From 294475b06a35d67de8ba899d17d210ada46b6fc2 Mon Sep 17 00:00:00 2001 From: Claude Date: Sun, 19 Jul 2026 12:49:33 +0000 Subject: [PATCH 1/2] =?UTF-8?q?plans:=20DeepNSM=20=C3=97=20Morton-comma=20?= =?UTF-8?q?facet=20=E2=80=94=20design=20+=20PROBE-DEEPNSM-FACET=20spec=20(?= =?UTF-8?q?blind-replication=20handoff)?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Design handoff for independent replication (RESULTS-FREE by construction). A DeepNSM word becomes a V3 facet: classid(4B)=norm(prefix,frequency,PoS) routing header + 6×(FisherZ:FisherZ) semantic payload (256:256 distribution, cosine replacement). Carries the game-matrix design theory (equilibrium = (Address,Dist,Header); the Payload lane is a fidelity-breaking defection) and the PROBE-DEEPNSM-FACET lane-test spec — the decisive cell: does frequency-in-payload collapse semantic distance vs frequency-in-header, measured on the committed lemmas_5k.csv 8-genre proxy. Adds: scaling to 20k academic COCA (academic_20k.csv committed, 20,845 rows — the header-rich list that structurally confirms the lane separation; O(V) not O(V²)), and the 144-verb (12×12) universal-grammar wiring hook (coarse anchor = verb-atom, NSM-prime pattern at grammar scale). Replication protocol: both sessions implement independently from the spec; results held for operator adjudication; no results in the PR/board until the operator confirms both have run. Co-Authored-By: Claude Opus 4.8 Claude-Session: https://claude.ai/code/session_01K3RyLEbuNSHxxB3NTTrGki --- .../plans/deepnsm-morton-comma-facet-v1.md | 180 + .../deepnsm/word_frequency/academic_20k.csv | 20846 ++++++++++++++++ 2 files changed, 21026 insertions(+) create mode 100644 .claude/plans/deepnsm-morton-comma-facet-v1.md create mode 100644 crates/deepnsm/word_frequency/academic_20k.csv diff --git a/.claude/plans/deepnsm-morton-comma-facet-v1.md b/.claude/plans/deepnsm-morton-comma-facet-v1.md new file mode 100644 index 00000000..b9774e1a --- /dev/null +++ b/.claude/plans/deepnsm-morton-comma-facet-v1.md @@ -0,0 +1,180 @@ +# DeepNSM × Morton-comma facet — design + PROBE-DEEPNSM-FACET spec (v1) + +> **Status:** SPEC (design handoff for independent replication). +> **Contains NO measured results** — this doc is the shared design + probe +> specification. Each session implements and runs independently; results are +> held for operator adjudication (see § Replication protocol). +> **Provenance:** the Morton-comma substrate (`E-PERTURBATION-CONVERGENCE-1`, +> merged) applied to `crates/deepnsm`. Cross-ref: OGAR `256×256 CENTROID TILE` +> canon; le-contract L4 `6×palette256:palette256`; the game-matrix reasoning +> in this doc's §2. + +## 0. The one-sentence design + +A DeepNSM word becomes a **canonical V3 facet**: +`classid(4B) = norm(prefix, frequency, PoS) | payload(12B) = 6 × (FisherZ:FisherZ)` +— prefix+frequency are a **routing/attention header** (codebook scoping + LOD), +NOT distance axes; the 6 byte-pairs are the **semantic distribution** (256:256, +Fisher-z cosine-replacement), analytic (48 B γ) or materialized (palette256). + +## 1. Why 256:256 over 256 (distribution over point) + +DeepNSM today: `96D subgenre-freq → 6 subspaces × 16D → k-means(256) → 6-byte +code`; distance = ADC (16-D L2 per subspace). Each subspace is a **point +estimate** (one centroid). The upgrade: each subspace becomes a **2-D +distributional coordinate** (`FisherZ:FisherZ`) — Fisher-z linearizes cosine, so +L2-in-Fisher-z ≈ cosine, and the pair keeps spread, not just location. Analytic: +`bgz-tensor::fisher_z` (cosine→atanh→8-byte per-family affine→normalized i8; +hydrate via tanh). Materialized alternative: 6 × 256² palette LUT. + +## 2. The game-matrix (design theory — the lane decision) + +Three players, each choosing a lane. **This section is DESIGN reasoning +(architectural payoffs), not measured results.** + +| Player | Strategies | +|---|---| +| **MC** Morton-comma | `Address` (position=key, replayable) · `Flat` | +| **P²** Palette256² | `Dist` (256:256) · `Point` (256 flat) | +| **PF** prefix:frequency | `Header` (classid→codebook-scope+LOD) · `Payload` (distance axis) · `Off` | + +**Pairwise structure:** MC×P² = super-additive (P² *is* the L4 tenant on the +Morton cascade — one structure); MC×PF = synergy (PF is the cascade's +longest-prefix routing header); **P²×PF = conditional** — synergy iff PF=`Header`, +**collapse** iff PF=`Payload`. + +**Dominant strategy: PF=`Header`.** It weakly dominates `Payload` (which only +adds collapse risk — its attention value is recoverable in the header) and `Off`. +**Equilibrium: (Address, Dist, Header).** The **defection trap** is +(Address, Dist, Payload): folding prefix:frequency into the 6×(8:8) is locally +tempting (one uniform code) but breaks fidelity (see §3 — this is exactly what the +probe measures). + +## 3. PROBE-DEEPNSM-FACET — the LANE TEST (the decisive cell) + +Full Fisher-z fidelity (hierarchical 256² vs flat 256) is gated on the +gitignored codebook (`codebook_pq.bin` / `subgenres_5k.csv`) — a **v2** leg that +needs the `.bin`. The **runnable decisive cell** — does frequency-in-payload +collapse semantic distance vs frequency-in-header — runs on **committed data**. + +### 3.1 Data (committed, reproducible) +- `crates/deepnsm/word_frequency/lemmas_5k.csv` — columns `blogPM,webPM,TVMPM, + spokPM,ficPM,magPM,newsPM,acadPM` (8 per-million genre profile) + `freq` + `PoS`. +- 5,050 lemmas. Both sessions read THIS file (no regeneration → identical ground + truth). + +### 3.2 Encoding (spec the normalization EXACTLY so impls match) +1. **Semantic vector** `s(w)` = the 8 `*PM` columns → `log1p` → per-dimension + z-score across the 5,050 vocab (mean 0, std 1 per genre column). 8-D. +2. **Frequency scalar** `f(w)` = `log1p(freq)` → z-score across vocab. 1-D. +3. **Semantic truth distance** `d_truth(a,b) = L2(s(a), s(b))` — this is the + distributional distance DeepNSM's CAM approximates. It is the reference. + +### 3.3 The two lanes +- **HEADER lane** (PF=Header): `d_header(a,b) = d_truth(a,b)` — frequency is a + separate routing header, NOT in the distance. +- **PAYLOAD lane** (PF=Payload): `d_payload(a,b) = L2([s(a); f(a)], [s(b); f(b)])` + — the 9-D distance with the normalized log-frequency APPENDED as a coordinate + (frequency folded into the payload). + +### 3.4 Measurements (report all; NO peeking at the other session) +1. **ρ_all** = Spearman ρ between `d_payload` and `d_truth` over a fixed + deterministic sample of pairs (spec: all pairs among the top-256 lemmas by + rank, = 32,640 pairs — deterministic, no RNG). +2. **Frequency-shuffle invariance (the orthogonality proof):** permute the `f` + values across words; recompute `d_header` (unchanged by construction) and + `d_payload` (changes). Report whether `d_header` is invariant (it must be) and + the magnitude of `d_payload`'s change. +3. **The collapse falsifier (the "the/this" shape):** among the top-256 lemmas, + identify pairs that are **high-frequency-similar** (|f(a)−f(b)| in the bottom + decile) but **semantically distant** (`d_truth` in the top decile). Report: + how many such pairs have `d_payload < d_truth` (pulled artificially closer by + shared frequency) = the collapse count; and the mean Δ = `d_payload − d_truth` + for this set vs the complement. +4. **Named anchors:** report `d_truth` vs `d_payload` for `(the, be)` and + `(the, of)` (top-frequency, genre-distinct) — the concrete collapse witnesses. + +### 3.5 PASS / COLLAPSE criteria (pre-registered — fill with YOUR numbers only) +- **HEADER lane** must be **frequency-shuffle-invariant** (measurement 2) — the + lane-orthogonality proof (frequency didn't leak into semantics). +- **COLLAPSE CONFIRMED** (⇒ PF=Payload is a defection, equilibrium holds) iff: + `ρ_all < 1.0` AND the collapse count (measurement 3) is **materially non-zero** + AND the named anchors (measurement 4) show `d_payload < d_truth` (frequent-far + pairs pulled together). +- **COLLAPSE REFUTED** (⇒ reconsider the matrix) iff `d_payload ≈ d_truth` + (ρ_all ≈ 1.0) and no anchor inversion — frequency did NOT corrupt semantics. + +## 3a. Scaling to 20k academic COCA (the regime where the facet earns its keep) + +Committed this PR: `crates/deepnsm/word_frequency/academic_20k.csv` (20,845 rows; +cols `ID, band, status, word, Pos, COCA-All, COCA-Acad, ratio, disp, range` — +the 20k most-frequent COCA-Academic words, academicwords.info). + +**Why 20k matters:** a dense distance matrix is O(V²). 5k → 25M (fine); **20k → +~400M cells** (borderline); full 151K → 23 GB (infeasible). The facet is O(V) +storage + O(1) render — the substrate's whole point. So 20k is precisely where +"store the metric, render the distance" beats "materialize the matrix." + +**The 20k list is STRUCTURAL evidence for the lane separation.** Its columns are +almost ALL header/routing signals — `band` (frequency-LOD stratum), `ratio` +(COCA-Acad / COCA-All = academic-register routing), `disp` (dispersion = +confidence/attention), `Pos` (grammatical routing) — with the distributional +*payload* (subgenre/embedding) held SEPARATELY. The academic list is a **header +table**; it confirms prefix+frequency+register belong in the classid, not the +distance. (No per-genre breakdown here — so the 20k fidelity leg needs the +distributional codebook; the 5k `lemmas_5k.csv` 8-genre proxy carries the §3 +lane test.) + +**Header packing for 20k (design):** `classid(4B)` = `band` (LOD) · quantized +`ratio` (register axis) · `Pos` · lemma-family prefix. This is the codebook-scope ++ attention header; the 6×(FisherZ:FisherZ) payload is the (separately-sourced) +distributional meaning. + +## 3b. Wiring into the 12×12 = 144-verb universal grammar (design hook) + +The rung-2 **144 verb-atoms** (`.claude/v3/knowledge/persona-vs-rung-ladder.md`: +"rung 2 = 144 verb atoms") are a universal, interpretable semantic basis — the +grammar analog of the 63 NSM primes DeepNSM already anchors on. Wiring: + +- **The coarse centroid level = the 144-verb basis, not anonymous k-means.** Each + word's coarse byte indexes its nearest verb-atom (144 < 256 → fits one byte), + making the coarse address **interpretable** (a verb, not centroid #173) and + **universal** (language-agnostic grammar). The fine byte is the within-atom + residual. So a subspace's `256:256` = `(verb-atom : residual)`. +- **12×12 = the coarse address is a `12:12` pair** — the two doz­enal axes of the + universal grammar (e.g. subject-role × predicate-role, or aspect × mood), + mapping directly onto the `(8:8)`-byte-pair carving (144 lives in the low bits + of the coarse byte). +- **Anchoring = the NSM-prime pattern, extended.** DeepNSM already gives each of + 63 NSM primes a CAM fingerprint (`nsm_primes.json`); the 144 verb-atoms are the + same move at grammar scale — they become the coarse codebook, and every word + resonates onto them. The `Pos='v'` rows in `academic_20k.csv` (thousands of + verbs) are the population the 144 basis must span. + +**Status: DESIRED WIRING (v2 hook), gated on the 144-verb basis being available +as fingerprints.** It does NOT change the §3 lane test (which is basis-agnostic — +it only tests header-vs-payload for `frequency`). It DOES sharpen the equilibrium: +if the coarse anchor is the 144-verb grammar, the "attention header" (§2 PF) is +literally routing a word to its grammatical verb-atom — the header lane and the +universal grammar are the same structure. + +## 4. Replication protocol (BLIND — read before running) + +- **Implement independently from THIS spec.** Do NOT import the other session's + probe code. Diverse implementations (e.g. Rust vs Python) strengthen the + witness — if two independent impls on the same committed CSV agree on the + collapse count + anchor inversions, the result is real, not a single-session + artifact. +- **Do NOT publish results** in this PR, in PR comments, in `EPIPHANIES.md`, or + any shared board file, until the operator confirms both sessions have run. + Report your numbers to the **operator only**. The operator adjudicates the two + blind results. +- Determinism: no RNG anywhere (fixed pair sets by rank). Same CSV + same spec ⇒ + the two impls should converge if the design is real. + +## 5. If PASS — what lands (v2, AFTER operator adjudication) +- Wire DeepNSM word → `classid[norm(prefix,freq,PoS)] + 6×(FisherZ:FisherZ)`. +- Distance = analytic Fisher-z (48 B γ) with materialized palette256 as the + optional cache (le-contract "table = cache of the formula"). +- The full hierarchical 256²-vs-flat-256 fidelity leg (needs the `.bin` codebook) + is the named v2. diff --git a/crates/deepnsm/word_frequency/academic_20k.csv b/crates/deepnsm/word_frequency/academic_20k.csv new file mode 100644 index 00000000..9842391f --- /dev/null +++ b/crates/deepnsm/word_frequency/academic_20k.csv @@ -0,0 +1,20846 @@ +ID,band,status,word,Pos,COCA-All,COCA-Acad,ratio,disp,range +1,1,c,the,a,23782116,7131341,1.04999169762732,0.962708808404016,9 +2,1,c,of,i,11155504,4060103,1.2744212650899,0.962708808404016,9 +3,1,c,be,v,16711569,3457266,0.724403805780164,0.962708808404016,9 +4,1,c,and,c,11654440,3291949,0.989069574782004,0.962708808404016,9 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+20835,42,r,choreograph,v,816,114,0.48919256425325,0.87290306582637,9 +20836,42,x,dislocate,v,433,114,0.921896379747464,0.864602999578127,8 +20837,42,r,embroider,v,887,114,0.450035098568942,0.77242316317813,8 +20838,42,r,excommunicate,v,227,114,1.75850719132446,0.775521464629732,5 +20839,42,x,howl,v,2320,114,0.172060832944246,0.881784461133778,7 +20840,42,r,mash,v,1233,114,0.32374787707271,0.825887130052898,7 +20841,42,x,plaster,v,1204,114,0.331545791055359,0.897280890712259,9 +20842,42,r,renege,v,449,114,0.889044838375616,0.873516767790633,8 +20843,42,x,revolt,v,429,114,0.930492150187999,0.858973143744479,6 +20844,42,x,shepherd,v,602,114,0.663091582110717,0.866338188757528,8 +20845,42,r,uncheck,v,120,114,3.3265094369221,0.597735873428249,1 From 0314c6692c71132efe057535bf79a950c3a9a97b Mon Sep 17 00:00:00 2001 From: Claude Date: Sun, 19 Jul 2026 12:53:58 +0000 Subject: [PATCH 2/2] plans/deepnsm-facet: fix impossible collapse criterion (Codex P1) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Codex P1 (correct): appending normalized frequency gives d_payload = sqrt(d_truth^2 + df^2) >= d_truth by Pythagoras, so d_payload < d_truth is impossible — the old collapse falsifier would always report zero and falsely REFUTE the defection, invalidating the blind experiment. Fix the operationalization: the real defection is neighbor/rank corruption, not absolute inversion. Frequency inflation pushes semantically-near-but-frequency-far pairs APART and reorders the neighborhood. New measurements: (3a) nearest-neighbor flip rate; (3b) inflation + downward rank displacement of the semantically-near/frequency-far set; (4) computed anchor = the nearest-decile pair with the largest frequency gap, its rank fall. PASS/COLLAPSE criteria updated to rho<1 + neighbor-flip + near-far displacement. Optional fixed-width REPLACE variant noted (where absolute inversion does arise). Spec stays results-free. Co-Authored-By: Claude Opus 4.8 Claude-Session: https://claude.ai/code/session_01K3RyLEbuNSHxxB3NTTrGki --- .../plans/deepnsm-morton-comma-facet-v1.md | 45 +++++++++++++------ 1 file changed, 32 insertions(+), 13 deletions(-) diff --git a/.claude/plans/deepnsm-morton-comma-facet-v1.md b/.claude/plans/deepnsm-morton-comma-facet-v1.md index b9774e1a..1876d5de 100644 --- a/.claude/plans/deepnsm-morton-comma-facet-v1.md +++ b/.claude/plans/deepnsm-morton-comma-facet-v1.md @@ -85,24 +85,43 @@ collapse semantic distance vs frequency-in-header — runs on **committed data** values across words; recompute `d_header` (unchanged by construction) and `d_payload` (changes). Report whether `d_header` is invariant (it must be) and the magnitude of `d_payload`'s change. -3. **The collapse falsifier (the "the/this" shape):** among the top-256 lemmas, - identify pairs that are **high-frequency-similar** (|f(a)−f(b)| in the bottom - decile) but **semantically distant** (`d_truth` in the top decile). Report: - how many such pairs have `d_payload < d_truth` (pulled artificially closer by - shared frequency) = the collapse count; and the mean Δ = `d_payload − d_truth` - for this set vs the complement. -4. **Named anchors:** report `d_truth` vs `d_payload` for `(the, be)` and - `(the, of)` (top-frequency, genre-distinct) — the concrete collapse witnesses. +3. **Neighborhood corruption — the collapse signal (NOT absolute inversion).** + ⚠ The append is **monotone-non-decreasing**: `d_payload = √(d_truth² + (Δf)²) + ≥ d_truth` (Pythagoras), so `d_payload < d_truth` is IMPOSSIBLE and must NOT + be used as a criterion. The real defection is **rank/neighbor corruption**: + frequency inflates distances by the frequency gap, which pushes + **semantically-near-but-frequency-far** pairs (near-synonyms with divergent + frequency) APART and reorders the neighborhood. Measure: + - (a) **Nearest-neighbor flip rate:** for each of the 256 words, its nearest + neighbor under `d_header`(=`d_truth`) vs under `d_payload`; report the + fraction whose nearest neighbor CHANGES. + - (b) **The corrupted set:** pairs that are semantically **near** (`d_truth` + bottom decile) but frequency-**far** (`|f(a)−f(b)|` top decile). Report + their mean inflation `d_payload − d_truth` (> 0) and their mean **downward + displacement** in the global nearness ranking (they fall relative to + frequency-near pairs) vs the complement. +4. **Named anchor (computed, not hand-picked):** among the semantically-nearest + decile of pairs, report the one with the LARGEST frequency gap — its + `d_truth`, `d_payload`, inflation, and how many rank positions it FALLS in the + nearness ordering (a true near-pair demoted purely by frequency). ### 3.5 PASS / COLLAPSE criteria (pre-registered — fill with YOUR numbers only) - **HEADER lane** must be **frequency-shuffle-invariant** (measurement 2) — the lane-orthogonality proof (frequency didn't leak into semantics). - **COLLAPSE CONFIRMED** (⇒ PF=Payload is a defection, equilibrium holds) iff: - `ρ_all < 1.0` AND the collapse count (measurement 3) is **materially non-zero** - AND the named anchors (measurement 4) show `d_payload < d_truth` (frequent-far - pairs pulled together). -- **COLLAPSE REFUTED** (⇒ reconsider the matrix) iff `d_payload ≈ d_truth` - (ρ_all ≈ 1.0) and no anchor inversion — frequency did NOT corrupt semantics. + `ρ_all < 1.0` AND the **nearest-neighbor flip rate** (3a) is materially + non-zero AND the semantically-near-frequency-far set (3b) shows systematic + positive inflation + downward rank displacement (frequency corrupts the + semantic neighborhood). +- **COLLAPSE REFUTED** (⇒ reconsider the matrix) iff `ρ_all ≈ 1.0` and ~zero + nearest-neighbor flips — frequency did NOT corrupt the ordering. +- **Optional stronger variant (fixed-width faithful):** since the real payload is + fixed-width `6×(8:8)`, "folding in" frequency means it REPLACES a semantic + axis, not appends. Under REPLACE (overwrite the lowest-variance genre dim with + `f`), absolute inversions `d_payload < d_truth` DO become possible (a dropped + axis shrinks some distances) on top of the frequency contamination — a report + may add this variant, but the neighbor/rank corruption above is the primary, + append-robust falsifier. ## 3a. Scaling to 20k academic COCA (the regime where the facet earns its keep)