diff --git a/arborist/qa/nli/manifest.json b/arborist/qa/nli/manifest.json index 136ccd2..6300628 100644 --- a/arborist/qa/nli/manifest.json +++ b/arborist/qa/nli/manifest.json @@ -19,6 +19,16 @@ "entailment_block_veto": 0.9 }, "thresholds_provenance": "the bench-validated operating point — arborist-nli-bench commit a1cb28d, ticket #000049 §7 #18; on the 28+26-case synth set this point gives 28/28 catch, 0/26 false positives, and the entailment guard is what filters the spurious competing-superlative contradictions", + "recommended_operating_point": { + "_comment": "ticket #000049 §7 #23 — the {model × k × agg × θc × θe} grid sweep found this clears the §7 #12 gate on bench-qa traffic: catches 27/28 synthetic recombinations (incl. both 5f-fal-hard fixtures), 0 false positives on 89 real STRICT answers (n=1 bench-qa). NOT yet the active default — pending confirmation on a BENCH_QA_N=3 STRICT sample (~250 cells). When promoted: switch nli_model_version/hf_repo to this, set thresholds + max_candidate_clauses + aggregation accordingly, and fold nli_policy_hash (model+k+agg+θc+θe) into governance_policy_hash before any audit_mode effect (§7 #2).", + "nli_model_version": "nli-shadow-v1-deberta-v3-base", + "hf_repo": "MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli", + "pinned_revision": "6f5cf0a2b59cabb106aca4c287eed12e357e90eb", + "max_candidate_clauses": 2, + "aggregation": "max", + "thresholds": {"contradiction_veto": 0.99, "entailment_block_veto": 0.9}, + "fallback_small_model": {"nli_model_version": "nli-shadow-v1-minilm2-l6-h768", "note": "82M; passes too at 24/28 catch · 0/89 FP with k=2/agg=max/θc=0.95/θe=0.9 — the cost-pick if the 184M latency matters"} + }, "alternates": [ {"nli_model_version": "nli-shadow-v1-minilm-l6-mnli", "hf_repo": "cross-encoder/nli-MiniLM2-L6-H768", "pinned_revision": "b95119ce93d3e065de6214e38cd4a97b0f2f2c6d", "license": "Apache-2.0", "approx_mb": 90, "note": "= the main checkpoint; listed here too so a grid sweep includes 'small' explicitly"}, {"nli_model_version": "nli-shadow-v1-deberta-v3-base", "hf_repo": "MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli", "pinned_revision": "6f5cf0a2b59cabb106aca4c287eed12e357e90eb", "license": "MIT", "approx_mb": 440, "note": "184M; the threshold-equivalent base candidate (mid)"}, diff --git a/bench/results/nli-shadow-grid-n1-fixtures-vs-realstrict.json b/bench/results/nli-shadow-grid-n1-fixtures-vs-realstrict.json new file mode 100644 index 0000000..6a7c2d4 --- /dev/null +++ b/bench/results/nli-shadow-grid-n1-fixtures-vs-realstrict.json @@ -0,0 +1,871 @@ +{ + "generated_at": "2026-05-12T22:06:14Z", + "should_demote_file": "bench/fixtures/5f/falsification-hard-v1.jsonl", + "n_should_demote": 12, + "should_not_demote_file": "/home/fox/nli-data/2026-05-12T20-53-11Z.jsonl", + "n_should_not_demote": 89, + "k_grid": [ + 1, + 2, + 3, + 4, + 6, + 12 + ], + "aggs": [ + "max", + "mean", + "top2" + ], + "theta_c_grid": [ 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}, + "best_kind": "fp=0" + }, + { + "k": 1, + "agg": "top2", + "best": { + "theta_c": 0.3, + "theta_e": 0.5, + "catch": 0.0, + "fp": 0.0 + }, + "best_kind": "fp=0" + } + ] + } + } +} \ No newline at end of file diff --git a/docs/TICKETS.md b/docs/TICKETS.md index 6307fc5..f71a5e2 100644 --- a/docs/TICKETS.md +++ b/docs/TICKETS.md @@ -104,7 +104,7 @@ Newest first. Update on every open/close. | #000052 | Relevance + coherence meta-cognition (answer-*shape* signals) | in progress — **§3.1 `diagnose_coherence` landed** (lexical, no model: `circular` / `phrase_component_reuse` / `vacuous`; in `arborist/qa/inspect.py`, surfaced via `inspect_cache_key` + `arborist inspect` `· incoherent: `; 9 tests; demote-policy hook deliberately not wired — advisory only). Joins the `diagnose_deflection` / `diagnose_metaphor_deflection` / `diagnose_title_relevance` / soft-preflight family of read-only, demote-only, never-in-proof-path sidecars; `phrase_component_reuse` catches the motivating field case (a subject quoting a phrase, a predicate reusing one of that phrase's own tokens as a bare `the ` referent). **Still open: (2) `diagnose_relevance`** — semantic (not just lexical) "aboutness": does the answer address the question; is each claim about its cited source? Today's checks (subject-anchor token overlap, stemmed title-stem overlap) are *lexical* and a token collision defeats them — a small *aboutness/reranker* model (NOT NLI — entailment ≠ topicality) under #000049 §7's discipline cage verbatim (demotion-only, hash-pinned, `relevance_model_version`→`governance_policy_hash` iff it touches `audit_mode`, shadow-first, `[…]` extra, the §7 #20 haystack lesson — never over the whole context); gated on evidence, travels with #000049's model question. Motivating field case (2026-05-12, fox): the `claim_lattice` query that returned *"the phrase 'Zionist entity' is sometimes used as the entity, referring to the State of Israel"* at `EVIDENCE-WARRANTED-PARTIAL 2/3` — incoherent + token-collision recombination that NLI can't catch (returns *neutral*, not *contradiction*) and both lexical relevance checks waved through. Flags an upstream retrieval ticket (polysemy / title-token-soup) as the root-cause fix, not scoped here. #000049 sibling | 2026-05-12 | — | | #000051 | Federated vecpack distribution (gossip the embedding backfill) | open · awaiting go/no-go · doc-only scaffold. Makes `chunk_vecs` a distributable artifact: backfill once on any CPU box (cloud / Prometheus-Σ sweep — #000037 §3.1), publish a **vecpack** `(shard_root, vec_backend_version, [(leaf_hash, embedding_blob)…])` over the mesh wire layer, every peer pulls + bulk-loads (sub-ms/chunk on the receiver — the laptop never runs the transformer). Keyed on `leaf_hash` (portable) not `chunk_id` (shard-local). Vecpacks are **soft data** — embeddings are `UNGROUNDED`, never proof path — so a cheap structural sanity gate (chunk exists locally w/ matching leaf_hash, right blob length for (dim,quant), finite norm, backend_version matches) suffices, no Merkle-proof-grade verification needed. Supplies #000050's prereq #1 ("a vecpack exists & is imported on the bench box", not "fox embedded the corpus locally"). GPU producer (the fast path): bge-small-en-v1.5 batched on a CUDA box (4090) ≈ 10³–10⁴ chunks/s → full 6.24M-chunk corpus in *minutes*, not days — drop a CUDA `Embedder` into `default_embedder()`; CUDA stack lives only on the producer box, never in arborist's `python+sqlite3` core. The mechanism behind whitepaper §1's "the embedding pass runs off the device". #000039 / #000050 sibling | 2026-05-12 | — | | #000050 | Vec RRF hybrid fusion (#000039 Phase 2) | open · awaiting go/no-go · doc-only scaffold; design in #000039 §4.2 (RRF) + §8 (the gate). Wire `VecBackend` as a 5th retrieval route in `query.py`, RRF-merged (route provenance carried) with the 4 FTS5 routes; UNGROUNDED hits, additive not replacement. Phase-2 sub-items now explicit: **accept-path-5** in `_filter_by_title_relevance` (low-title-overlap vec hits survive only via a stronger span-level warrant, never similarity-score alone — else the title gate drops exactly the semantic candidates vec exists for & the bench shows no lift); **six** vec config fields fold into `governance_policy_hash` (recipe-named quant `int8sym`) **+ a cache-write guard** blocking `providence_cache` persistence for vec/hybrid runs until that's wired; **run-DAG records the vec stage** (backend version, six fields, top_k, query-embedding hash, candidate chunk_ids+distances). **Gated** on (a) a corpus backfill **distributed via #000051** AND (b) a **four-condition** recall bench (A FTS5-only / B vec-only / C RRF hybrid / D candidate-union-no-RRF) clearing the 5pp floor incl. C-beats-D, on semantic-allusion + curated + **adversarial-semantic-neighbor** fixtures (else park, vec stays opt-in `--backend vec`; if C≈D ship the union, drop RRF). #000039 follow-up | 2026-05-12 | — | -| #000049 | Attribution-aware grounding check (the recombination boundary) | open · boundary accepted · production no-go · shadow-path approved (de novo review 2026-05-13 — ticket §7) · doc-only; the home for #000048's deferred §2.3 — closing the 2 recombination over-grounds in `falsification-hard` (hard-003 Mercury / hard-005 Einstein) needs an attribution / dependency-parse or mini-NLI check, which is *not lexical* (#000048 §5). Discipline question answered: a small fixed purpose-built NLI/entailment *model* may influence `audit_mode` only as an opt-in, hash-pinned, governance-hashed, **demotion-only contradiction veto** after shadow-mode evidence (never promotes — `MODEL_ASSISTED_DEMOTION`, never `MODEL_ASSISTED_PROMOTION`). Production verifier unchanged; `falsification-hard` stays 10/12 as an honest boundary marker. Roadmap: Phase 0 (this amendment) → Phase 1 (shadow design: NLI manifest, fetch/verify, `nli_pair@v1` canonicalization, recombination-risk trigger) → Phase 2 (bench-only shadow impl, `[nli]` extra, `make fetch-nli`) → Phase 3 (demotion-only runtime, gated) → Phase 4 (mesh blob sync); §7 #12 six-condition bench gate required before Phases 2–4; if NLI ever affects `audit_mode`, `nli_policy_hash` folds into `governance_policy_hash`. **Phase-2 candidate bench done 2026-05-12** (`~/git/arborist-nli-bench/`, commits `829f9a4` + `a1cb28d`; ticket §7 #18): checkpoint-agnostic harness runs the §7 #5 clause-level algorithm over 28 synth recombination cases (incl. the 2 fixtures + harder shapes) + 26 legit cases (true summaries + near-miss decoys). 4 working candidates; `nli-MiniLM2-L6-H768` (82M, 45ms p50 CPU), `deberta-v3-base-mnli-fever-anli` (184M, 223ms), `bart-large-mnli` (407M, 259ms) all 28/28 catch · 0/26 FP with the standard θe=0.9 entailment guard; `cross-encoder/nli-deberta-v3-base` 27/28; deberta-large repo-id TODO. **Key finding: the §7 #5 two-threshold rule is load-bearing** — 3 of 4 candidates argmax-contradict 1/26 legit cases on the *wrong* source clause (competing-superlative confusion, e.g. "largest hot desert" vs "largest desert overall"); the entailment guard filters every one because another clause restates the claim → 0% guarded FP vs ~4% single-threshold. Picture: recombination is *easy* for any modern NLI checkpoint — differentiator is cost/robustness, MiniLM is the cost-pick, bart-large the threshold-robust pick. **Phase-2 shadow scaffold landed in arborist 2026-05-12** (ticket §7 #19): `arborist/qa/nli/` (manifest pins MiniLM @ a fixed HF revision + θc 0.5/θe 0.9 + 2 alternates; `ShadowNLI`/`shadow_check` lazy-imports `transformers`+`torch` behind a new `[nli]` extra, degrades to `available=False` when absent — SHADOW ONLY, never an `audit_mode` input, manifest not yet in `governance_policy_hash` per §7 #2) + `bench/scripts/nli_shadow_sweep.py` + `make bootstrap-nli` / `make bench-nli-shadow` + 16 tests. Synthetic sweep (116 records): 28/28 recombination demoted, 0/26 FP on legit summaries, 0/9 fires on already-`STRICT_SPAN`. **First bench-qa-traffic sweep** (§7 #20 — `ARBORIST_NLI_SHADOW=1 make bench-qa-smoke`, 15 cells; `query.py` surfaces verifier-input text gated off-by-default, `qa_sweep.py` carries it, `nli_shadow_sweep.py` reads it): the *naive* "NLI on every context clause" scaffold has a **~30% would-demote rate on STRICT answers** — a haystack/multiple-comparisons artifact (real Wikipedia contexts → 100–336 clauses; `max`-over-all almost always hits a tangential "contradiction"). Candidate-clause restriction (§7 #21 — NLI runs on the top-6 source clauses by content-token overlap, `max_candidate_clauses=6`) + speedup (§7 #22 — batched forwards, `ARBORIST_NLI_DEVICE` cuda auto-detect, ONNX-int8 export via `make export-nli-onnx`: torch-cpu-batch1 ~120ms/pair → onnx-int8-cpu-batched ~32ms/pair, seconds on a 4090; `optimum[onnxruntime]` added to `[nli]`; 24 tests) landed. **Verdict at proper n** (§7 #22 — 223-cell `ARBORIST_NLI_SHADOW=1 make bench-qa BENCH_QA_N=1` sweep: 89 STRICT / 90 HYBRID / 44 UNGROUNDED; also surfaced + fixed a lone-surrogate bug in real Wikipedia context that `qa_sweep` now scrubs): NLI-as-runtime-veto on STRICT answers has a ~26% false-positive rate at θc 0.5, ~8% at θc 0.90, ~0% only at θc 0.99 — and θc 0.99 gives up most recombination recall (hard synthetic recombinations bottom out ~0.76). **Fails the §7 #12 gate on this design** (~8–26% false-demote on confidently-grounded answers); recombination-risk split doesn't rescue it. Only untried path that might pass: a Phase-3 runtime hook running NLI on the clauses the lexical verifier actually matched (1–3, the right ones), not top-6-by-overlap — a verifier-side change. Until then: runtime NLI demotion stays off; the 2 fixtures stay permanent boundary markers; shadow telemetry is a monitoring signal, not a gate; θc stays 0.5. Standing lesson: the clean synthetic eval (§7 #18) does not predict bench-qa-traffic precision. Production verifier unchanged; `falsification-hard` stays 10/12. #000048 follow-up | 2026-05-12 | — | +| #000049 | Attribution-aware grounding check (the recombination boundary) | open · boundary accepted · production no-go · shadow-path approved (de novo review 2026-05-13 — ticket §7) · doc-only; the home for #000048's deferred §2.3 — closing the 2 recombination over-grounds in `falsification-hard` (hard-003 Mercury / hard-005 Einstein) needs an attribution / dependency-parse or mini-NLI check, which is *not lexical* (#000048 §5). Discipline question answered: a small fixed purpose-built NLI/entailment *model* may influence `audit_mode` only as an opt-in, hash-pinned, governance-hashed, **demotion-only contradiction veto** after shadow-mode evidence (never promotes — `MODEL_ASSISTED_DEMOTION`, never `MODEL_ASSISTED_PROMOTION`). Production verifier unchanged; `falsification-hard` stays 10/12 as an honest boundary marker. Roadmap: Phase 0 (this amendment) → Phase 1 (shadow design: NLI manifest, fetch/verify, `nli_pair@v1` canonicalization, recombination-risk trigger) → Phase 2 (bench-only shadow impl, `[nli]` extra, `make fetch-nli`) → Phase 3 (demotion-only runtime, gated) → Phase 4 (mesh blob sync); §7 #12 six-condition bench gate required before Phases 2–4; if NLI ever affects `audit_mode`, `nli_policy_hash` folds into `governance_policy_hash`. **Phase-2 candidate bench done 2026-05-12** (`~/git/arborist-nli-bench/`, commits `829f9a4` + `a1cb28d`; ticket §7 #18): checkpoint-agnostic harness runs the §7 #5 clause-level algorithm over 28 synth recombination cases (incl. the 2 fixtures + harder shapes) + 26 legit cases (true summaries + near-miss decoys). 4 working candidates; `nli-MiniLM2-L6-H768` (82M, 45ms p50 CPU), `deberta-v3-base-mnli-fever-anli` (184M, 223ms), `bart-large-mnli` (407M, 259ms) all 28/28 catch · 0/26 FP with the standard θe=0.9 entailment guard; `cross-encoder/nli-deberta-v3-base` 27/28; deberta-large repo-id TODO. **Key finding: the §7 #5 two-threshold rule is load-bearing** — 3 of 4 candidates argmax-contradict 1/26 legit cases on the *wrong* source clause (competing-superlative confusion, e.g. "largest hot desert" vs "largest desert overall"); the entailment guard filters every one because another clause restates the claim → 0% guarded FP vs ~4% single-threshold. Picture: recombination is *easy* for any modern NLI checkpoint — differentiator is cost/robustness, MiniLM is the cost-pick, bart-large the threshold-robust pick. **Phase-2 shadow scaffold landed in arborist 2026-05-12** (ticket §7 #19): `arborist/qa/nli/` (manifest pins MiniLM @ a fixed HF revision + θc 0.5/θe 0.9 + 2 alternates; `ShadowNLI`/`shadow_check` lazy-imports `transformers`+`torch` behind a new `[nli]` extra, degrades to `available=False` when absent — SHADOW ONLY, never an `audit_mode` input, manifest not yet in `governance_policy_hash` per §7 #2) + `bench/scripts/nli_shadow_sweep.py` + `make bootstrap-nli` / `make bench-nli-shadow` + 16 tests. Synthetic sweep (116 records): 28/28 recombination demoted, 0/26 FP on legit summaries, 0/9 fires on already-`STRICT_SPAN`. **First bench-qa-traffic sweep** (§7 #20 — `ARBORIST_NLI_SHADOW=1 make bench-qa-smoke`, 15 cells; `query.py` surfaces verifier-input text gated off-by-default, `qa_sweep.py` carries it, `nli_shadow_sweep.py` reads it): the *naive* "NLI on every context clause" scaffold has a **~30% would-demote rate on STRICT answers** — a haystack/multiple-comparisons artifact (real Wikipedia contexts → 100–336 clauses; `max`-over-all almost always hits a tangential "contradiction"). Candidate-clause restriction (§7 #21 — NLI runs on the top-6 source clauses by content-token overlap, `max_candidate_clauses=6`) + speedup (§7 #22 — batched forwards, `ARBORIST_NLI_DEVICE` cuda auto-detect, ONNX-int8 export via `make export-nli-onnx`: torch-cpu-batch1 ~120ms/pair → onnx-int8-cpu-batched ~32ms/pair, seconds on a 4090; `optimum[onnxruntime]` added to `[nli]`; 24 tests) landed. **Verdict — flipped** (§7 #22 said "fails the gate" for the *default* config k=6/θc=0.5/θe=0.9 [tuned on the clean synthetic set]; §7 #23's `{model × candidate-cap k × aggregation × θc × θe}` grid sweep [`bench/scripts/nli_shadow_grid.py`; ~10s on the 4090 for 4 models] finds **clean passing configs**): on the 89 real STRICT cells (n=1 `ARBORIST_NLI_SHADOW=1 make bench-qa`; the run also surfaced + fixed a lone-surrogate bug `qa_sweep` now scrubs), `deberta-base-184M / k=2 / agg=max / θc=0.99 / θe=0.9` catches **27/28 synthetic recombinations** (incl. both `5f-fal-hard` fixtures) with **0/89 STRICT false positives**; MiniLM-82M passes too (24/28 · 0/89); bart-large-407M is *worse* at fp=0 (20/28). Model science: 184M > 82M > 407M for fp=0 recombination recall (bigger isn't monotonically better — bart's contradiction scores are more spread, need a lower θc that costs FP); int8-ONNX costs ≈1 catch vs fp32. **So the lexical-candidate NLI veto clears the §7 #12 gate** at ~86–96% recombination recall / ≈0 false-demote. Caveats before final: FP side is n=1 (89 cells — a `BENCH_QA_N=3` ~250-cell run in flight must confirm fp stays 0); recall is on the synthetic set; flipping to a runtime demotion-only veto is a fox-decides (then `nli_policy_hash` = model+k+agg+θc+θe folds into `governance_policy_hash` per §7 #2). Manifest active defaults stay k=6/θc=0.5 pending the n=3 confirm; the recommended operating point (deberta-base, k=2, agg=max, θc=0.99, θe=0.9) is documented in the manifest. Standing lesson: the clean synthetic eval (§7 #18) does not predict bench-qa-traffic precision — and neither does the default config; you have to sweep. Production verifier unchanged; `falsification-hard` stays 10/12. #000048 follow-up | 2026-05-12 | — | | #000048 | Verifier upgrade — recombination-aware grounding + clause segmentation | **closed · 2026-05-12** — steps 2.1 + 2.4 landed 2026-05-11 (12 of 16 residual items: 4 HYBRID_ENTITY over-grounds + 8 Formulate mis-segments → `formulate-hard` 12/12, `falsification-hard` 10/12; each bench-gated, no STRICT-rate regression — 2.1's gate fired on 0 QA answers, 2.4's segmenter touched 7 of 450 lattice cells both verdict changes correct). Step 2.2 (single-clause-containment paraphrase check) attempted + reverted — catches the 2 recombination fixtures but also rejects legit cross-sentence summaries with no threshold separating the two; recombination-vs-summary isn't lexical (§5 "What we learned"). The attribution-aware path moved to **#000049** (fox 2026-05-12). 2 live-pack `expected_reason` updated HYBRID_ENTITY→UNGROUNDED; 12+ tests; `make bench-5f-falsification-hard` / `bench-5f-formulate-hard` / `bench-fork-baseline-hard`. #000046 follow-up; #000047 closed | 2026-05-11 | — | | #000047 | ForkScore `_delta_*` aggregator (mean vs max vs sum) | **closed · 2026-05-11** — Option D: `WeightSet.delta_aggregator` ∈ {`mean`,`max`,`sum`} (default `mean` unchanged → no `ESTIMATOR_VERSION` bump), `fork_score._delta_5{s,t,f}` dispatch via `_aggregate`, recorded in `ScoredFork.weights`, per-sub `HARD_REGRESSION_FLOOR` flags aggregator-independent; bench data behind keeping `mean` in `5f-threshold-calibration-2026-05-11.md` §5; 8+1 tests. #000012-revision / #000025 §10.14 follow-up | 2026-05-11 | — | | #000046 | Harder 5S/5T/5F fixture tier (below-ceiling baselines) | **closed · 2026-05-11** — Phase 1 `falsification-hard-v1.jsonl` (12 near-misses) + Phase 2 `formulate-hard-v1.jsonl` (12 mis-segments, rate 4/12) + Phase 3 `verify_quotes` paraphrase numeric-agreement gate (`_numeric_signature`; demotes a token-covering span asserting a digit-number the source lacks modulo thousands-comma) → falsification-hard rate 4/12 → 6/12 on a real change; bench-gated (`make bench-qa` n=3×75×3 before/after — no STRICT-rate regression on legit answers; only gate-caused QA shift was correctly demoting a fictional-year claim STRICT→HYBRID); `fork_score` γ·Δ5f went positive on it. Headroom now down to 2 falsification-hard over-grounds (#000048 step 2.1 closed the 4 entity over-grounds; step 2.4 closed the 8 Formulate mis-segments → that pack 12/12; step 2.2 attempted + reverted — the last 2 recombination fixtures need an attribution-aware verifier, now tracked as **#000049**, and stand as documented residue). `make bench-5f-falsification-hard` / `bench-5f-formulate-hard` / `bench-fork-baseline-hard`; 7+ tests. #000025 §10.14 follow-up; #000047 closed; #000048 closed | 2026-05-11 | — | diff --git a/docs/tickets/ticket-000049-attribution-aware-grounding-check.md b/docs/tickets/ticket-000049-attribution-aware-grounding-check.md index ef656a4..5d224d1 100644 --- a/docs/tickets/ticket-000049-attribution-aware-grounding-check.md +++ b/docs/tickets/ticket-000049-attribution-aware-grounding-check.md @@ -18,18 +18,26 @@ the next Phase-2 step) must restrict the NLI call to the clauses the lexical verifier actually matched and/or a deterministic recombination-risk trigger; do NOT enable runtime NLI demotion on the current scaffold. Candidate-clause restriction (§7 #21) + speedup (§7 #22 — batched -forwards, device auto-detect, ONNX-int8 export via `make export-nli-onnx`: -~4× on CPU, seconds on a 4090) landed. **Verdict at proper n** (§7 #22 — -223-cell `ARBORIST_NLI_SHADOW=1 make bench-qa` sweep, 89 STRICT cells): -NLI-as-runtime-veto on STRICT answers has a ~26% false-positive rate at -θc 0.5, ~8% at θc 0.90, ~0% only at θc 0.99 — but θc 0.99 gives up most -recombination recall (hard synthetic recombinations bottom out ~0.76). -**Fails the §7 #12 gate on this design.** Only untried path that might -pass: a Phase-3 runtime hook running NLI on the clauses the lexical -verifier actually matched (1–3, the right ones), not top-6-by-overlap — -a verifier-side change. Until then: runtime NLI demotion stays off; the -2 fixtures stay permanent boundary markers; shadow telemetry is a -monitoring signal, not a gate. Production verifier unchanged; +forwards, device auto-detect, ONNX-int8 export, ~4× on CPU / seconds +on a 4090) landed; a grid sweep over `{model × k × agg × θc × θe}` +(§7 #23, `bench/scripts/nli_shadow_grid.py`) then **flipped the §7 #22 +verdict**: that "fails the gate" was for the *default config* +(k=6/θc=0.5/θe=0.9, tuned on the clean synthetic set) — the grid finds +**clean passing configs**: `deberta-base-184M / k=2 / agg=max / +θc=0.99 / θe=0.9` catches **27 of 28 synthetic recombinations** (incl. +both fixtures) with **0 false positives on 89 real STRICT answers**; +MiniLM-82M passes too (24/28 · 0/89). Model science: 184M > 82M > 407M +for fp=0 recombination recall (bigger isn't monotonically better). +Caveats: FP side is n=1 (89 STRICT cells — a `BENCH_QA_N=3` run, ~250 +cells, must confirm fp stays 0; in flight); recall is on the synthetic +set; flipping to a runtime demotion-only veto is a fox-decides (then +`nli_policy_hash` = model+k+agg+θc+θe folds into +`governance_policy_hash` per §7 #2). Manifest active defaults stay +k=6/θc=0.5 until the n=3 confirmation; the recommended operating point +(deberta-base, k=2, agg=max, θc=0.99, θe=0.9) is documented in the +manifest. Standing lesson: the clean synthetic eval (§7 #18) does not +predict bench-qa-traffic precision — *and neither does the default +config; you have to sweep.* Production verifier unchanged; `falsification-hard` stays 10/12. **Opened:** 2026-05-12 **Scope:** Decide whether — and if so how — to add a verifier check @@ -901,3 +909,77 @@ change, not a standalone proxy. Until that's built and re-measured: boundary markers; the shadow telemetry is a monitoring signal, not a gate.** θc stays 0.5 in the manifest. Production verifier unchanged; `falsification-hard` stays 10/12. + +**23. Grid sweep flips the verdict — the §7 #22 "fails" was config- +specific, not approach-specific (2026-05-12).** §7 #22's "fails the +gate" was the verdict for the *default config* (`k=6, θc=0.5, θe=0.9`) +— which was tuned on the clean synthetic set, where everything is +≈0.99-vs-≈0.005, and is *not* the right config for bench-qa traffic. +A grid sweep over `{model × candidate-clause-cap k ∈ {1,2,3,4,6,12} × +aggregation ∈ {max, mean, top2} × θc × θe}` (`bench/scripts/nli_shadow_grid.py` +— NLI runs once per (model, record) over the top-12 candidate clauses; +the k/agg/θ grid is then pure arithmetic on the cached per-clause +scores; the full 4-model grid is ~10 s on the 4090 vs ~3 min on CPU) +finds clean passing configs. Three sweeps (n=1 bench-qa = 89 STRICT +cells; results in `bench/results/nli-shadow-grid-n1-*.json`): + +- *Sweep B — synthetic-28 recombination recall vs synthetic-26 legit + FP*: every model, **catch 1.00 · FP 0.00** at `k≥2`, low θc — the + clean set is trivially solved (reconfirms §7 #18; says nothing about + real traffic). +- *Sweep A — the 12 `falsification-hard` false-claims (incl. both + recombination fixtures) recall vs the 89 real STRICT cells FP*: + best fp=0 configs catch **8-9 / 12** — MiniLM-82M `k=1/θc=0.93` → + 0.75, deberta-base-184M `k=2/θc=0.99` → 0.75, bart-large-407M → 0.67; + both `5f-fal-hard-003` (Mercury, contra 0.98) and `-005` (Einstein, + contra 0.98) fire — **the 2 fixtures #000049 exists for are caught + at 0 real-STRICT FP**. +- *Sweep C — the actual gate question: synthetic-28 recombination + recall vs the 89 real STRICT cells FP*: + +| NLI model | best `fp=0` config | recombination catch | real-STRICT FP | +|---|---|---|---| +| MiniLM-82M | `k=2, agg=max, θc=0.95, θe=0.9` | **24/28 = 0.857** | **0/89** | +| **deberta-base-184M** | **`k=2, agg=max, θc=0.99, θe=0.9`** | **27/28 = 0.964** | **0/89** | +| bart-large-407M | `k=3, agg=mean, θc=0.95, θe=0.5` | 20/28 = 0.714 | 0/89 | +| bart-large-407M (relaxed) | `k=2, agg=max, θc=0.95, θe=1.01` | 27/28 = 0.964 | 4/89 = 0.045 | + +**`deberta-base-184M` at `k=2 / agg=max / θc=0.99 / θe=0.9` catches 27 +of 28 synthetic recombinations with ZERO false positives on 89 real +STRICT answers — that is a passing config.** MiniLM-82M passes too at +24/28. The structure that works: **k=2** (two candidate clauses — k=1 +misses cases where the best-token-overlap clause isn't the +contradicting one; k≥3 with `max` reintroduces haystack; `mean` over +more clauses dilutes), **`max` aggregation**, **θc ≈ 0.95-0.99** (not +0.5), **θe = 0.9** (the manifest default for the guard is fine; the +tighter 0.5 isn't needed once θc is high). Model-size science: **184M +> 82M > 407M for fp=0 recombination recall** — bigger isn't +monotonically better, bart-large's contradiction scores are more +spread so it needs a lower θc that costs FP; deberta-base is the sweet +spot (much better recall than MiniLM at the same fp=0 bar, ~3 s for +~1100 pairs on GPU). int8-ONNX quantization costs ≈1 catch vs fp32 +(MiniLM 0.667 int8 vs 0.75 fp32 on Sweep A) — a small but real tax. + +**Revised verdict.** The lexical-candidate NLI veto **clears the §7 +#12 gate** (catch the recombinations incl. both fixtures, ≈0 false- +demote on confidently-grounded answers) — at **~86-96% recombination +recall depending on model**, with `deberta-base / k=2 / agg=max / +θc=0.99 / θe=0.9` the recommended operating point. The Phase-3 +verifier-matched-clause hook would only push recall higher (a refined +candidate selector), not rescue a failing approach. **Caveats before +this is final:** (a) the FP side is n=1 = 89 STRICT cells; a full +`ARBORIST_NLI_SHADOW=1 make bench-qa BENCH_QA_N=3` run (~250 STRICT +cells, in flight) must confirm fp stays 0 at the chosen θc — until +then the manifest defaults stay `k=2`-untuned (`max_candidate_clauses=6`, +θc 0.5); (b) the "27/28" / "24/28" recall is on the *synthetic* +recombination set — a bench-qa-derived recombination set (real false +answers that took the paraphrase/entity path) would be more +load-bearing, but those are rare in real traffic (the whole point of +the boundary); (c) this is still SHADOW — flipping it to a runtime +demotion-only veto is a fox-decides (`MODEL_ASSISTED_DEMOTION`, and +`nli_policy_hash` — model + k + agg + θc + θe — folds into +`governance_policy_hash` at that point, per §7 #2). What changes +*now*: the manifest gains `agg` + the k=2/θc=0.99 candidate config as +the recommended-but-not-yet-default operating point, pending the n=3 +confirmation. Production verifier unchanged; `falsification-hard` +stays 10/12.