glam/SESSION_COMPLETE_ARGENTINA_ENRICHMENT.txt
2025-11-19 23:25:22 +01:00

112 lines
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ARGENTINA CONABIP WIKIDATA ENRICHMENT - SESSION COMPLETE
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Date: November 17, 2025
Status: ✅ SUCCESS
Duration: ~1.5 hours
ACCOMPLISHMENTS
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✅ Wikidata enrichment script created (scripts/enrich_argentina_wikidata.py)
✅ Full dataset processed (288 institutions in 6 minutes)
✅ 21 institutions enriched with Wikidata Q-numbers (7.3% rate)
✅ Complete documentation generated
✅ Ready for LinkML YAML export
KEY RESULTS
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Total Institutions: 288
Wikidata Q-numbers: 21 (7.3%)
+ VIAF IDs: 1
+ Websites: 13
+ Founding dates: 15
Geographic coverage: 284/288 (98.6%) with coordinates
Service metadata: 178/288 (61.8%) with services
Provinces covered: 22 (all Argentine provinces)
ENRICHED INSTITUTIONS (Sample)
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• Biblioteca Popular Cornelio Saavedra → Q58406890 (100% match)
• Biblioteca Popular Florentino Ameghino → Q17622826 (100% match)
• Biblioteca Popular del Paraná → Q5727856 (100% match)
• Biblioteca Popular Bartolomé Mitre → Q57777791 (100% match)
• Biblioteca Popular José Enrique Rodó → Q57781295 (89% match)
WHY 7.3% ENRICHMENT RATE?
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This is EXPECTED and APPROPRIATE:
• CONABIP libraries are small community institutions
• Wikidata has only 168 Argentine libraries total
• We prioritized QUALITY over quantity (85% threshold)
• Zero synthetic/fake Q-numbers (follows project policy)
• 267 libraries could be added to Wikidata (future opportunity)
FILES CREATED
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Main Script:
scripts/enrich_argentina_wikidata.py (300 lines)
Enriched Data:
data/isil/AR/conabip_libraries_wikidata_enriched.json (207 KB)
Logs:
data/isil/AR/wikidata_enrichment_full_log.txt (50 KB)
Documentation:
docs/sessions/SESSION_SUMMARY_ARGENTINA_WIKIDATA_ENRICHMENT.md
NEXT_SESSION_HANDOFF.md (updated)
scripts/check_argentina_enrichment_status.sh (monitoring)
TECHNICAL HIGHLIGHTS
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• SPARQL query fetches 168 Argentine libraries from Wikidata
• Fuzzy matching: 3 strategies (ratio, partial, token_set)
• Geographic validation (city + province matching)
• 85% match threshold (quality-first approach)
• Rate limiting: 1 second per query
• City normalization (CABA → Buenos Aires)
NEXT STEPS (Choose One)
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Option 1: Export to LinkML YAML ⭐ RECOMMENDED
- Convert JSON to LinkML-compliant YAML instances
- Use existing parser: src/glam_extractor/parsers/argentina_conabip.py
- Generate batches of 50 institutions each
- Estimated time: 1-2 hours
Option 2: Create Wikidata Entries
- Add 267 missing libraries to Wikidata
- Use MCP Wikidata authenticated server
- Estimated time: 3-4 hours
Option 3: Integration Testing
- Merge with global GLAM dataset
- Validate GHCID uniqueness
- Generate statistics and visualizations
- Estimated time: 2-3 hours
QUICK START FOR NEXT SESSION
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cd /Users/kempersc/apps/glam
# Check status
bash scripts/check_argentina_enrichment_status.sh
# View enriched data
python3 -c "
import json
data = json.load(open('data/isil/AR/conabip_libraries_wikidata_enriched.json'))
enriched = sum(1 for i in data['institutions']
if any(id.get('identifier_scheme') == 'Wikidata'
for id in i.get('identifiers', [])))
print(f'Enriched: {enriched}/288 institutions')
"
# Read handoff document
cat NEXT_SESSION_HANDOFF.md
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STATUS: Ready for LinkML YAML export
BLOCKING ISSUES: None
DEPENDENCIES: All scripts and data files in place
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