AI-102 Practice Test 38 — 15 Questions

Question 1

You run the PowerShell script above to call the Text Analytics API. The response shows a sentiment label of 'positive' with a score of 0.99. However, you expected 'negative' because the word 'excellent' was meant to be sarcastic. What is the most likely reason for this result?

Accepted Answer

The model does not detect sarcasm and interprets the text literally.. Option A is correct because the Text Analytics API does not inherently detect sarcasm; it analyzes literal sentiment. Option B is wrong because the API does handle negation. Option C is wrong because the language parameter is correctly set. Option D is wrong because the API version is stable.

Answer

The score threshold for negative sentiment is too high.

Answer

The language parameter is set incorrectly.

Answer

The API version does not support sentiment analysis.

Question 2

You are designing a solution that must extract personally identifiable information (PII) from medical records stored in Azure Blob Storage. The solution must redact the PII before storing the results. Which combination of Azure services should you use?

Accepted Answer

Use Azure AI Language's PII detection feature and a custom Azure Function to redact.. Option A is correct because Azure AI Language's PII detection can detect PII, and a custom function can redact it. Option B is incorrect because Azure AI Search does not redact. Option C is incorrect because Text Analytics for Health does not redact. Option D is incorrect because Azure OpenAI may not have built-in redaction.

Answer

Use Azure AI Search with cognitive skills for PII detection.

Answer

Use Azure OpenAI to detect and redact PII.

Answer

Use Text Analytics for Health and then manually redact.

Question 3

Which TWO Azure AI services can be used to perform sentiment analysis on text?

Accepted Answer

Azure AI Language. Azure AI Language is the primary service for sentiment analysis. Azure AI Translator can also detect sentiment as part of its translation capabilities. Azure AI Search and Azure AI Bot Service do not perform sentiment analysis natively.

Answer

Azure AI Search

Answer

Azure AI Bot Service

Answer

Azure AI Content Safety

Question 4

Your team uses Azure AI Language in a multi-region architecture. You need to ensure that the solution is resilient to regional outages. Which THREE actions should you take?

Accepted Answer

Use a global endpoint that routes to the nearest region. Deploying resources in multiple regions, using a load balancer to distribute traffic, and using a global endpoint provide high availability. Single region and disabling regional endpoints do not improve resilience.

Answer

Disable regional endpoints

Answer

Use a single region with high availability enabled

Question 5

You need to translate a large batch of documents from English to multiple languages. Which Azure service should you use?

Accepted Answer

Azure AI Translator. Azure AI Translator is the correct service for text translation. Speech Translation is for real-time speech. Language Detection identifies language. CLU is for intents.

Answer

Conversational Language Understanding

Answer

Azure AI Language Detection

Answer

Azure AI Speech Translation

Question 6

You are developing a multilingual chatbot that must understand user intents in English, Spanish, and French. You are using the Azure AI Language service with a Conversational Language Understanding (CLU) project. What is the recommended approach to handle multiple languages?

Accepted Answer

Add utterances in all three languages to the CLU project and enable multi-lingual detection.. Option C is correct because you should add utterances in all target languages to the CLU project and enable multi-lingual detection. Option A is wrong because separate projects per language are not recommended; CLU supports multi-lingual models. Option B is wrong because translating on the fly increases complexity and may not capture nuances. Option D is wrong because the Translator service does not understand intents.

Answer

Use Azure AI Translator to translate all input to English before sending to CLU.

Answer

Use the Translator service to detect language and route to language-specific CLU endpoints.

Answer

Create separate CLU projects for each language.

Question 7

You need the project to support English, Spanish, and French. What change should you make to the command?

Accepted Answer

Change --multilingual false to --multilingual true.. Option B is correct because setting --multilingual true enables the project to support multiple languages. Option A is wrong because the language parameter specifies the primary language, but multilingual must be enabled. Option C is wrong because the description does not affect language support. Option D is wrong because the project name is irrelevant to language support.

Answer

Change --language to "multi".

Answer

Add --description "Multi-language support".

Answer

Change --project-name to "SupportBotML".

Question 8

You are using Azure AI Language to analyze customer reviews. You need to identify specific aspects (e.g., 'price', 'service') and their associated sentiment. Which feature should you use?

Accepted Answer

Aspect-based sentiment analysis. Option D is correct because Aspect-based sentiment analysis (ABSA) identifies aspects and their sentiment. Option A is wrong because standard sentiment analysis gives overall sentiment. Option B is wrong because key phrase extraction identifies phrases but not sentiment. Option C is wrong because opinion mining is a subset of ABSA; ABSA is the correct feature name.

Answer

Opinion Mining

Answer

Sentiment Analysis

Answer

Key Phrase Extraction

Question 9

A company is building a chatbot using Azure AI Language. The chatbot must understand user intents and extract entities like dates and locations. The solution should minimize manual labeling effort. Which feature should the team use?

Accepted Answer

CLU prebuilt entity components. Option C is correct because the CLU prebuilt entity components can automatically recognize common entities like dates and locations without custom labeling. Option A is wrong because Orchestration Workflow routes to different projects but does not extract entities. Option B is wrong because prebuilt intents cover common intents, not entities. Option D is wrong because QnA Maker is for FAQ, not intent/entity extraction.

Answer

Conversational Language Understanding (CLU) Orchestration Workflow

Answer

CLU prebuilt intents

Answer

Azure AI QnA Maker

Question 10

You are designing an NLP solution to analyze legal documents. The solution must identify specific clauses and parties involved. Which Azure AI service is most appropriate?

Accepted Answer

Custom Named Entity Recognition in Azure AI Language. Option B is correct because Custom NER allows you to train a model to recognize custom entities like clauses and parties. Option A is incorrect because pre-built NER only recognizes common entities. Option C is incorrect because text analytics for health is focused on medical data. Option D is incorrect because the Immersive Reader is for reading support, not entity extraction.

Answer

Pre-built Named Entity Recognition in Azure AI Language

Answer

Text Analytics for Health

Answer

Immersive Reader

Question 11

You are testing a Conversational Language Understanding application. You send the JSON request shown in the exhibit. What is the purpose of this request?

Accepted Answer

Analyze the utterance for intent and entities.. Option D is correct because the request is analyzing a conversation utterance to detect intent and entities. Option A is incorrect because it's not translating. Option B is incorrect because it's not summarizing. Option C is incorrect because it's not generating a response.

Answer

Translate the text to another language.

Answer

Generate a response to the user.

Answer

Summarize the conversation.

Question 12

A PowerShell script (exhibit) attempts to update the endpoint for an Azure AI Language resource. What is the outcome of running this script?

Accepted Answer

The script fails because the property does not exist. The property path 'apiProperties.textAnalytics.documentEndpoint' is incorrect. The correct property for custom endpoint is not modifiable via this method; the script will fail because the property does not exist. The endpoint is set during creation and cannot be changed this way.

Answer

The script creates a new resource

Answer

The script changes the API version

Answer

The script updates the endpoint successfully

Question 13

You are deploying a custom Named Entity Recognition (NER) model using Azure AI Language. You have 500 labeled documents. After training, the model shows high precision but low recall. Which action is most likely to improve recall?

Accepted Answer

Add more labeled examples covering the missed entities. Low recall means many true entities are missed. Adding more labeled examples that include the missed entities helps the model learn to recognize them. Increasing training epochs may lead to overfitting. Changing the model to a different type (e.g., CLU) is not appropriate for NER. Reducing the confidence threshold would allow more predictions but could lower precision, and the question targets recall specifically.

Answer

Switch to Conversational Language Understanding

Answer

Reduce the confidence threshold for entity extraction

Answer

Increase the number of training epochs

Question 14

Refer to the exhibit. You send this request to the Conversational Language Understanding API. The response includes the intent 'BookFlight' with entities 'FromCity: Seattle' and 'ToCity: Boston', but the 'Date' entity is missing. What is the most likely cause?

Accepted Answer

The model was not trained to recognize date entities. The utterance includes 'next Tuesday' but the model might not have been trained with date entities or the date entity is not defined in the schema. The API request looks correct. The missing date is not due to a different endpoint or API version.

Answer

The stringIndexType should be 'Utf16CodeUnit'

Answer

The API version does not support entity extraction

Answer

The endpoint is pointing to the wrong deployment

Question 15

Your organization has a large corpus of legal documents that need to be analyzed for specific clauses. You need to extract key information such as party names, dates, and monetary amounts. The solution must be able to handle varying document formats (PDF, Word, scanned images). Which combination of Azure AI services should you use?

Accepted Answer

Azure AI Document Intelligence and Custom Entity Extraction. Option D is correct because Document Intelligence (formerly Form Recognizer) extracts text from documents (including scanned images), and Custom Entity Extraction in Azure AI Language extracts the needed entities. Option A is wrong because Translator is for translation, not extraction. Option B is wrong because Computer Vision can read text but does not extract custom entities. Option C is wrong because Speech is for audio, not documents.

Answer

Azure AI Computer Vision and Custom Entity Extraction

Answer

Azure AI Translator and Custom Entity Extraction

Answer

Azure AI Speech and Custom Entity Extraction

AI-102 Practice Test 38 — 15 Questions

Exhibit

AI-102 Practice Test 38 — 15 Questions

Exhibit