Silent Record Loss in Document Extraction Pipelines and How to Fix It
TangeloOk9486 · reddit · 2026-08-23
A common pitfall in document extraction pipelines (e.g., invoices, reports) is silent record loss. While small files process cleanly, large documents often result in the extractor silently under-returning rows. Precision remains high (extracted values are correct), but a chunk of records is missing without raising any errors or logs.
The Trap:
- Missing records are indistinguishable from a document that simply has fewer rows.
- Discrepancies are usually only caught during downstream reconciliation.
The Fix:
- Implement a completeness check rather than relying solely on the model.
- Chunk the document by section, extract each chunk, and reconcile expected vs. returned record counts.
- Fail loudly if the count falls short of the bound.
- Use parsers like LlamaParse that provide per-field grounding for verification.
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