Calibrated AidData annotation pipeline and schema review

• Day: 2026-06-28
• Time: 12:10 to 12:30
• Project: Dev
• Workspace: WP 2: Operational
• Status: Completed
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Aiddata, Promptflow, Schema-Calibration, Smoke-Test, Jsonl, Taxonomy

Description

Session Goal

Validate and streamline an AidData annotation pipeline by narrowing the input schema, generating smoke-test samples, and reviewing input/output consistency before scaling up.

Key Activities

• Reframed the smoke test to use AidData-only core columns instead of a wide mixed-World Bank CSV.
• Defined a compact calibration setup with random samples of 3, 20, and 100 rows to test the pipeline at increasing sizes.
• Specified PromptFlow wiring and reproducible preparation steps for the annotation workflow, including file creation, flow templates, static wiring checks, and cleanup guidance.
• Performed a row-by-row audit plan comparing inputs.jsonl and output.jsonl to verify schema validity, internal coherence, and substantive classification quality.
• Reviewed the smoke-test results and identified a semantic issue in the ontology: the locally_implemented taxonomy is too narrow and is being conflated with no_macro_policy / non-local cases.

Achievements

• Confirmed that the pipeline is technically functioning and the schema is valid on the smoke test.
• Clarified that the current issue is label semantics, not execution failure.
• Established that the current result should be treated as a working milestone, not final annotations.
• Identified the need for enum refinement before larger calibration batches are run.

Pending Tasks

• Refine the locally_implemented label taxonomy so it does not collapse distinct non-local / macro-policy-only cases.
• Re-run calibration on a larger batch after schema adjustments.
• Decide whether the current outputs are sufficient to share as an interim milestone or need another prompt/schema iteration first.

Evidence

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• event_ids: []