AI-103 Text Analysis Practice Test 4 — 15 Questions

Question 1

You need to detect the language of a batch of text documents and want to minimize the number of API calls. What is the maximum number of documents you can include in a single request payload to the language detection endpoint?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

10 documents. Azure AI Language batch APIs typically support up to 10 documents per synchronous request payload.

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1 document

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1,000 documents

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100,000 documents

Question 2

You are configuring an Azure AI Language service resource in the Azure portal. Which THREE settings or blades are available for managing the resource? (Choose three.)

Accepted Answer

Keys and Endpoint. In the Azure portal, resource management blades for Azure AI Language include Keys and Endpoint, Pricing tier, and Identity (managed identities). Diagnostic settings and Access control are also standard Azure resource blades.

Answer

Virtual machine size selector

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Container registry integration blade

Question 3

You are developing an application that uses the Azure AI Language REST API for text analysis. Which TWO requirements must be met when constructing HTTP requests to the service? (Choose two.)

Accepted Answer

Set the 'Content-Type' header to 'application/json'.. Requests to Azure AI Language require the Ocp-Apim-Subscription-Key header (or token authorization) and the Content-Type header set to application/json.

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Format all request payloads as XML documents.

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Include the master account password in the request query string.

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Authenticate exclusively using HTTP Basic Authentication with username and password.

Question 4

You need to ensure data privacy and compliance when processing user feedback containing sensitive information. Which TWO types of sensitive data can Azure AI Language PII detection identify and redact? (Choose two.)

Accepted Answer

Phone numbers. PII detection identifies personal data such as email addresses and phone numbers.

Answer

Weather forecast coordinates

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Source code syntax errors

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CPU utilization metrics

Question 5

You are configuring custom named entity recognition in Language Studio. Which TWO types of entity components can you configure when defining custom entities? (Choose two.)

Accepted Answer

Regex component. Custom NER projects support Learned entity components (trained from labeled data) and Regex or List components for exact pattern or dictionary matching.

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Quantum computation component

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Neural speech synthesis component

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Optical character recognition component

Question 6

You are planning a text analytics pipeline that uses asynchronous batch operations. Which THREE text analysis tasks support asynchronous long-running batch operations in Azure AI Language? (Choose three.)

Accepted Answer

Health text analytics. Asynchronous batch operations are supported for text summarization, extractive summarization, health text analytics, and custom classification/NER tasks where large volumes of documents are processed.

Answer

Simple key phrase extraction

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Language detection

Question 7

You are exploring Azure AI Language features. Which TWO tasks can be accomplished using prebuilt named entity recognition (NER)? (Choose two.)

Accepted Answer

Extracting person names from text. Prebuilt NER recognizes standard entities such as dates, times, people, and locations.

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Detecting the written language of a document

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Redacting credit card numbers for security

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Classifying entire documents into custom business categories

Question 8

You are building an application to process customer reviews. Which TWO metrics are returned in the standard JSON response of a sentiment analysis document evaluation? (Choose two.)

Accepted Answer

Overall document sentiment label. Sentiment analysis document responses return the overall sentiment label and confidence scores (positive, neutral, negative).

Answer

Estimated reading time in minutes

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Detected language translation confidence score

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Total word count of the document

Question 9

You are designing an enterprise text analysis solution with high availability and security requirements. Which THREE practices should you implement? (Choose three.)

Accepted Answer

Implement exponential backoff retry logic in client applications to handle rate limiting (429 errors).. Enterprise best practices include deploying private endpoints, using managed identities for authentication, and implementing retry logic with exponential backoff for resilience.

Answer

Store subscription keys in plain text configuration files inside the source code repository.

Answer

Disable TLS encryption on HTTP client requests to improve API throughput.

Question 10

You are troubleshooting an Azure AI Language resource deployment. Which THREE error codes or HTTP status codes might indicate an issue with your API request structure or payload? (Choose three.)

Accepted Answer

404 Not Found. HTTP 400 (Bad Request) indicates malformed JSON or invalid parameters, HTTP 404 indicates an incorrect endpoint URL, and HTTP 422 indicates unprocessable data. HTTP 200 is success.

Answer

100 Continue

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200 OK

Question 11

You are configuring text summarization using the Azure AI Language REST API. Which THREE parameters or configuration options are associated with summarization requests? (Choose three.)

Accepted Answer

maxSentenceCount parameter. Summarization requests involve specifying the task type (e.g., extractive or abstractive), setting summary length parameters (like maxSentenceCount or maxSummaryLength), and providing document inputs.

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Audio sample rate frequency

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Image resolution DPI setting

Question 12

You are evaluating the performance of a custom text classification model in Language Studio. Which THREE evaluation metrics are provided to assess model quality? (Choose three.)

Accepted Answer

F1-score. Custom text classification models are evaluated using Precision, Recall, and F1-score metrics.

Answer

HTTP request latency in milliseconds

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CPU utilization percentage

Question 13

You are preparing training data for a custom named entity recognition (NER) project in Language Studio. Which THREE guidelines should you follow to ensure high model accuracy? (Choose three.)

Accepted Answer

Ensure consistent and accurate tagging of entities across all training documents.. Best practices for custom NER training data include providing a diverse set of documents, ensuring consistent tagging across all instances, and maintaining sufficient sample counts per entity type.

Answer

Use exactly one training document for the entire project.

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Tag every single word in every document as an entity.

Question 14

You need to extract key concepts from customer feedback. Which TWO characteristics describe key phrase extraction in Azure AI Language? (Choose two.)

Accepted Answer

It works well on unstructured text documents.. Key phrase extraction identifies main concepts, works on unstructured text, and returns a list of strings without requiring pre-defined taxonomies.

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It evaluates the emotional tone of sentences.

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It requires a pre-defined taxonomy of thousands of categories.

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It automatically translates documents into English.

Question 15

You are designing an architecture that processes incoming multilingual support emails using Azure AI Language. Which THREE processing steps should you include in your pipeline? (Choose three.)

Accepted Answer

Execute named entity recognition to extract relevant organizations, locations, and names.. A robust multilingual pipeline typically detects the language first, routes or translates if needed, and then applies text analysis tasks such as sentiment analysis, PII redaction, or entity recognition.

Answer

Train a new speech-to-text acoustic model for every email received.

Answer

Convert all email text into raw binary executable files before analysis.