Your Extraction Is 98% Accurate. One Document in Three Still Needs a Human.

Описание и применение

Высокая точность по полям не гарантирует, что документы обрабатываются без ошибок. Внедрение детерминированных правил проверки и отслеживания происхождения данных повышает пропускную способность и снижает необходимость ручного вмешательства.

Задача

Document extraction demos often report high per‑field accuracy (≈98 %) but still leave a significant fraction of documents with errors, eroding real‑world productivity gains.

Результат

Implementing deterministic validation rules and provenance tracking reduces the proportion of documents requiring human intervention from ~33 % to a lower, measurable rate, improving straight‑through throughput and overall efficiency.

Рабочий процесс

• 1. Classify the incoming document (invoice, credit note, etc.).
• 2. Extract structured fields (supplier, date, invoice number, line items, tax, total).
• 3. Validate extracted data: check arithmetic consistency, master data matches, duplicate detection, and date/range rules.
• 4. Flag any inconsistencies for human review.
• 5. Post validated records into the business system, ensuring correct supplier or case linkage and no duplicates.
• 6. Maintain provenance metadata (page, bounding box) for each field to aid review and debugging.

Доказательства

Accuracy figures are almost always quoted per field. Your users experience the system per document.

Источник

If each of twenty fields is right 98 times out of 100, the chance that every field on a document is right is 0.98 to the power of 20, which is about 0.67.

Источник

The strong signal is checking extracted values against things you already know.

Источник

Keep provenance on every field.

Источник