Exam AI-103 Topic 1 Question 3 Discussion
Actual exam question for Microsoft's AI-103 exam
Question #: 3
Topic #: 1
Question #: 3
Topic #: 1
You have an Azure AI Search indexer that ingests PDF policy manuals.
Client applications must display page-level citations that have bounding polygons for both text and images.
You need to add a single built-in multimodal content extraction skill to the Azure AI Search skillset. The solution must meet the following requirements:
- Provide text and image location metadata.
- Extract tables that span multiple pages.
What should you add?
Client applications must display page-level citations that have bounding polygons for both text and images.
You need to add a single built-in multimodal content extraction skill to the Azure AI Search skillset. The solution must meet the following requirements:
- Provide text and image location metadata.
- Extract tables that span multiple pages.
What should you add?
Suggested Answer: B Vote an answer
To meet all requirements for this project, you need the Azure Content Understanding skill (integrated via Azure AI Foundry / Microsoft Foundry Tools).
1. Extracting Cross-Page Tables: A critical constraint is the ability to recognize and extract tables that span multiple pages as a single unit. The Azure Content Understanding skill natively supports this capability, whereas the older Document Layout skill outputs layout content as flattened text/markdown boundaries that break across pages, leading to information loss.
2. Page-Level Bounding Polygons: It functions as a layout-aware, built-in multimodal content extraction skill that maps out text and image location metadata (location_metadata), satisfying your client application requirement for strict page-level citation boundaries.
Reference:
https://learn.microsoft.com/en-us/azure/search/cognitive-search-skill-content-understanding
1. Extracting Cross-Page Tables: A critical constraint is the ability to recognize and extract tables that span multiple pages as a single unit. The Azure Content Understanding skill natively supports this capability, whereas the older Document Layout skill outputs layout content as flattened text/markdown boundaries that break across pages, leading to information loss.
2. Page-Level Bounding Polygons: It functions as a layout-aware, built-in multimodal content extraction skill that maps out text and image location metadata (location_metadata), satisfying your client application requirement for strict page-level citation boundaries.
Reference:
https://learn.microsoft.com/en-us/azure/search/cognitive-search-skill-content-understanding
by Orville at Sep 22, 2026, 09:25 AM
0
0
0
10
Comments
Upvoting a comment with a selected answer will also increase the vote count towards that answer by one. So if you see a comment that you already agree with, you can upvote it instead of posting a new comment.
Report Comment
Commenting
You can sign-up / login (it's free).