AI-102 Practice Question: Implement knowledge mining and information extraction solutions
You are designing a knowledge mining solution that ingests documents from SharePoint Online and makes them searchable using Azure AI Search. The solution must extract text from images and perform optical character recognition (OCR) on embedded images within PDFs. Which built-in skill should you include in the skillset?
⚠ Common exam trap
Candidates often confuse the OCR skill with other text-processing skills like key phrase extraction or entity recognition, mistakenly thinking those can also extract text from images, but only the OCR skill is designed for image-to-text conversion.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
OCR skill
The OCR skill (Optical Character Recognition) is the correct built-in skill for extracting text from images and performing OCR on embedded images within PDFs in Azure AI Search. It specifically handles image files (e.g., JPEG, PNG) and embedded images in PDFs, outputting text that can be indexed and searched. Other skills like translation, key phrase extraction, or entity recognition do not perform text extraction from images.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
OCR skill
Why this is correct
The OCR skill extracts text from embedded images and scanned PDF content within the enrichment pipeline, feeding recognised text downstream for indexing. It directly satisfies the requirement to perform optical character recognition on images embedded in PDFs from SharePoint Online.
- ✗
Translation skill
Why it's wrong here
The translation skill converts text between languages; it neither detects embedded images nor extracts their characters. OCR requires the built-in OCR skill, which reads text from image files and embedded PDF images. Translation is correct when ingested content is in a foreign language and must be normalised before indexing.
- ✗
Key phrase extraction skill
Why it's wrong here
Key phrase extraction identifies salient terms within already-extracted text; it cannot read characters from images or embedded PDF graphics. OCR is the skill that produces that text in the first place. Key phrase extraction is correct when you need searchable topic tags from textual content, not image text extraction.
- ✗
Entity recognition skill
Why it's wrong here
Entity recognition extracts people, places and organisations from text; it does not read pixels, so embedded images in PDFs stay unread. It is tempting because it enriches already-extracted text with structured entities, which suits knowledge mining over text-heavy documents — but the OCR skill is what converts image content into searchable text.
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Senior Network & Security Engineer · founder of Courseiva
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