Add Phono_Quality column, downgrade contested/doubtful pairs

- Added 15th column 'Phono_Quality' (strong/moderate/weak/none/unscored)
based on SCA score thresholds to flag phonologically divergent cognates
- Downgraded 27,059 Robbeets cross-family pairs from certain to contested
- Fixed 2,906 Sino-Tibetan pairs from certain to doubtful (STEDT doubt markers)
- Rebuilt Parquet (31.3 MB) with new schema
- Added changelog entry 007 and flagging script

data/training/cognate_pairs/cognate_pairs_inherited.parquet

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data/training/cognate_pairs/cognate_pairs_inherited.tsv

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docs/changelog/007_phono_quality_flagging.md

@@ -0,0 +1,117 @@
+# 007 — Phonological Quality Flagging & Confidence Corrections
+
+**Date**: 2026-03-19
+
+## Objective
+
+Post-audit quality flagging to address three issues identified by a 4-agent adversarial certification audit:
+
+1. **Phonological divergence**: ~31% of "certain" cognate pairs have surface forms so divergent (Score ≤ 0.2 or unscored) that they are indistinguishable from random word pairs, despite being etymologically correct cognates. Downstream consumers need a way to filter by phonological evidence strength.
+2. **Robbeets cross-family contestation**: 27,059 pairs from the Transeurasian dataset cross language family boundaries (e.g., Turkic↔Japonic). The Transeurasian hypothesis is formally contested in published academic rebuttals. These were incorrectly labeled "certain."
+3. **Sino-Tibetan doubt markers**: The original STEDT source data contains doubt markers (`!`, `?`, `doubtful`) in the NOTE column for 655 cognate sets, but the extraction script hardcoded all pairs as "certain."
+
+## Scripts Used
+
+| Script | Lines | Purpose |
+|--------|------:|---------|
+| `scripts/flag_phono_quality.py` | 185 | Stream-processes 23.5M rows: adds `Phono_Quality` column, downgrades Robbeets cross-family Confidence, fixes Sino-Tibetan doubt markers |
+
+**Data integrity**: No data was added, removed, or fabricated. The script only adds a new column (`Phono_Quality`) and corrects two existing `Confidence` values based on source metadata. All changes are deterministic and reproducible.
+
+## Data Sources
+
+No new external data sources. All corrections derive from metadata already present in existing sources:
+
+| Source | File Used | Purpose |
+|--------|-----------|---------|
+| Robbeets et al. 2021 | `sources_tier1/robbeetstriangulation/cldf/languages.csv` | Family column for cross-family detection |
+| STEDT / Sagart et al. 2019 | `ancient-scripts-datasets/sources/sinotibetan/sinotibetan_dump.tsv` | NOTE column for doubt markers |
+
+## Methodology
+
+### Phono_Quality Classification
+
+A new 15th column `Phono_Quality` is added to every row based on the existing SCA score:
+
+| Value | Score Range | Meaning | Count | % |
+|-------|-------------|---------|------:|--:|
+| `strong` | Score ≥ 0.5 | Clear phonological similarity between surface forms | 6,551,211 | 27.92% |
+| `moderate` | 0.2 ≤ Score < 0.5 | Detectable but weak surface similarity | 9,565,693 | 40.76% |
+| `weak` | 0 < Score < 0.2 | Minimal similarity, possibly coincidental | 2,210,058 | 9.42% |
+| `none` | Score = 0.0 | Zero surface similarity despite cognacy | 3,314,102 | 14.12% |
+| `unscored` | Score = -1.0 | No SCA score computed (ACD pairs) | 1,825,701 | 7.78% |
+
+**Rationale for thresholds**: The SCA (Sound Class Alphabet) distance metric from List (2012) returns a normalized similarity score in [0, 1]. The 0.5 threshold separates pairs where a human could plausibly identify shared phonological material from those where similarity is statistical only. The 0.2 threshold separates detectable patterns from near-noise. These thresholds are conservative — phonological similarity below 0.2 is rarely distinguishable from chance resemblance across unrelated languages.
+
+**Why `none` ≠ "not cognate"**: A pair with Score=0.0 (e.g., Pohnpeian `ehd` and Atayal `isa`, both "one" from proto-Austronesian \*esa) can be a genuine cognate whose surface forms diverged beyond recognition over millennia. The `none` flag means "the phonological evidence is invisible at the surface level," not "the cognacy judgment is wrong."
+
+### Robbeets Cross-Family Downgrade
+
+The Robbeets Transeurasian dataset contains cognate sets that span 5 language families: Turkic, Mongolic, Tungusic, Koreanic, and Japonic. For each Robbeets pair:
+
+1. Look up both Lang_A and Lang_B in the Robbeets `languages.csv` → get `Family` column
+2. If `Family_A ≠ Family_B` → the pair is cross-family
+3. Downgrade `Confidence` from `certain` to `contested`
+
+**Academic justification**: The Transeurasian hypothesis (Robbeets et al. 2021, Nature) is contested by multiple published rebuttals. Georg (2023) and others argue that the cross-family cognate sets fail strict sound correspondence criteria. Within-family cognate sets (e.g., Turkic↔Turkic) are universally accepted and remain `certain`.
+
+**Breakdown of cross-family pairs (27,059 total)**:
+- Mongolic↔Turkic: 8,859
+- Mongolic↔Tungusic: 6,863
+- Tungusic↔Turkic: 5,624
+- Japonic↔Turkic: 2,754
+- Japonic↔Mongolic: 1,083
+- Japonic↔Tungusic: 959
+- Japonic↔Koreanic: 305
+- Koreanic↔Tungusic: 262
+- Koreanic↔Turkic: 243
+- Koreanic↔Mongolic: 107
+
+### Sino-Tibetan Doubt Marker Fix
+
+The STEDT source data contains a NOTE column with doubt markers for 655 cognate sets (890 individual form rows). When any form in a cognate set has a doubt marker (`!`, `?`, `?!`, or `doubtful`), all pairs derived from that cognate set are downgraded from `certain` to `doubtful`.
+
+**Source_Record_ID format**: `st_{COGID}` — the COGID maps directly to the STEDT etymological set. 2,906 pairs were fixed.
+
+## Tests Performed
+
+1. **Row count verification**: Output has exactly 23,466,765 rows (matches input)
+2. **Column verification**: Header contains all 15 columns including new `Phono_Quality`
+3. **Confidence distribution check**:
+   - `certain`: 22,721,849 (was 22,751,814 — reduced by 27,059 + 2,906)
+   - `doubtful`: 717,857 (was 714,951 — increased by 2,906)
+   - `contested`: 27,059 (new category)
+4. **Cross-tabulation**: Phono_Quality × Confidence verified for all 13 combinations
+5. **Spot checks**: Verified Robbeets cross-family pairs (jpn↔kor) show `contested`, Sino-Tibetan doubt pairs show `doubtful`
+
+## Output Summary
+
+| File | Rows | Size | Change |
+|------|-----:|-----:|--------|
+| `cognate_pairs_inherited.tsv` | 23,466,765 | ~5.3 GB | +1 column (Phono_Quality), Confidence corrections |
+| `cognate_pairs_inherited.parquet` | 23,466,765 | 31.3 MB | Rebuilt with new column |
+
+### Schema Change
+
+Column 15 added: `Phono_Quality` (string enum: `strong`, `moderate`, `weak`, `none`, `unscored`)
+
+### Confidence Value Changes
+
+| Change | Count | Reason |
+|--------|------:|--------|
+| `certain` → `contested` | 27,059 | Robbeets cross-family pairs |
+| `certain` → `doubtful` | 2,906 | Sino-Tibetan doubt markers from STEDT |
+
+## Limitations
+
+1. **Phono_Quality thresholds are heuristic**: The 0.5 and 0.2 boundaries are reasonable but not calibrated against a held-out dataset. Different downstream tasks may want different cutoffs.
+2. **ACD pairs remain `unscored`**: The ACD source provides no IPA transcriptions, so SCA scoring is impossible. These 1.8M pairs are likely genuine cognates (Blust's life work) but their phonological quality cannot be assessed.
+3. **Score=0.0 does not mean "not cognate"**: Deep cognates with millennia of divergence can legitimately score 0.0. The `none` flag is informational, not a rejection.
+4. **Robbeets within-family pairs remain `certain`**: Only the 27,059 cross-family pairs are downgraded. The 134,090 within-family pairs (Turkic↔Turkic, etc.) are universally accepted.
+
+## Academic References
+
+- List, J.-M. (2012). "SCA: Phonetic alignment based on sound classes." New Directions in Logic, Language, and Computation, Springer. (SCA distance metric)
+- Robbeets, M. et al. (2021). "Triangulation supports agricultural spread of the Transeurasian languages." Nature 599, 616-621.
+- Georg, S. (2023). "Review of Robbeets et al. 2021." (Formal rebuttal of cross-family cognate claims)
+- Sagart, L. et al. (2019). "Dated language phylogenies shed light on the ancestry of Sino-Tibetan." PNAS 116(21):10317-10322.

docs/changelog/INDEX.md

@@ -6,6 +6,7 @@ All changes to the `Nacryos/ancient-scripts-datasets` HuggingFace dataset are lo
 
 | Date | Entry | Summary |
 |------|-------|---------|
+| 2026-03-19 | [007_phono_quality_flagging.md](007_phono_quality_flagging.md) | Added `Phono_Quality` column (strong/moderate/weak/none/unscored), downgraded 27K Robbeets cross-family to "contested", fixed 2.9K Sino-Tibetan doubt markers |
 | 2026-03-19 | [006_tier1_cldf_ingestion.md](006_tier1_cldf_ingestion.md) | +573K expert cognate pairs from IE-CoR, Robbeets, Savelyev — 31 new ancient languages, 4-agent adversarial audit |
 | 2026-03-15 | [005_parquet_conversion.md](005_parquet_conversion.md) | Added Parquet files + YAML dataset card for HF `datasets` library integration |
 | 2026-03-14 | [004_phylo_enrichment.md](004_phylo_enrichment.md) | Added phylogenetic metadata (`phylo_pairs.tsv`) derived from Glottolog CLDF |

scripts/flag_phono_quality.py

@@ -0,0 +1,237 @@
+#!/usr/bin/env python3
+"""
+Post-audit quality flagging for cognate pairs dataset.
+
+Changes applied:
+  1. Adds 'Phono_Quality' column based on SCA Score thresholds
+  2. Downgrades Robbeets cross-family pairs: Confidence "certain" → "contested"
+  3. Fixes Sino-Tibetan confidence: propagates doubt markers from source NOTE column
+
+Phono_Quality values:
+  - "strong"   : Score >= 0.5 — clear phonological similarity
+  - "moderate" : 0.2 <= Score < 0.5 — detectable but weak similarity
+  - "weak"     : 0 < Score < 0.2 — minimal similarity, possibly coincidental
+  - "none"     : Score == 0.0 — zero surface similarity despite cognacy
+  - "unscored" : Score == -1.0 — no SCA score computed (e.g. ACD)
+
+Streams line-by-line for memory efficiency on the 23.5M row file.
+"""
+import csv
+import os
+import sys
+from collections import defaultdict
+from pathlib import Path
+
+# Force UTF-8 on Windows
+if sys.stdout.encoding != 'utf-8':
+    sys.stdout.reconfigure(encoding='utf-8')
+
+
+def build_robbeets_family_map(repo_dir: str) -> dict:
+    """
+    Build a mapping from language identifier → family for Robbeets data.
+    Maps both ISO codes and internal IDs to family names.
+    """
+    lang_csv = Path(repo_dir) / 'cldf' / 'languages.csv'
+    family_map = {}
+    with open(lang_csv, encoding='utf-8') as f:
+        for row in csv.DictReader(f):
+            internal_id = row['ID']
+            iso = row.get('ISO639P3code', '').strip()
+            family = row.get('Family', '').strip()
+            if not family:
+                continue
+            # Map internal ID → family
+            family_map[internal_id] = family
+            # Map ISO → family (if available)
+            if iso:
+                family_map[iso] = family
+    return family_map
+
+
+def build_sinotibetan_doubt_cogids(source_path: str) -> set:
+    """
+    Build a set of COGID values that have doubt-marked forms in the
+    Sino-Tibetan source data. A COGID is flagged if ANY form in that
+    cognate set has a doubt marker (!, ?, ?!, doubtful).
+    """
+    doubt_cogids = set()
+    with open(source_path, encoding='utf-8') as f:
+        reader = csv.DictReader(f, delimiter='\t')
+        for row in reader:
+            note = row.get('NOTE', '').strip()
+            cogid = row.get('COGID', '').strip()
+            if not cogid:
+                continue
+            # Flag if note starts with ! or ? or is "doubtful"
+            if note.startswith('!') or note.startswith('?') or note.lower() == 'doubtful':
+                doubt_cogids.add(cogid)
+    return doubt_cogids
+
+
+def classify_phono_quality(score_str: str) -> str:
+    """Classify phonological quality based on SCA score."""
+    try:
+        score = float(score_str)
+    except (ValueError, TypeError):
+        return 'unscored'
+
+    if score == -1.0:
+        return 'unscored'
+    elif score == 0.0:
+        return 'none'
+    elif score < 0.2:
+        return 'weak'
+    elif score < 0.5:
+        return 'moderate'
+    else:
+        return 'strong'
+
+
+def main():
+    hf_dir = Path(__file__).parent.parent
+    inherited_tsv = hf_dir / 'data' / 'training' / 'cognate_pairs' / 'cognate_pairs_inherited.tsv'
+    output_tsv = inherited_tsv.with_suffix('.flagged.tsv')
+
+    # ── Pre-load lookup tables ──
+
+    # 1. Robbeets family map
+    robbeets_dir = hf_dir / 'sources_tier1' / 'robbeetstriangulation'
+    if robbeets_dir.exists():
+        print('Loading Robbeets family map...')
+        robbeets_family = build_robbeets_family_map(str(robbeets_dir))
+        print(f'  {len(robbeets_family)} language→family mappings')
+    else:
+        print('WARNING: Robbeets source dir not found, skipping cross-family detection')
+        robbeets_family = {}
+
+    # 2. Sino-Tibetan doubt COGIDs
+    st_source = hf_dir.parent / 'ancient-scripts-datasets' / 'sources' / 'sinotibetan' / 'sinotibetan_dump.tsv'
+    if st_source.exists():
+        print('Loading Sino-Tibetan doubt markers...')
+        st_doubt_cogids = build_sinotibetan_doubt_cogids(str(st_source))
+        print(f'  {len(st_doubt_cogids)} doubt-flagged COGIDs')
+    else:
+        print('WARNING: Sino-Tibetan source not found, skipping doubt marker fix')
+        st_doubt_cogids = set()
+
+    # ── Check LFS pointer ──
+    with open(inherited_tsv, encoding='utf-8') as f:
+        first_line = f.readline()
+        if first_line.startswith('version https://git-lfs.github.com'):
+            print('ERROR: inherited TSV is an LFS pointer. Run: git lfs pull')
+            sys.exit(1)
+
+    # ── Stream-process ──
+    INPUT_COLUMNS = [
+        'Lang_A', 'Word_A', 'IPA_A', 'Lang_B', 'Word_B', 'IPA_B',
+        'Concept_ID', 'Relationship', 'Score', 'Source',
+        'Relation_Detail', 'Donor_Language', 'Confidence', 'Source_Record_ID',
+    ]
+    OUTPUT_COLUMNS = INPUT_COLUMNS + ['Phono_Quality']
+
+    # Counters
+    total = 0
+    phono_counts = defaultdict(int)
+    robbeets_downgraded = 0
+    st_doubt_fixed = 0
+    source_counts = defaultdict(int)
+    confidence_changes = defaultdict(int)
+
+    print(f'\nProcessing {inherited_tsv}...')
+    print(f'Output: {output_tsv}')
+
+    with open(inherited_tsv, encoding='utf-8') as fin, \
+         open(output_tsv, 'w', encoding='utf-8', newline='') as fout:
+
+        reader = csv.DictReader(fin, delimiter='\t')
+        writer = csv.DictWriter(fout, fieldnames=OUTPUT_COLUMNS, delimiter='\t',
+                                extrasaction='ignore')
+        writer.writeheader()
+
+        for row in reader:
+            total += 1
+            source = row.get('Source', '')
+            source_counts[source] += 1
+
+            # ── 1. Phono_Quality from Score ──
+            phono_quality = classify_phono_quality(row.get('Score', ''))
+            row['Phono_Quality'] = phono_quality
+            phono_counts[phono_quality] += 1
+
+            # ── 2. Robbeets cross-family → "contested" ──
+            if source == 'robbeetstriangulation' and robbeets_family:
+                lang_a = row['Lang_A']
+                lang_b = row['Lang_B']
+                fam_a = robbeets_family.get(lang_a, '')
+                fam_b = robbeets_family.get(lang_b, '')
+                if fam_a and fam_b and fam_a != fam_b:
+                    if row['Confidence'] == 'certain':
+                        row['Confidence'] = 'contested'
+                        robbeets_downgraded += 1
+                        confidence_changes['certain→contested'] += 1
+
+            # ── 3. Sino-Tibetan doubt markers ──
+            if source == 'sinotibetan' and st_doubt_cogids:
+                # Source_Record_ID format: st_{COGID}
+                src_id = row.get('Source_Record_ID', '')
+                if src_id.startswith('st_'):
+                    cogid = src_id[3:]  # strip "st_" prefix
+                    if cogid in st_doubt_cogids:
+                        if row['Confidence'] == 'certain':
+                            row['Confidence'] = 'doubtful'
+                            st_doubt_fixed += 1
+                            confidence_changes['certain→doubtful (ST)'] += 1
+
+            writer.writerow(row)
+
+            if total % 5_000_000 == 0:
+                print(f'  Processed {total:,} rows...')
+
+    # ── Summary ──
+    print(f'\n=== PROCESSING COMPLETE ===')
+    print(f'Total rows: {total:,}')
+
+    print(f'\n--- Phono_Quality Distribution ---')
+    for quality in ['strong', 'moderate', 'weak', 'none', 'unscored']:
+        count = phono_counts[quality]
+        pct = count / total * 100 if total else 0
+        print(f'  {quality:12s}: {count:>12,} ({pct:5.2f}%)')
+
+    print(f'\n--- Source Counts ---')
+    for src, count in sorted(source_counts.items(), key=lambda x: -x[1]):
+        print(f'  {src:30s}: {count:>12,}')
+
+    print(f'\n--- Confidence Changes ---')
+    print(f'  Robbeets cross-family downgraded: {robbeets_downgraded:,}')
+    print(f'  Sino-Tibetan doubt-fixed:         {st_doubt_fixed:,}')
+    for change, count in sorted(confidence_changes.items()):
+        print(f'  {change}: {count:,}')
+
+    # ── Replace original with flagged version ──
+    print(f'\nReplacing original TSV with flagged version...')
+    backup = inherited_tsv.with_suffix('.tsv.bak')
+    os.rename(inherited_tsv, backup)
+    os.rename(output_tsv, inherited_tsv)
+    print(f'  Original backed up to {backup.name}')
+    print(f'  Flagged version now at {inherited_tsv.name}')
+
+    # ── Verify ──
+    print(f'\nVerifying final file...')
+    verify_count = 0
+    has_phono_col = False
+    with open(inherited_tsv, encoding='utf-8') as f:
+        header = f.readline().strip()
+        if 'Phono_Quality' in header:
+            has_phono_col = True
+        for _ in f:
+            verify_count += 1
+    print(f'  Header has Phono_Quality: {has_phono_col}')
+    print(f'  Data rows: {verify_count:,}')
+    assert verify_count == total, f'COUNT MISMATCH: {verify_count} vs {total}'
+    assert has_phono_col, 'Phono_Quality column missing from header!'
+    print(f'  VERIFICATION PASSED')
+
+
+if __name__ == '__main__':
+    main()