AI-103 Text Analysis Practice Test 3 — 15 Questions

Question 1

You are reviewing the pricing details for Azure AI Language. How is billing calculated for pre-built text analysis features such as sentiment analysis and key phrase extraction?

Accepted Answer

Number of text records (documents) processed. Text analysis features are billed based on the number of text records (documents) processed, where each record is up to 1,000 characters.

Answer

Hourly uptime of the resource endpoint

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Number of unique client application connections

Answer

Total gigabytes of training data uploaded

Question 2

You are building a custom named entity recognition model in Language Studio. You want to extract product serial numbers that follow a specific pattern (two uppercase letters followed by four digits, a hyphen, and three digits). Which entity type definition method should you use?

Accepted Answer

Regex entity type. When defining custom entities with rigid patterns, you can use a 'Regex' (regular expression) component to extract items matching exact rules.

Answer

List entity type

Answer

Learned entity type

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Prebuilt entity type

Question 3

You are processing customer feedback emails that contain both English and Spanish paragraphs within the same message. You need to perform sentiment analysis on each paragraph separately. What should you do?

Accepted Answer

Split the email into individual paragraphs and submit them as separate documents in the request payload.. Because language detection and sentiment analysis operate per document, you should split the multi-lingual email into separate document chunks (or paragraphs) and specify the language parameter for each document if necessary.

Answer

Use custom text classification instead of sentiment analysis.

Answer

Submit the entire email as a single document with the language set to auto-detect.

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Translate the entire email to French before calling sentiment analysis.

Question 4

You are configuring a webhook to receive notifications when an asynchronous batch text summarization job completes in Azure AI Language. Which Azure service should you use to capture and route the webhook events to your backend function?

Accepted Answer

Azure Event Grid. Azure Event Grid is the native event routing service in Azure that integrates with Azure AI services to publish and deliver job completion events.

Answer

Azure API Management

Answer

Azure Stream Analytics

Answer

Azure Logic Apps

Question 5

You are writing a Python script using the Azure AI Language SDK (`azure-ai-textanalytics`). Which client class should you instantiate to connect to your language resource?

Accepted Answer

TextAnalyticsClient. The `TextAnalyticsClient` class is the main entry point for interacting with Azure AI Language text analysis features using the Python SDK.

Answer

LanguageServiceClient

Answer

TextAnalysisClient

Answer

CognitiveServicesClient

Question 6

You are implementing a text classification pipeline using Azure AI Language. You want to deploy your trained custom model to a production endpoint. What is required before you can assign traffic to the model deployment in Language Studio?

Accepted Answer

You must successfully complete model training and create a deployment in Language Studio.. Before a custom model can be deployed and used for inference, it must be successfully trained, and then assigned to a deployment name.

Answer

You must export the model container and deploy it to an Azure Kubernetes Service (AKS) cluster.

Answer

You must submit a support ticket to Microsoft to enable custom model endpoints.

Answer

You must convert the model files to ONNX format.

Question 7

You are developing a .NET application that analyzes customer feedback. Which NuGet package should you install to use the Azure AI Language client library in C#?

Accepted Answer

Azure.AI.TextAnalytics. The official NuGet package for Azure AI Language text analysis in .NET is `Azure.AI.TextAnalytics`.

Answer

Azure.AI.Language.Text

Answer

Microsoft.CognitiveServices.TextAnalytics

Answer

Microsoft.Azure.CognitiveServices.Language

Question 8

You are building an application that extracts named entities from technical specifications. You need to ensure that entity extraction respects casing requirements for part numbers (e.g., 'Model-X' vs 'Model-x'). Where can you configure case sensitivity for custom NER projects?

Accepted Answer

In the project settings within Language Studio during project creation.. When creating a custom NER project in Language Studio, you can specify project settings such as whether entity extraction and text evaluation should be case-sensitive or case-insensitive.

Answer

In the HTTP request headers of every API call.

Answer

In the Azure Monitor diagnostics logs.

Answer

In the Azure portal subscription access control blade.

Question 9

You are analyzing survey responses. You want to categorize each response into one of three predefined business categories ('Billing', 'Technical Support', 'General Inquiry'). Which Azure AI Language feature should you use?

Accepted Answer

Custom text classification. Custom text classification allows you to train a model to categorize documents into your own custom-defined categories.

Answer

Key phrase extraction

Answer

Extractive summarization

Answer

Prebuilt Named Entity Recognition

Question 10

You are setting up Azure AI Language. You want to authenticate your client application using Microsoft Entra ID (formerly Azure Active Directory) instead of using API subscription keys. Which role must be assigned to your application's service principal to allow it to call text analysis APIs?

Accepted Answer

Cognitive Services User. To call Azure AI Language APIs using Microsoft Entra ID, the security principal must be assigned the 'Cognitive Services User' role.

Answer

Reader

Answer

Storage Blob Data Contributor

Answer

Contributor

Question 11

You are troubleshooting a custom text classification model that exhibits high training loss and low validation accuracy, indicating severe model underfitting. What adjustment should you make to improve the model?

Accepted Answer

Increase the diversity and volume of training data and ensure model training is allowed to complete fully.. Underfitting occurs when a model is too simple or hasn't learned enough patterns. Increasing training iterations (epochs) or adding more descriptive features and training data helps resolve underfitting.

Answer

Lower the confidence score threshold to 0.01.

Answer

Reduce the training dataset size by 90%.

Answer

Switch the resource pricing tier from Standard to Free.

Question 12

You are analyzing product reviews and need to identify specific product features mentioned by users along with whether users expressed positive or negative opinions about those specific features. Which advanced feature of sentiment analysis should you enable?

Accepted Answer

Opinion mining. Opinion mining is an advanced feature of sentiment analysis that extracts aspects (targets) and their associated opinions (assessments).

Answer

Extractive summarization

Answer

Key phrase extraction

Answer

Named Entity Recognition

Question 13

You are configuring a custom named entity recognition project in Language Studio. You have tagged your training documents and want to split your dataset into training and testing sets. What are the recommended split options available in Language Studio?

Accepted Answer

Automatic split by percentage or manual assignment of documents to sets.. Language Studio allows you to automatically split your labeled dataset (e.g., 80% training / 20% testing) or manually assign documents to training and testing sets.

Answer

Splitting exclusively by alternating lines within each document.

Answer

External split configuration via an Azure DevOps pipeline YAML file.

Answer

Command-line split using Azure PowerShell scripts only.

Question 14

You are designing a customer feedback processing system. You need to extract key phrases from customer reviews and store them in an Azure Cosmos DB database. When you inspect the JSON response from the key phrase API, what data structure is returned for the key phrases?

Accepted Answer

An array of strings representing the key phrases found in the document.. The key phrase extraction response returns a list of string values representing the extracted key phrases for each document.

Answer

A single concatenated string with semicolons separating each phrase.

Answer

A nested dictionary mapping phrase weights to sentiment scores.

Answer

An array of objects containing 'text', 'category', and 'confidenceScore' properties.

Question 15

You are designing a text analysis solution using Azure AI Language. Which TWO features are available as prebuilt capabilities without requiring custom model training? (Choose two.)

Accepted Answer

Language detection. Sentiment analysis and language detection are prebuilt capabilities provided out-of-the-box by Azure AI Language without requiring custom model training. Custom text classification and custom NER require training.

Answer

Custom named entity recognition

Answer

Custom text classification

Answer

Custom summarization models