AI-102 · topic practice

Implement knowledge mining and information extraction solutions practice questions

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Practise Microsoft Azure AI Engineer Associate AI-102 Implement knowledge mining and information extraction solutions practice questions — original exam-style scenarios with answer choices, explanations, and analysis of common mistakes.

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20 questionsDomain: Implement knowledge mining and information extraction solutions

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What to know about Implement knowledge mining and information extraction solutions

Implement knowledge mining and information extraction solutions questions test whether you can apply the concept in context, not just recognise a definition.

How the topic appears in realistic exam-style scenarios.

Which detail in the question changes the correct answer.

How to eliminate plausible but wrong options.

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Common Implement knowledge mining and information extraction solutions exam traps

▸Answering from memory before reading the full scenario.
▸Missing a constraint such as cost, availability, security, scope or command context.
▸Choosing a broad answer when the question asks for the most specific fix.
▸Ignoring why the wrong options are tempting.

Practice set

Implement knowledge mining and information extraction solutions questions

20 questions · select your answer, then reveal the explanation

Question 1mediummultiple choice

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You are designing a knowledge mining solution for a medical research organization. The solution must extract relationships between drugs, diseases, and genes from scientific articles. The data will be stored in a knowledge graph for querying. Which Azure AI service should you use for the extraction?

Trap 1: Azure AI Search with semantic ranking

Semantic ranking improves search relevance but does not extract relationships.

Trap 2: Azure AI Translator with dictionary lookup

Translation is unrelated to relationship extraction.

Trap 3: Azure AI Document Intelligence custom extraction model

Document Intelligence extracts fields from document layouts, not semantic relationships from text.

Study all Implement knowledge mining and information extraction solutions common traps →

A
Azure AI Search with semantic ranking
Why wrong: Semantic ranking improves search relevance but does not extract relationships.
B
Azure AI Translator with dictionary lookup
Why wrong: Translation is unrelated to relationship extraction.
C
Azure AI Document Intelligence custom extraction model
Why wrong: Document Intelligence extracts fields from document layouts, not semantic relationships from text.
D
Azure AI Language healthcare entity recognition and relation extraction
Azure AI Language has specialized healthcare models for extracting entities and relationships.

Implement knowledge mining and information extraction solutions practice questions

What to know about Implement knowledge mining and information extraction solutions

Common Implement knowledge mining and information extraction solutions exam traps

Implement knowledge mining and information extraction solutions questions

Which THREE factors should you consider when designing a knowledge mining solution that uses Azure AI Search and custom skills to extract insights from large volumes of documents?

Which TWO configurations are required to enable Azure AI Search to index content from an Azure SQL database?

Your organization uses Microsoft Purview to catalog data assets. You need to enable knowledge mining on these assets to allow users to search across structured and unstructured data. Which integration should you use to connect Microsoft Purview with Azure AI Search?

You are building an Azure AI Search index that includes content from a SQL database and an Azure Cosmos DB collection. The index must support autocomplete suggestions as users type. Which TWO configurations are required to enable autocomplete?

Which TWO Azure AI Search features are used to map skill outputs to search index fields? (Select TWO.)

You are designing a knowledge mining solution for a legal firm. The solution must index contracts and support queries like 'find all contracts where the governing law is New York'. The contracts are stored as PDFs in Azure Blob Storage. Which approach should you use?

You are using Azure AI Document Intelligence to extract data from purchase orders. The purchase orders have a table of line items. Which prebuilt model should you use?

You are designing an Azure Cognitive Search solution for a legal document repository. The solution must support search across multiple languages, including English and Spanish. You need to ensure that searches return documents regardless of the language of the query. Which approach should you use?

Which TWO Azure AI Search features should you enable to improve the relevance of search results for a knowledge mining solution that supports natural language queries?

You are building a knowledge mining solution for a legal firm to extract clauses from contracts. The contracts are stored as PDFs in Azure Blob Storage. You need to design the solution to minimize cost while ensuring high accuracy for clause extraction. Which approach should you use?

You are building a knowledge mining solution to extract insights from a large set of PDF contracts. The solution must identify parties, dates, and monetary amounts. Which Azure AI service should you use as the primary extraction engine?

Your team has built a knowledge mining pipeline using Azure AI Search and Document Intelligence. After ingestion, you notice that some documents are not appearing in search results. What is the most likely cause?

You are designing a knowledge mining solution that must extract entities from scanned handwritten forms. The forms contain signatures and checkboxes. Which combination of Azure AI services should you recommend?

Your knowledge mining solution uses Azure AI Search. Users complain that search results are not relevant. You have enabled semantic search but results still lack context. What should you do to improve relevance?

You need to extract key-value pairs from a large set of invoices. The invoices have a consistent layout but vary in format (PDF, TIFF). Which Document Intelligence model should you use?

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