updating seeding pipeline

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lila 2026-04-05 19:29:47 +02:00
parent dfeb6a4cb0
commit e3c05b5596

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@ -1,105 +0,0 @@
"""
scripts/extract-en-it-nouns.py
Extract ALL bilingual nouns from Open Multilingual Wordnet (OMW).
Output mirrors the terms table schema exactly — no filtering, no ranking.
Decks handle curation later.
"""
import json
import os
import sys
from pathlib import Path
import wn
def extract_bilingual_nouns(
source_lang: str = "en",
target_lang: str = "it",
output_path: str = "datafiles/en-it-nouns.json",
) -> None:
"""
Extract all noun synsets present in both languages via ILI.
Args:
source_lang: Source language code (e.g., "en" for English)
target_lang: Target language code (e.g., "it" for Italian)
output_path: Where to write the seed JSON
"""
print(f"Loading WordNets: {source_lang=}, {target_lang=}")
try:
source_wn = wn.Wordnet(lang=source_lang)
target_wn = wn.Wordnet(lang=target_lang)
except wn.Error as e:
print(f"Error loading WordNet: {e}")
print(f"Run: wn download omw-{target_lang}:1.4 oewn:2024")
sys.exit(1)
# Index nouns by ILI (Inter-Lingual Index)
source_by_ili: dict[str, wn.Synset] = {}
for synset in source_wn.synsets(pos="n"):
if synset.ili:
source_by_ili[synset.ili] = synset
target_by_ili: dict[str, wn.Synset] = {}
for synset in target_wn.synsets(pos="n"):
if synset.ili:
target_by_ili[synset.ili] = synset
# Find bilingual synsets (present in both languages)
common_ilis = set(source_by_ili.keys()) & set(target_by_ili.keys())
print(f"Found {len(common_ilis):,} bilingual noun synsets")
# Build seed data matching schema exactly
terms: list[dict] = []
for ili in sorted(common_ilis, key=lambda x: int(x[1:])):
en_syn = source_by_ili[ili]
it_syn = target_by_ili[ili]
# All lemmas (synonyms) for each language
en_lemmas = [str(lemma) for lemma in en_syn.lemmas()]
it_lemmas = [str(lemma) for lemma in it_syn.lemmas()]
term = {
"synset_id": f"ili:{ili}", # e.g., "ili:i12345"
"pos": "noun",
"translations": {source_lang: en_lemmas, target_lang: it_lemmas},
# Note: id, created_at added by seed.ts during insert
}
terms.append(term)
# Ensure output directory exists
output_file = Path(output_path)
output_file.parent.mkdir(parents=True, exist_ok=True)
# Write JSON
with open(output_file, "w", encoding="utf-8") as f:
json.dump(terms, f, indent=2, ensure_ascii=False)
print(f"Wrote {len(terms):,} terms to {output_path}")
# Summary stats
total_en_lemmas = sum(len(t["translations"][source_lang]) for t in terms)
total_it_lemmas = sum(len(t["translations"][target_lang]) for t in terms)
print(f"\nLemma counts:")
print(
f" English: {total_en_lemmas:,} total ({total_en_lemmas / len(terms):.1f} avg per synset)"
)
print(
f" Italian: {total_it_lemmas:,} total ({total_it_lemmas / len(terms):.1f} avg per synset)"
)
# Sample output
print(f"\n--- Sample terms ---")
for t in terms[1000:1005]:
print(
f"{t['synset_id']}: {t['translations'][source_lang]} -> {t['translations'][target_lang]}"
)
if __name__ == "__main__":
extract_bilingual_nouns()