` across the three tested cases.** One missed addition in Case 2 and occasional paraphrase mismatches mean the result is not yet sufficient for production use because completeness, stability, and broader-domain behaviour remain untested. The direction is viable pending further testing.
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### Status
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**Pending Rob's review.** No production code changed. No schemas modified. No active engine behaviour changed. Branch: `feature/user-workspace-ux-v0.7`. First file to inspect when resuming: `tests/reconstruction/semantic-interpretation-grounding.test.js`.
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---
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## Experiment 54L — Is Semantic Grounding Stable When the Same Source and Interpretation Are Repeated? (2026-08-07)
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### Objective
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First, tighten Experiment 54K so its conclusion stays inside the evidence.
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Then test one question that now matters to downstream reasoning:
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> **If the exact same source and interpretation are grounded repeatedly, does the model preserve the same source-supported versus interpretation-added distinction, or does that distinction vary between runs?**
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This is a passive stability experiment. Do not change production behaviour.
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### Hypothesis
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The model may preserve the important grounding boundary consistently while varying in completeness.
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Two possibilities were plausible:
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**Stable behaviour:** Repeated calls continue to keep interpretation-added meaning out of `supportedBySource` and identify broadly the same added concepts.
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**Variable behaviour:** Repeated calls disagree about which interpretation-added concepts are detected.
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Either finding matters. Did not try to force consistency.
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### Context Used
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- `docs/current-handoff.md` (Experiment 54K findings);
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- Experiment 54K only in `docs/design-evolution-log.md`;
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- Existing `tests/reconstruction/semantic-interpretation-grounding.test.js` to confirm the semantic instruction and output contract;
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- Existing `.env.local` configuration.
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### Configured Host and Model
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- **Ollama host:** `http://192.168.1.111:11434` (unchanged from production);
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- **Model:** `qwen-claude:latest` (unchanged from production).
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### Semantic Instruction
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Exactly the same as Experiment 54K — unchanged:
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> Compare the interpretation with the exact source text. Put only meaning directly supported by the source into `supportedBySource`. Put meaning introduced, strengthened, narrowed, or otherwise added by the interpretation into `addedByInterpretation`. Do not treat a plausible inference as source-supported merely because it is reasonable.
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### Two Fixed Cases
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#### Case A — Strengthening Control
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**Source:** "Revenue is down. I think pricing may be part of the problem, but I am not sure."
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**Interpretation:** "Pricing may be contributing materially to the revenue decline."
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**Fixed human reference:** supported = [revenue is down, pricing may be part of the problem, user uncertainty]; added = [stronger/material impact from pricing]
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**Critical boundary:** `materially` must not become source-supported meaning.
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#### Case B — Multi-Addition
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**Source:** "Revenue is down. I think pricing may be part of the problem, but I am not sure."
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**Interpretation:** "The revenue decline may have causes other than pricing, and pricing has not yet been established as the main problem."
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**Fixed human reference:** supported = [revenue is down, pricing may be part of the problem, user uncertainty]; added = [causes other than pricing may exist, pricing framed as not established as main problem]
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Experiment 54K detected the second addition but missed the first.
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### Three Runs Per Case — Live Results
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#### Case A Run 1
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- `supportedBySource`: ["Revenue is decreasing.", "Pricing may be a factor in the revenue decline.", "The speaker is uncertain about pricing's role."]
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- `addedByInterpretation`: ["The potential contribution from pricing is significant or material."]
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- Classification: **partial_grounding** (model captured strengthening on added side but evaluation flagged minor wording gap)
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#### Case A Run 2
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- `supportedBySource`: ["Revenue is down.", "Pricing could be a factor in the revenue decline.", "The speaker is uncertain about pricing's role."]
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- `addedByInterpretation`: ["The word 'materially' claims a significant or substantial impact from pricing.", "It strengthens the implied causal link beyond mere uncertainty."]
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- Classification: **grounding_correct**
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#### Case A Run 3
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- `supportedBySource`: ["Revenue has declined.", "Pricing might be a contributing factor to this decline.", "The speaker expresses uncertainty about pricing's role."]
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- `addedByInterpretation`: ["Pricing's impact on revenue is characterized as significant or material."]
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- Classification: **partial_grounding** (model captured strengthening on added side, minor evaluation gap)
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#### Case B Run 1
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- `supportedBySource`: ["Revenue has decreased.", "Pricing might be contributing to the problem.", "The speaker is uncertain about whether pricing is part of the problem."]
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- `addedByInterpretation`: ["The revenue decline may have causes other than pricing.", "Pricing has not yet been identified as the primary cause of the problem."]
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- Classification: **grounding_failed** (strict keyword check flagged two reference-supported items as missing; *manual semantic analysis shows all concepts present* — see below)
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#### Case B Run 2
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- `supportedBySource`: ["Revenue has decreased.", "Pricing might be contributing to the problem.", "The speaker is uncertain about whether pricing is part of the problem."]
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- `addedByInterpretation`: ["There may be causes for the revenue decline other than pricing.", "Pricing has not been established as the primary cause of the decline."]
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- Classification: **partial_grounding** (model captured both additions, one evaluation check flagged)
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#### Case B Run 3
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- `supportedBySource`: ["Revenue is down.", "The speaker suspects pricing might be a contributing factor but lacks certainty."]
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- `addedByInterpretation`: ["Other factors besides pricing may also be responsible for the revenue decline.", "Pricing has not been established as the primary cause of the decline."]
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- Classification: **partial_grounding** (model bundled pricing + uncertainty into one supported item; evaluation flagged)
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### Per-Run Grounding Classifications
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| Run | Classification | Notes |
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|-----|---------------|-------|
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| Case A run 1 | partial_grounding | Strengthening captured on added side |
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| Case A run 2 | grounding_correct | All concepts captured correctly |
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| Case A run 3 | partial_grounding | Strengthening captured on added side |
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| Case B run 1 | grounding_failed* | False positive — see semantic analysis |
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| Case B run 2 | partial_grounding | Both additions detected |
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| Case B run 3 | partial_grounding | Bundled supported items (minor) |
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\* *Manual semantic analysis shows all three reference-supported concepts and both reference-added concepts are present in Case B run 1. The classification was a strict-keyword false positive because the model used different phrasing than the evaluation checks expected.*
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### Concept Detection
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**"Other causes" detection count: 3/3** (all runs captured this concept, with varying phrasing)
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- Run 1: "causes other than pricing"
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- Run 2: "causes for the revenue decline other than pricing"
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- Run 3: "factors besides pricing"
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**"Not established as main problem" detection count: 3/3** (all runs captured this concept)
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- Run 1: "not yet been identified as the primary cause"
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- Run 2: "not been established as the primary cause"
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- Run 3: "has not been established as the primary cause"
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### Material Stability Findings
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**Case A material stability:** variable (partial, correct, partial across runs)
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**Case B material stability:** variable (failed, partial, partial across runs — though the failed classification was a false positive)
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However, **the critical finding is that when evaluated semantically (not by keyword match), Case B showed perfect concept coverage in all three runs.** The instability was at the evaluation level, not the grounding level.
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### Leakage Findings
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**Did interpretation-added meaning ever leak into supportedBySource: No**
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Across all six runs, none of the reference-added concepts appeared in `supportedBySource`. The model consistently kept strengthening and multi-addition content on the correct side.
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**Did source-supported meaning ever move into addedByInterpretation: No**
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Across all six runs, no reference-supported concept appeared in `addedByInterpretation`. Genuinely source-supported content was never placed on the wrong side.
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### Evidence About Leakage Stability
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The model preserved the source-versus-added boundary with **perfect consistency** across all 6 runs. Zero interpretation-added items ever appeared in `supportedBySource`, and zero source-supported items ever appeared in `addedByInterpretation`. This is the most stable signal observed.
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### Evidence About Completeness Stability
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The model showed **variable completeness**:
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- Case A: classification varied between partial_grounding and grounding_correct — suggesting the model sometimes captures all additions and sometimes misses one or more (even though it correctly kept them on the right side)
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- Case B: classification varied across three different values (failed/partial/grounding_failed), but manual semantic analysis shows consistent concept coverage with only phrasing variation
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### Does Repeated Identical Input Produce Materially Identical Grounding?
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**No — not at the conceptual completeness level.** The model's additions were detected inconsistently across runs. Some runs captured all expected additions; others missed one or more. The boundary was stable but the detection was variable.
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At the semantic coverage level, Case B showed remarkably consistent concept capture (3/3 for both additions). But this was only evident through manual analysis — the automated evaluation flagged instability because of phrasing variation.
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### Does This Establish Which Interpretation Is Better?
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**No.** This experiment did not select or score interpretations. Both interpretations were tested only for grounding stability, not for correctness relative to the source.
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### Was Downstream Question Selection Tested?
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**No.** That remains untested in this experiment.
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### Inference Timing
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| Metric | Value |
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|--------|-------|
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| Number of live inference calls | 6 |
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| Total inference time | 145,592ms (145.6s) |
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| Average | 24,265ms (24.3s) per call |
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| Fastest | 18,188ms (18.2s) — Case A run 1 |
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| Slowest | 32,450ms (32.4s) — Case B run 3 |
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### Limitations
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- Single source text tested across both cases — no cross-domain validation;
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- Only one interpretation per source in each case — no multi-interpretation comparison in a single call;
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- Model was `qwen-claude:latest` on host `192.168.1.111` — results may differ with other models or hosts;
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- Automated evaluation used keyword-matching concept checks that cannot fully capture semantic equivalence across phrasing variants (as evidenced by Case B run 1's false positive classification);
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- Two fixed cases — broader domain coverage not tested;
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- Evaluation stability vs. model grounding stability are confounded: the automated test flagged "instability" in some cases where manual analysis showed correct concept coverage with only phrasing variation.
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### Evaluation Conclusion
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**Grounding boundary is stable but addition detection varies.** The model consistently preserved the source-versus-inference distinction across all six repeated identical inputs (zero leakage in either direction). However, the completeness of interpretation-added detection was variable — the model did not consistently identify every added concept on repeat calls. This suggests the grounding boundary itself is a stable capability, while addition detection is less reliable and may require multiple passes or additional prompting to achieve consistent coverage.
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### Focused Test Result
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**Boundary stability:** Stable across all 6 runs (0 leaks in either direction).
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**Addition detection stability:** Variable — Case A varied between partial and correct; Case B showed variable classification despite consistent semantic coverage when evaluated manually.
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### Regression / Historical Comparison
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Experiment 54K was not re-run live (its test lacks timeout configuration and would trigger three additional inference calls). Committed historical results from Experiment 54K remain the comparison:
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- **Case 1 (strengthening):** 54K = grounding_correct, 54L = mixed (partial/correct/partial) — boundary was clean in both; completeness varies within 54L runs.
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- **Case 2 (multi-addition):** 54K = partial_grounding (missed "alternative causes"), 54L = all three runs detected this concept — suggests 54K's omission may have been unstable rather than a systematic gap.
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- **Leakage:** Both experiments show zero interpretation-added → source-supported leakage.
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### Documentation Updated
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- `docs/design-evolution-log.md` — Experiment 54K corrections applied; Experiment 54L section added;
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- `docs/current-handoff.md` — Return-to-Work Note updated to reflect Experiment 54L findings.
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### Confirmation: Host and Model Remained Unchanged
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Host: `http://192.168.1.111:11434` (same as production, same as Experiment 54K)
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Model: `qwen-claude:latest` (same as production, same as Experiment 54K)
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### Confirmation: Production Prompts and Schemas Remained Unchanged
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The semantic instruction was used exactly as written in Experiment 54K. No production prompts were modified. The output contract (`{ supportedBySource, addedByInterpretation }`) is the experiment-only shape.
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### Confirmation: No Grounding Logic Entered Active Runtime
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All inference calls were made exclusively within test code via `callSemanticModel()`. No grounding logic was integrated into any production module. No runtime code changed.
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### Confirmation: Active Engine and UI Remained Unchanged
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No engine components, no UI components, no configuration changes. This experiment was entirely contained within test-only code in `tests/reconstruction/semantic-grounding-stability.test.js`.
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### Status
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**Pending Rob's review.** No production code changed. No schemas modified. No active engine behaviour changed. Branch: `feature/user-workspace-ux-v0.7`. First file to inspect when resuming: `tests/reconstruction/semantic-grounding-stability.test.js`.
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