- A
Azure AI Language (custom NER)
Why wrong: Custom NER is text-based and misses layout features like tables.
- B
Azure AI Search with integrated vectorization
Why wrong: Azure AI Search is for indexing and search, not primary extraction.
- C
Azure OpenAI Service with GPT-4o
Why wrong: Overkill and higher cost; Document Intelligence is purpose-built.
- D
Azure AI Document Intelligence
Designed for extracting fields from forms and documents.
Question 620 of 993
Implement knowledge mining and information extraction solutions →mediumMultiple ChoiceObjective-mapped
How to Extract Parties, Dates, and Monetary Amounts from Contracts Using Prebuilt Models
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 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?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"primary"Why it matters: Asks for the main purpose or function, not a secondary benefit. Eliminate answers that describe side-effects or partial functions.
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
✓
Azure AI Document Intelligence
Azure AI Document Intelligence (formerly Form Recognizer) is the correct choice because it is specifically designed for document analysis and extraction of structured data such as parties, dates, and monetary amounts from PDFs and images. Its prebuilt models (e.g., the 'prebuilt-invoice' or 'prebuilt-contract' model) use optical character recognition (OCR) and deep learning to extract key-value pairs and entities from contracts without requiring custom training.
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.
- ✗
Azure AI Language (custom NER)
Why it's wrong here
Custom NER is text-based and misses layout features like tables.
- ✗
Azure AI Search with integrated vectorization
Why it's wrong here
Azure AI Search is for indexing and search, not primary extraction.
- ✗
Azure OpenAI Service with GPT-4o
Why it's wrong here
Overkill and higher cost; Document Intelligence is purpose-built.
- ✓
Azure AI Document Intelligence
Why this is correct
Designed for extracting fields from forms and documents.
Clue confirmation
The clue word "primary" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse Azure AI Language (custom NER) as a suitable choice for PDF extraction, overlooking that it requires pre-extracted text and lacks native PDF processing, while Azure AI Document Intelligence is the dedicated service for document-based extraction.
Detailed technical explanation
How to think about this question
Azure AI Document Intelligence uses a combination of layout analysis (detecting tables, paragraphs, and form fields) and prebuilt neural models trained on thousands of invoices and contracts to extract entities like 'Party', 'Date', and 'Amount' with high accuracy. Under the hood, it leverages the Read OCR API for text recognition and then applies a transformer-based model to map extracted text to semantic fields, supporting both synchronous and asynchronous batch processing for large PDF sets. In a real-world scenario, you would use the 'prebuilt-document' model or a custom extraction model if the contracts have unique layouts, ensuring compliance with legal data extraction requirements.
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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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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: Azure AI Document Intelligence — Azure AI Document Intelligence (formerly Form Recognizer) is the correct choice because it is specifically designed for document analysis and extraction of structured data such as parties, dates, and monetary amounts from PDFs and images. Its prebuilt models (e.g., the 'prebuilt-invoice' or 'prebuilt-contract' model) use optical character recognition (OCR) and deep learning to extract key-value pairs and entities from contracts without requiring custom training.
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.
Are there clue words in this question I should notice?
Yes — watch for: "primary". Asks for the main purpose or function, not a secondary benefit. Eliminate answers that describe side-effects or partial functions.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Last reviewed: Jul 4, 2026
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