Question 1hardmultiple choice
Full question →hardmultiple choiceObjective-mapped
A law firm needs to process thousands of legal contracts. They want to extract specific clauses (e.g., 'confidentiality', 'indemnity') and also identify the names of parties and monetary amounts mentioned. Which Azure AI Language feature(s) should they use together to achieve both tasks?
Answer choices
Why each option matters
Good practice is not just finding the correct option. The wrong answers often show the exact trap the exam wants you to fall into.
A
Distractor review
Key phrase extraction and sentiment analysis
Key phrase extraction identifies important phrases but not specific clauses or structured entities like monetary amounts. Sentiment analysis gauges emotion, not relevant.
B
Best answer
Custom text classification and named entity recognition
Custom text classification can identify which clauses are present (e.g., confidentiality). Named entity recognition can extract parties and monetary amounts. Together they fulfill both requirements.
C
Distractor review
Entity linking and language detection
Entity linking associates entities with a knowledge base, not suitable for classifying clauses. Language detection identifies the language, not relevant.
D
Distractor review
Summarization and conversational language understanding
Summarization creates a summary but does not extract specific clauses or entities. CLU is for intent recognition in chatbots, not for contract analysis.
Common exam trap
Common exam trap: NAT rules depend on direction and matching traffic
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Technical deep dive
How to think about this question
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
KKey Concepts to Remember
- Static NAT maps one inside address to one outside address.
- PAT allows many inside hosts to share one public address using ports.
- Inside local and inside global describe the private and translated addresses.
- NAT ACLs identify traffic for translation, not always security filtering.
TExam Day Tips
- Identify inside and outside interfaces first.
- Check whether the scenario needs static NAT, dynamic NAT or PAT.
- Do not confuse NAT matching ACLs with normal packet-filtering intent.
Related practice questions
Related AI-900 practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
More questions from this exam
Keep practising from the same exam bank, or move into a focused topic page if this question exposed a weak area.
Question 1
A developer wants to build a virtual assistant that can understand user intents such as 'Book a flight' or 'Check weather' and extract relevant entities like destination and date. The developer has a small set of labeled example utterances. Which Azure AI Language feature should the developer use?
Question 2
A developer is building a customer support chatbot using Azure OpenAI. The chatbot should never reveal its system instructions or internal configuration. The developer wants to add a rule at the beginning of the conversation to prevent prompt injection attacks. Which technique should they use?
Question 3
A developer is using Azure OpenAI Service to generate product descriptions from technical specifications. The generated descriptions sometimes include plausible-sounding but incorrect details (hallucinations). The developer wants to ensure the model's responses are strictly based on the provided product data and does not add any external or invented information. Which approach should the developer use?
Question 4
A developer is using Azure OpenAI with GPT-4 to build a chatbot that answers legal questions based on a company's internal policy documents. The developer wants the model's responses to be maximally deterministic and factual, avoiding any creative or speculative language. Which parameter should the developer set to the lowest possible value in the API call?
Question 5
A developer is using Azure OpenAI to generate creative product descriptions. The outputs are often repetitive and lack variety. The developer wants to increase the diversity of the generated text while still keeping it coherent. Which parameter should the developer increase?
Question 6
A developer is using Azure OpenAI Service to generate product descriptions. They want the output to be highly focused and deterministic, with less randomness. Which parameter should they decrease?
FAQ
Questions learners often ask
What does this AI-900 question test?
Static NAT maps one inside address to one outside address.
What is the correct answer to this question?
The correct answer is: Custom text classification and named entity recognition — Custom text classification can be trained to classify entire documents or specific clauses into predefined categories. Named entity recognition (NER) extracts entities like person names, organizations, and monetary values. Combining both meets the requirement. Custom NER can be used if entity types are unique to the domain, but standard NER handles common types like monetary amounts. The question expects the combination that covers both classification and entity extraction.
What should I do if I get this AI-900 question wrong?
Then try more questions from the same exam bank and focus on understanding why the wrong options are tempting.
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