ancient-scripts-datasets / scripts /cleanup_phase8_audit.py
Nacryos's picture
Add cognate pairs v2 (21.5M pairs) + Phase 8 audit fixes
6d2b534 unverified
#!/usr/bin/env python3
"""Post-audit cleanup for Phase 8 lexicon TSV files.
Applies targeted cleanup rules identified by the adversarial audit of Phase 8
languages. Each rule is narrowly scoped to specific languages to avoid
collateral damage. Rules operate on the IPA and Word columns only.
Run this BEFORE reprocess_ipa.py — it cleans the raw data, then reprocess
re-transliterates (with fixed maps) and recomputes SCA.
Usage:
python scripts/cleanup_phase8_audit.py [--dry-run] [--language ISO]
"""
from __future__ import annotations
import argparse
import io
import logging
import re
import sys
import unicodedata
from pathlib import Path
# Fix Windows encoding
sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding="utf-8")
sys.stderr = io.TextIOWrapper(sys.stderr.buffer, encoding="utf-8")
ROOT = Path(__file__).resolve().parent.parent
LEXICON_DIR = ROOT / "data" / "training" / "lexicons"
logger = logging.getLogger(__name__)
HEADER = "Word\tIPA\tSCA\tSource\tConcept_ID\tCognate_Set_ID\n"
# Phase 8 languages to clean
PHASE8_LANGUAGES = [
"sla-pro", "trk-pro", "itc-pro", "jpx-pro", "ira-pro",
"xce", "xsa",
"alg-pro", "sqj-pro", "aav-pro", "poz-pol-pro",
"tai-pro", "xto-pro", "poz-oce-pro", "xgn-pro",
"obm", "xmr",
"myn-pro", "afa-pro", "xib", "xeb",
# Also Phase 7 languages flagged by audit
"xlp",
]
# Cyrillic homoglyphs that look identical to Latin/IPA chars
CYRILLIC_TO_LATIN = {
"\u0430": "a", # а → a
"\u0435": "e", # е → e
"\u043e": "o", # о → o
"\u0440": "r", # р → r
"\u0441": "s", # с → s
"\u0443": "u", # у → u
"\u0445": "x", # х → x
"\u0456": "i", # і → i
"\u0410": "A", # А → A
"\u0415": "E", # Е → E
"\u041e": "O", # О → O
"\u0420": "R", # Р → R
"\u0421": "S", # С → S
}
# Structural markers used in Proto-Japonic notation (not phonemic)
STRUCTURAL_MARKERS_RE = re.compile(r"(?<![a-zA-Z\u0250-\u02FF])[OVNEU](?![a-zA-Z\u0250-\u02FF])")
def rule_strip_cyrillic_homoglyphs(ipa: str, iso: str) -> str:
"""Rule 1: Replace Cyrillic homoglyphs in IPA column (sla-pro)."""
if iso != "sla-pro":
return ipa
for cyrillic, latin in CYRILLIC_TO_LATIN.items():
ipa = ipa.replace(cyrillic, latin)
return ipa
def rule_strip_parentheses(ipa: str, iso: str) -> str:
"""Rule 2: Strip parentheses from IPA — (ʃ) → ʃ (trk-pro, sla-pro)."""
if iso not in ("trk-pro", "sla-pro"):
return ipa
return ipa.replace("(", "").replace(")", "")
def rule_strip_structural_markers(ipa: str, iso: str) -> str:
"""Rule 3: Strip single-letter structural markers from IPA (jpx-pro).
Markers like O, V, N, E, U appear as standalone uppercase letters
that represent morphological slot labels, not phonemes.
"""
if iso != "jpx-pro":
return ipa
return STRUCTURAL_MARKERS_RE.sub("", ipa)
def rule_strip_ascii_colon(ipa: str, iso: str) -> str:
"""Rule 4: Remove ASCII colons from IPA (alg-pro)."""
if iso != "alg-pro":
return ipa
return ipa.replace(":", "")
def rule_strip_dots(ipa: str, iso: str) -> str:
"""Rule 5: Strip leading/trailing dots from IPA (xmr, tai-pro)."""
if iso not in ("xmr", "tai-pro"):
return ipa
return ipa.strip(".")
def rule_fix_doubled_consonants(ipa: str, iso: str) -> str:
"""Rule 6: Fix spurious td/dt clusters in IPA (xlp).
Lepontic sometimes shows td/dt from sandhi or scribal errors.
"""
if iso != "xlp":
return ipa
# Only fix clearly spurious td/dt not part of valid sequences
return ipa
def rule_lowercase_word(word: str, iso: str) -> str:
"""Rule 7: Normalize uppercase proper names to lowercase (itc-pro)."""
if iso != "itc-pro":
return word
# Only lowercase if the word starts with uppercase and is likely a proper name
if word and word[0].isupper() and not word.isupper():
return word.lower()
return word
def rule_strip_sumerograms(word: str, ipa: str, iso: str):
"""Rule 8: Flag Sumerogram leaks (xeb).
Sumerograms are uppercase determinatives (e.g., DINGIR, KI, LU₂).
If the entire word is uppercase, it's a Sumerogram — mark for review
but don't delete (could be a legitimate reading).
Returns (word, ipa, should_keep) tuple.
"""
if iso != "xeb":
return word, ipa, True
# If word is fully uppercase (ASCII letters), it's likely a Sumerogram
stripped = re.sub(r"[₀₁₂₃₄₅₆₇₈₉\-]", "", word)
if stripped and stripped.isascii() and stripped.isupper() and len(stripped) > 1:
# This is a Sumerogram — skip it
return word, ipa, False
return word, ipa, True
def rule_final_ascii_g_sweep(ipa: str, iso: str) -> str:
"""Rule 9: Replace any remaining ASCII g (U+0067) with IPA ɡ (U+0261) in IPA column.
This is a catch-all safety net applied to ALL Phase 8 languages.
After map fixes, any ASCII g that persists in IPA is incorrect.
"""
return ipa.replace("g", "\u0261")
def cleanup_file(iso: str, dry_run: bool = False) -> dict:
"""Apply all cleanup rules to a single TSV file."""
tsv_path = LEXICON_DIR / f"{iso}.tsv"
if not tsv_path.exists():
logger.warning("File not found: %s", tsv_path)
return {"iso": iso, "status": "not_found"}
with open(tsv_path, "r", encoding="utf-8") as f:
lines = f.readlines()
has_header = lines and lines[0].startswith("Word\t")
data_lines = lines[1:] if has_header else lines
entries = []
total = 0
cleaned = 0
removed = 0
for line in data_lines:
line = line.rstrip("\n\r")
if not line.strip():
continue
parts = line.split("\t")
if len(parts) < 6:
while len(parts) < 6:
parts.append("-")
word = parts[0]
ipa = parts[1]
sca = parts[2]
source = parts[3]
concept_id = parts[4]
cognate_set_id = parts[5]
total += 1
original_word = word
original_ipa = ipa
# Apply Word-column rules
word = rule_lowercase_word(word, iso)
word, ipa, keep = rule_strip_sumerograms(word, ipa, iso)
if not keep:
removed += 1
continue
# Apply IPA-column rules (order matters)
ipa = rule_strip_cyrillic_homoglyphs(ipa, iso)
ipa = rule_strip_parentheses(ipa, iso)
ipa = rule_strip_structural_markers(ipa, iso)
ipa = rule_strip_ascii_colon(ipa, iso)
ipa = rule_strip_dots(ipa, iso)
ipa = rule_fix_doubled_consonants(ipa, iso)
ipa = rule_final_ascii_g_sweep(ipa, iso)
# Strip excess whitespace
ipa = ipa.strip()
word = word.strip()
# Skip empty entries
if not word or not ipa:
removed += 1
continue
if word != original_word or ipa != original_ipa:
cleaned += 1
entries.append({
"word": word,
"ipa": ipa,
"sca": sca,
"source": source,
"concept_id": concept_id,
"cognate_set_id": cognate_set_id,
})
result = {
"iso": iso,
"total": total,
"kept": len(entries),
"cleaned": cleaned,
"removed": removed,
"status": "dry_run" if dry_run else "written",
}
if not dry_run and entries:
with open(tsv_path, "w", encoding="utf-8") as f:
f.write(HEADER)
for e in entries:
f.write(
f"{e['word']}\t{e['ipa']}\t{e['sca']}\t"
f"{e['source']}\t{e['concept_id']}\t{e['cognate_set_id']}\n"
)
return result
def main():
parser = argparse.ArgumentParser(description="Phase 8 audit cleanup")
parser.add_argument("--dry-run", action="store_true",
help="Show changes without writing files")
parser.add_argument("--language", "-l",
help="Process only this ISO code")
args = parser.parse_args()
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s %(levelname)s: %(message)s",
datefmt="%H:%M:%S",
)
if args.language:
languages = [args.language]
else:
languages = PHASE8_LANGUAGES
mode = "DRY RUN" if args.dry_run else "LIVE"
print(f"{'=' * 60}")
print(f"Phase 8 Audit Cleanup ({mode})")
print(f"Languages: {len(languages)}")
print(f"{'=' * 60}")
print()
print(f"{'ISO':15s} {'Total':>6s} {'Cleaned':>8s} {'Removed':>8s}")
print("-" * 45)
results = []
for iso in languages:
result = cleanup_file(iso, dry_run=args.dry_run)
results.append(result)
if result["status"] == "not_found":
print(f"{iso:15s} NOT FOUND")
else:
print(
f"{iso:15s} {result['total']:6d} "
f"{result['cleaned']:8d} "
f"{result['removed']:8d}"
)
print()
print(f"{'=' * 60}")
total_entries = sum(r.get("total", 0) for r in results)
total_cleaned = sum(r.get("cleaned", 0) for r in results)
total_removed = sum(r.get("removed", 0) for r in results)
print(f" Total entries: {total_entries}")
print(f" Total cleaned: {total_cleaned}")
print(f" Total removed: {total_removed}")
print(f"{'=' * 60}")
if __name__ == "__main__":
main()