Microsoft Azure AI Engineer Associate AI-102 Practice Question
You are configuring a skillset in Azure AI Search to index scanned PDF contracts stored in Azure Blob Storage. The pipeline must extract each table as structured data, detect and store embedded images, and identify organization and person names that appear in the contract text. Which built-in skills should you add to the skillset to meet all requirements with minimal custom development?
DocumentIntelligenceLayoutSkill, EntityRecognitionSkill, and ImageAnalysisSkill
OCRSkill, KeyPhraseExtractionSkill, and MergeSkill
DocumentExtractionSkill, EntityRecognitionSkill, and ImageAnalysisSkill
WebApiSkill that calls the Document Intelligence Analyze Document REST API, plus EntityRecognitionSkill
DocumentIntelligenceLayoutSkill calls the Azure AI Document Intelligence layout model, which returns document structure that includes tables and can extract embedded images when the extractionOptions parameter includes "images" . EntityRecognitionSkill performs named-entity recognition and returns organizations and people found in the text . ImageAnalysisSkill analyses each extracted image and can generate captions, tags, or object metadata; it also works on images embedded in PDFs . Together, these three built-in skills satisfy all stated requirements without writing custom code. DocumentExtractionSkill cannot provide table structure , and using a WebApiSkill would require custom implementation.
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How does the DocumentIntelligenceLayoutSkill extract tables and images from PDF documents?
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What is the purpose of the EntityRecognitionSkill in this pipeline?
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What insights does the ImageAnalysisSkill provide for embedded images?
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Microsoft Azure AI Engineer Associate AI-102
Implement knowledge mining and information extraction solutions
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