Run #003 surfaced rampant cross-pollination: Q2's "OSHA-30 forklift Wisconsin" recording (w-4435) became warm top-1 for Q19 (dental hygienist), Q20 (RN), Q21 (software engineer), and 6 other unrelated staffing queries. Cause: InjectPlaybookMisses inherited the same DefaultPlaybookMaxDistance (0.5) as the boost path, but inject is structurally riskier than boost — boost only re-ranks results that already retrieved on their own merits, while inject FORCES a result into top-K, so a loose match cross-pollinates wrong-domain answers. Empirical motivation from v3: Implied playbook hit distances for cross-pollinated cases: 0.20-0.46 Implied distances for the 6/6 paraphrase recoveries: 0.23-0.30 Threshold of 0.20 should keep most paraphrases, kill the OOD bleed. Implementation: - New DefaultPlaybookMaxInjectDistance = 0.20 in playbook.go. - New PlaybookMaxInjectDistance field on SearchRequest (override). - InjectPlaybookMisses signature gains maxInjectDist param; hits whose Distance exceeds it are skipped (boost path may still re-rank them). - TestInjectPlaybookMisses_RespectsInjectThreshold locks the contract with one tight + one loose hit, asserting only the tight one injects. - Existing tests pass explicit threshold (0 = default for tight tests, 0.5 for the dedupe test which uses 0.30 hits). Run #004 result on identical queries with the split threshold: Verbatim discovery 8 (vs v3's 6 — judge variance, separate) Verbatim lift 6 / 8 (75%) Paraphrase top-1 6 / 8 (75%) Paraphrase any-rank in K 6 / 8 OOD queries Q19/Q20/Q21 ALL show warm top-1 = cold top-1 (no injection) — cross-pollination eliminated where it was wrong-direction. Mean Δ top-1 distance dropped from -0.164 (v3, distorted) to -0.071 (v4, comparable to v1's -0.053). Two paraphrases missed in v4 (Q9, Q15) were ones where qwen2.5 rephrased liberally enough to drift past 0.20 — Q9: "Inventory specialist..." → "Individual needed for inventory management..." and Q15: "Engaged warehouse associate..." → "Warehouse associate currently engaged with a robust history...". The system correctly refusing to inject when it's not confident is the right product behavior; the boost path still re-ranks recorded answers when they appear in regular retrieval. The Q6 ↔ Q7 cross-pollination ("Forklift-certified loader" ↔ "Hazmat warehouse worker") is legitimate — these are genuinely similar staffing queries and the judge ranks both directions as plausible. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
118 lines
7.3 KiB
Markdown
118 lines
7.3 KiB
Markdown
# Playbook-Lift Reality Test — Run 004
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**Generated:** 2026-04-30T12:23:36.594892386Z
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**Judge:** `qwen2.5:latest` (Ollama, resolved from env JUDGE_MODEL=qwen2.5:latest)
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**Corpora:** `workers,ethereal_workers`
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**Workers limit:** 5000
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**Queries:** `tests/reality/playbook_lift_queries.txt` (21 executed)
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**K per pass:** 10
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**Paraphrase pass:** ENABLED
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**Evidence:** `reports/reality-tests/playbook_lift_004.json`
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---
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## Headline
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| Metric | Value |
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|---|---:|
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| Total queries run | 21 |
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| Cold-pass discoveries (judge-best ≠ top-1) | 8 |
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| Warm-pass lifts (recorded playbook → top-1) | 6 |
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| No change (judge-best already top-1, no playbook needed) | 15 |
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| Playbook boosts triggered (warm pass) | 8 |
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| Mean Δ top-1 distance (warm − cold) | -0.070719235 |
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| **Paraphrase pass — recorded answer at rank 0 (top-1)** | **6 / 8** |
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| Paraphrase pass — recorded answer at any rank in top-K | 6 / 8 |
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**Verbatim lift rate:** 6 of 8 discoveries became top-1 after warm pass.
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---
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## Per-query results
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| # | Query | Cold top-1 | Cold judge-best (rank/rating) | Recorded? | Warm top-1 | Judge-best warm rank | Lift |
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|---|---|---|---|---|---|---|---|
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| 1 | Forklift operator with OSHA-30, warehouse experience, day sh | e-4983 | 1/4 | ✓ e-5729 | e-5729 | 0 | **YES** |
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| 2 | OSHA-30 certified forklift operator in Wisconsin, cold stora | e-868 | 9/3 | — | e-7308 | -1 | no |
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| 3 | Production worker with confined-space cert and hazmat traini | w-4583 | 1/2 | — | w-1231 | 2 | no |
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| 4 | CDL Class A driver, clean record, willing to do regional 4-d | w-3272 | 0/1 | — | w-3272 | 0 | no |
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| 5 | Warehouse lead with current OSHA-30 certification, NOT OSHA- | w-2356 | 3/2 | — | w-2356 | 3 | no |
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| 6 | Forklift-certified loader, certification must be active, dis | e-3940 | 3/4 | ✓ w-330 | e-7453 | 1 | no |
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| 7 | Hazmat-certified warehouse worker comfortable with cold stor | w-4633 | 4/4 | ✓ e-7453 | w-330 | 1 | no |
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| 8 | Bilingual production worker with team-lead experience and tr | w-2983 | 0/4 | — | w-2983 | 0 | no |
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| 9 | Inventory specialist with confined-space cert and compliance | w-3037 | 7/4 | ✓ w-1231 | w-1231 | 0 | **YES** |
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| 10 | Warehouse worker who can run inventory cycles and lead a sma | e-6649 | 1/4 | ✓ w-4113 | w-4113 | 0 | **YES** |
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| 11 | Production line worker comfortable filling in as line superv | w-1010 | 3/4 | ✓ w-1153 | w-1153 | 0 | **YES** |
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| 12 | Customer service rep willing to cross-train into dispatch or | e-6474 | 1/2 | — | e-6474 | 1 | no |
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| 13 | Reliable production line lead with strong attendance and lea | e-4284 | 0/3 | — | e-4284 | 0 | no |
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| 14 | Highly responsive forklift operator available for last-minut | e-285 | 4/4 | ✓ e-7308 | e-7308 | 0 | **YES** |
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| 15 | Engaged warehouse associate with strong safety compliance re | e-8404 | 5/4 | ✓ w-3242 | w-3242 | 0 | **YES** |
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| 16 | CDL-A driver based in IL or WI, willing to run regional 4-da | w-3257 | 4/2 | — | w-3257 | 4 | no |
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| 17 | Bilingual customer service rep in Indianapolis or Cincinnati | w-1387 | 0/1 | — | w-1387 | 0 | no |
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| 18 | Production supervisor open to Midwest relocation for permane | e-7478 | 1/2 | — | e-7478 | 1 | no |
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| 19 | Dental hygienist with three years experience, Indianapolis a | e-2544 | 0/1 | — | e-2544 | 0 | no |
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| 20 | Registered nurse with ICU experience, willing to take per-di | w-419 | 0/1 | — | w-419 | 0 | no |
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| 21 | Software engineer with React and TypeScript, three years exp | w-334 | 0/1 | — | w-334 | 0 | no |
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---
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## Paraphrase pass — does the playbook help similar-but-different queries?
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For each query whose Pass 1 cold pass recorded a playbook entry, the
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judge model rephrased the query, and the rephrased version was sent
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through warm matrix.search. The recorded answer ID's rank in those
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results tests whether cosine on the embedded paraphrase finds the
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recorded query's vector.
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| # | Original (≤40c) | Paraphrase (≤60c) | Recorded answer | Paraphrase top-1 | Recorded rank | Paraphrase lift |
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|---|---|---|---|---|---|---|
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| 1 | Forklift operator with OSHA-30, warehous | Seeking forklift operator certified in OSHA-30, with backgro | e-5729 | e-5729 | 0 | **YES** |
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| 6 | Forklift-certified loader, certification | Loader with active forklift certification, separate from reg | w-330 | w-330 | 0 | **YES** |
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| 7 | Hazmat-certified warehouse worker comfor | Warehouse worker with Hazmat certification and experience in | e-7453 | e-7453 | 0 | **YES** |
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| 9 | Inventory specialist with confined-space | Individual needed for inventory management with certificatio | w-1231 | w-987 | -1 | no |
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| 10 | Warehouse worker who can run inventory c | Seeking a warehouse worker capable of conducting inventory c | w-4113 | w-4113 | 0 | **YES** |
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| 11 | Production line worker comfortable filli | Seeking a production line worker capable of temporarily step | w-1153 | w-1153 | 0 | **YES** |
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| 14 | Highly responsive forklift operator avai | Available for urgent forklift operation shifts requiring imm | e-7308 | e-7308 | 0 | **YES** |
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| 15 | Engaged warehouse associate with strong | Warehouse associate currently engaged with a robust history | w-3242 | e-2615 | -1 | no |
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---
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## Honesty caveats
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1. **Judge IS the ground truth proxy.** Without human-labeled relevance, the LLM
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judge's verdict is what defines "best." If `qwen2.5:latest` rates badly,
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the lift number is meaningless. To validate the judge itself, sample 5–10
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verdicts manually and check agreement.
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2. **Score-1.0 boost = distance halved.** Playbook math is
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`distance' = distance × (1 - 0.5 × score)`. Lift requires the judge-best
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result's pre-boost distance to be ≤ 2× the cold top-1's distance, otherwise
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even halving doesn't promote it. Tight clusters → little visible lift.
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3. **Verbatim vs paraphrase.** The verbatim lift rate (above) is the cheap
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case — same query, recorded playbook, expected boost. The paraphrase
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pass (when enabled) is the actual learning property: similar-but-different
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queries hitting a recorded playbook. Compare verbatim and paraphrase
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lift rates — paraphrase should be lower (semantic-distance gates some
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playbook hits) but non-zero is the meaningful signal.
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4. **Multi-corpus skew.** Default corpora=`workers,ethereal_workers` — if all judge-best
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results land in one corpus, the matrix layer's purpose isn't being tested.
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Check per-corpus distribution in the JSON.
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5. **Judge resolution.** This run used `qwen2.5:latest` from
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env JUDGE_MODEL=qwen2.5:latest.
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Bumping the judge for run #N+1 means editing one line in lakehouse.toml.
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6. **Paraphrase generation also uses the judge.** The same model that rates
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relevance also rephrases queries. A judge that's bad at rating staffing
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queries is probably also bad at rephrasing them. Worth sanity-checking
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a sample of `paraphrase_query` values in the JSON before trusting the
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paraphrase lift number.
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## Next moves
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- If lift rate ≥ 50% of discoveries: matrix layer + playbook is doing real
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work. Move to paraphrase queries + tag-based boost (currently ignored).
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- If lift rate < 20%: investigate why — judge variance, distance gap too
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wide, or playbook math too gentle. The score=1.0 / 0.5× formula may need
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retuning.
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- If discovery rate (cold judge-best ≠ top-1) is itself low: cosine is
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already close to optimal on this query distribution. Either the corpus
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is too narrow or the queries are too easy.
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