- A
Use Azure AI Search with a custom skill to extract the governing law field
Custom skills can extract specific fields for indexing.
- B
Use Azure AI Search with vector search
Why wrong: Vector search is for similarity, not exact field extraction.
- C
Use Azure AI Search with a built-in skillset for OCR
Why wrong: OCR extracts text but does not create a separate field.
- D
Use Azure AI Search with full-text search on the extracted text
Why wrong: Full-text search cannot filter by a specific field reliably.
Question 56 of 993
Implement knowledge mining and information extraction solutions →mediumMultiple ChoiceObjective-mapped
AI-102 Practice Question: Implement knowledge mining and information extraction solutions
This AI-102 practice question tests your understanding of implement knowledge mining and information extraction solutions. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
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?
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
✓
Use Azure AI Search with a custom skill to extract the governing law field
Azure AI Search custom skills allow you to invoke external processing (e.g., a custom model or logic) to extract specific fields like 'governing law' from PDF content. Since the contracts are stored as PDFs in Blob Storage, you would first use OCR or text extraction (via built-in skills) to get raw text, then a custom skill to parse and extract the structured field. This enables precise queries such as 'find all contracts where the governing law is New York' using a filter on that extracted field.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Use Azure AI Search with a custom skill to extract the governing law field
Why this is correct
Custom skills can extract specific fields for indexing.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use Azure AI Search with vector search
Why it's wrong here
Vector search is for similarity, not exact field extraction.
- ✗
Use Azure AI Search with a built-in skillset for OCR
Why it's wrong here
OCR extracts text but does not create a separate field.
- ✗
Use Azure AI Search with full-text search on the extracted text
Why it's wrong here
Full-text search cannot filter by a specific field reliably.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse built-in skills (like OCR) with the ability to extract specific fields, forgetting that custom skills are required for domain-specific field extraction beyond simple text or entity recognition.
Trap categories for this question
Similar concept trap
Vector search is for similarity, not exact field extraction.
Detailed technical explanation
How to think about this question
Under the hood, Azure AI Search custom skills are implemented as HTTP endpoints (e.g., Azure Functions or Logic Apps) that receive a JSON payload with the document's content and return extracted fields. The skill set pipeline processes documents in order: first, a built-in OCR or text extraction skill converts PDF to text, then the custom skill parses the text (e.g., using regex or a trained NER model) to identify and output the 'governing law' field. This field is then indexed as a filterable, searchable field, enabling efficient OData filter queries like `$filter=governing_law eq 'New York'`.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
Quick reference
Azure Blob Storage Tier Comparison
| Tier | Storage Cost | Retrieval Cost | Latency | Use Case |
|---|---|---|---|---|
| Hot | Highest | Lowest | Immediate | Active data, frequent reads |
| Cool | Lower | Higher | Immediate | Data accessed < once / month |
| Cold | Lower still | Higher | Immediate | Data accessed < once / quarter |
| Archive | Lowest | Highest + rehydration delay | Hours | Long-term compliance retention |
What to study next
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FAQ
Questions learners often ask
What does this AI-102 question test?
Implement knowledge mining and information extraction solutions — This question tests Implement knowledge mining and information extraction solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use Azure AI Search with a custom skill to extract the governing law field — Azure AI Search custom skills allow you to invoke external processing (e.g., a custom model or logic) to extract specific fields like 'governing law' from PDF content. Since the contracts are stored as PDFs in Blob Storage, you would first use OCR or text extraction (via built-in skills) to get raw text, then a custom skill to parse and extract the structured field. This enables precise queries such as 'find all contracts where the governing law is New York' using a filter on that extracted field.
What should I do if I get this AI-102 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
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Last reviewed: Jul 4, 2026
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