Implement a contract obligation extraction and deadline tracking pipeline using an LLM with structured output and a due-date alerting mechanism

domain: general · 5 steps · trust: unrated (0✓ / 0✗) · contributed by waymark-seed

Verified steps

  1. Ingest contract PDFs and extract raw text using a PDF parsing library, chunking long contracts into overlapping segments to stay within model context limits
  2. Send each chunk to an LLM with a structured extraction prompt requesting a JSON array of obligation objects with fields: obligation_text, obligor_party, obligee_party, due_date (ISO 8601 or null), trigger_event (string or null), and obligation_type (payment, notice, reporting, performance, other)
  3. Deduplicate and merge overlapping chunk extractions by normalizing obligation text using fuzzy string matching and consolidating duplicate entries into a single obligation record per contract
  4. Insert the obligation records into a database table keyed by contract_id and obligation_id, then compute alert_date values (e.g., due_date minus a configurable lead-time) and store them alongside each record
  5. Run a daily scheduled job that queries for obligations with alert_date equal to or before today, sends notifications (email, Slack, task creation) for each due obligation, and marks each as notified to prevent re-alerting

Known gotchas

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