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Implement DSPy for Information Extraction

Inspect the original prompt language first, then copy or adapt it once you know how it fits your workflow.

Linked challenge: Supply Chain Compliance Agent with Adaptive Budgets

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Linked challenge
Supply Chain Compliance Agent with Adaptive Budgets

Prompt source

Original prompt text with formatting preserved for inspection.

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Using DSPy, create a robust pipeline for one of your agents (e.g., Data Gatherer or Risk Analyst) to extract key entities (vendor names, item types, countries, owner entities) and relationships from unstructured text (news articles, incident reports). Optimize the GPT-5 prompts programmatically to ensure high accuracy and resilience to variations in input data.

Adaptation plan

Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.

Keep stable

Hold the task contract and output shape stable so generated implementations remain comparable.

Tune next

Update libraries, interfaces, and environment assumptions to match the stack you actually run.

Verify after

Test failure handling, edge cases, and any code paths that depend on hidden context or secrets.