Quiz lié à un guide · Moyen Niveau

Quiz sur l'IA sur les documents

Testez l'OCR et l'ordre de lecture, les unités du tableau, la provenance des champs, les erreurs de type valide, les valeurs manquantes, les limites de confiance et la confidentialité des documents.

Chemins de guidage associésDocumenter l'IA
Question 1 de 8

A scanned invoice has no usable text layer. Which step can make its characters machine-readable?

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Les réponses et les explications apparaissent au fur et à mesure que vous répondez au quiz.

  1. A scanned invoice has no usable text layer. Which step can make its characters machine-readable?
    • Only changing the PDF filename
    • Only adding a category label
    • Only searching its metadata
    • Optical character recognition, with later verification
  2. A PDF has a text layer but two columns read in the wrong order. What is still needed?
    • Layout-aware interpretation of reading order
    • Another OCR pass guarantees the order
    • A larger font in the output
    • Only the document’s page count
  3. A table column says “Revenue, thousands of USD” and the row value is 250. What is the interpreted USD amount?
    • 250 USD regardless of heading
    • 25,000 USD by default
    • 250,000 USD if the heading applies to the row
    • The number cannot have units
  4. An extracted total is a valid number but has a misplaced decimal point. Which check can catch it?
    • Check only the numeric JSON type
    • Compare with the source and related arithmetic
    • Trust OCR confidence as proof
    • Ignore the source once parsing succeeds
  5. A required field is absent from a form. How should the system represent it?
    • As missing or explicitly unknown, not a plausible invented value
    • Guess from a similar prior form
    • Fill it with the most common value silently
    • Treat absence as evidence of zero
  6. Which record helps a reviewer check an extracted value?
    • Only a final summary with no source link
    • Only the model checkpoint size
    • Only the file upload timestamp
    • Page number, source text and bounding location
  7. Why does high OCR confidence not prove a complete extracted record is correct?
    • OCR confidence guarantees all table structure
    • Layout, row association and meaning may still be wrong
    • Every recognized word is a verified fact
    • The record has no fields
  8. What privacy scope should a document AI pipeline include?
    • Only the original PDF, not extracted data
    • Only the screen used to view the file
    • Original files plus derived text, embeddings and retention paths
    • Only the person who uploaded it