Use extraction pipeline to backfill NULL metadata on existing experiment artifacts
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[Atlas] Backfill 188 experiment artifacts with structured metadata [task:atl-ex-07-BKFL]2026-04-15
[Atlas] Auto-link extracted experiments to KG entities [task:atl-ex-03-LINK]2026-04-13
[Docs] Update atl-ex-01-SCHM work log: implementation complete [task:atl-ex-01-SCHM]2026-04-13
[Atlas] Add experiment extraction constants and validate_experiment_metadata() [task:atl-ex-01-SCHM]2026-04-13
Spec File
Goal
The 188 existing experiment artifacts have titles but NULL metadata. Use the extraction pipeline to backfill them with structured experimental data, linking them to their source papers and KG entities.
Acceptance Criteria
☐ All 188 existing experiment artifacts have non-null structured metadata
☐ Each backfilled experiment linked to source paper via derives_from
☐ Extraction confidence recorded for each backfill
☐ Experiments that can't be reliably backfilled marked with low confidence
☐ Quality scores updated based on metadata completeness
☐ Before/after statistics: field completeness, link counts, quality distribution
Dependencies
atl-ex-01-SCHM — Schemas define the target structure
atl-ex-02-PIPE — Pipeline does the actual extraction
Dependents
atl-ex-03-LINK — Backfilled experiments need entity linking too
Work Log
2026-04-15 18:00 PT — Slot 50
Analyzed 188 non-PMID experiments (161 from wiki, 27 from debate_extraction)
Confirmed all 188 had NULL schema-compliant metadata (required: experiment_type, source.type, entities)
Created backfill_experiment_metadata.py script to:
1. Transform existing metadata to schema-compliant format 2. Map experiments table fields (target_gene, disease, target_pathway) to schema entities 3. Create source dict with PMID when available, 'manual' type when not 4. Record extraction confidence (0.8 with PMID, 0.4 without) 5. Calculate quality_score based on metadata completeness
Ran backfill: all 188 experiments now have schema-compliant metadata