AI-102 Implement natural language processing solutions Practice Test 4 — 15 Questions

Question 1

Refer to the exhibit. You are calling the Azure AI Language API for conversational language understanding (CLU). The CLU project 'SupportBot' has an intent 'CancelOrder' with an entity 'OrderNumber' of type 'Number'. The deployment 'production' is active. What is the expected output?

Accepted Answer

The response will contain the top intent 'CancelOrder' and the entity 'OrderNumber' with value '12345'.. Option D is correct because the CLU model will predict the 'CancelOrder' intent and extract the entity 'OrderNumber' with value '12345'. Option A is wrong because the intent is indeed recognized. Option B is wrong because the entity is extracted. Option C is wrong because the entity is correctly extracted as a number.

Answer

The response will contain an error because the deployment is not active.

Answer

The response will contain the entity 'OrderNumber' with value '#12345' because the hash is part of the entity.

Answer

The response will contain only the top intent, but no entities because the entity type is not recognized.

Question 2

Refer to the exhibit. You are calling the Azure AI Language API for entity linking. What is the primary purpose of this request?

Accepted Answer

To identify entities in the text and link them to a knowledge base.. Option A is correct because entity linking identifies named entities and links them to a knowledge base (like Wikipedia). Option B is wrong because entity extraction without linking is done by NER. Option C is wrong because key phrase extraction is a different API. Option D is wrong because sentiment analysis is separate.

Answer

To extract named entities from the text without linking.

Answer

To extract key phrases from the text.

Answer

To analyze the sentiment of the text.

Question 3

A company is building a chatbot that must handle user queries in multiple languages. The chatbot uses Azure AI Language Service. Which feature should be used to detect the language of incoming messages before routing them to the appropriate language model?

Accepted Answer

Language Detection. The correct answer is A because Language Detection is the feature specifically designed to identify the language of text. B (Key Phrase Extraction) extracts key phrases without language detection; C (Sentiment Analysis) determines sentiment; D (Entity Recognition) identifies entities like names and locations.

Answer

Sentiment Analysis

Answer

Key Phrase Extraction

Answer

Entity Recognition

Question 4

A company uses Azure AI Language Service to analyze customer feedback. They notice that the sentiment scores for negative reviews are often incorrectly labeled as neutral. Which configuration should be adjusted to improve accuracy?

Accepted Answer

Create a custom sentiment analysis model using Custom Text Classification. The correct answer is C because sentiment analysis accuracy can be improved by providing a custom model trained on domain-specific data. A (increasing confidence threshold) would reduce false positives but not address mislabeling. B (changing to a different region) does not affect model accuracy. D (using key phrase extraction) is unrelated to sentiment.

Answer

Deploy the Language service in a different Azure region

Answer

Increase the confidence threshold for sentiment classification

Answer

Enable Key Phrase Extraction to preprocess the text

Question 5

A healthcare organization deploys an Azure AI Language Service custom entity recognition model to extract medical conditions from clinical notes. During testing, the model fails to recognize rare diseases mentioned in the training data. What is the most likely cause?

Accepted Answer

The model requires more labeled examples of rare diseases. The correct answer is D because custom entity recognition models require sufficient examples per entity; rare diseases with few examples lead to poor recognition. A (overfitting) would cause high training accuracy but poor generalization, but the issue is specifically with rare diseases. B (imbalanced training data) could be a factor, but the primary cause is the low number of examples. C (entity length limit) is not relevant as rare diseases are not necessarily long.

Answer

The entity length exceeds the maximum allowed for the model

Answer

The model is overfitting to common diseases

Answer

The training data is imbalanced with too many common diseases

Question 6

A company uses Azure AI Language Service to summarize long documents. They need to generate concise summaries that capture the main points. Which feature should they use?

Accepted Answer

Extractive Summarization. The correct answer is B because Extractive Summarization extracts key sentences from the text. A (Key Phrase Extraction) extracts phrases, not a summary. C (Entity Recognition) identifies entities. D (Sentiment Analysis) determines sentiment.

Answer

Entity Recognition

Answer

Key Phrase Extraction

Answer

Sentiment Analysis

Question 7

A company is developing a conversational AI solution using Microsoft Copilot Studio. They want the copilot to answer questions based on a knowledge base of technical documents. Which data source integration should they use?

Accepted Answer

Azure AI Search. The correct answer is B because Microsoft Copilot Studio can use Azure AI Search as a knowledge source for retrieval-augmented generation. A (Azure SQL Database) is not directly supported as a knowledge base for Copilot Studio. C (Azure Blob Storage) requires additional indexing. D (Microsoft Lists) is for simpler data.

Answer

Azure Blob Storage

Answer

Azure SQL Database

Answer

Microsoft Lists

Question 8

A company uses Azure AI Language Service for custom text classification. The model is trained to classify support tickets into categories. After deployment, the model performs well on the test set but poorly on new incoming tickets. Which action should be taken to improve generalization?

Accepted Answer

Add more labeled data from actual production tickets. The correct answer is C because adding more diverse training data from production helps the model generalize. A (increasing the number of training epochs) may lead to overfitting. B (reducing the confidence threshold) does not address generalization. D (using a prebuilt model) may not fit the custom categories.

Answer

Switch to a prebuilt text classification model

Answer

Increase the number of training epochs

Answer

Reduce the confidence threshold for classification

Question 9

A company needs to extract personally identifiable information (PII) from customer support transcripts stored in Azure Blob Storage. Which Azure AI service should they use?

Accepted Answer

Azure AI Language Service. The correct answer is B because Azure AI Language Service includes PII detection. A (Azure AI Vision) handles images, not text. C (Azure AI Speech) handles audio. D (Azure AI Translator) translates text.

Answer

Azure AI Speech

Answer

Azure AI Translator

Answer

Azure AI Vision

Question 10

A company is implementing a question-answering system using Azure AI Language Service. They have a set of FAQ documents in PDF format. Which feature should they use to automatically generate question-answer pairs?

Accepted Answer

Custom Question Answering. The correct answer is A because Custom Question Answering can ingest FAQ documents and generate Q&A pairs. B (Conversational Language Understanding) is for intent recognition. C (Extractive Summarization) summarizes text. D (Key Phrase Extraction) extracts phrases.

Answer

Key Phrase Extraction

Answer

Extractive Summarization

Answer

Conversational Language Understanding

Question 11

A company uses Azure AI Language Service with Custom Entity Recognition to extract invoice fields. The model correctly extracts invoice numbers but fails to extract dates in the format 'dd/mm/yyyy'. The training data includes dates in 'mm/dd/yyyy' format. What is the most likely issue?

Accepted Answer

The training data does not contain examples with the 'dd/mm/yyyy' format. The correct answer is C because the model learns the date format from training data; if training data uses a different format, it will not recognize other formats. A (entity length) is not the issue. B (overfitting) would still recognize dates if format matches. D (language detection) is irrelevant.

Answer

The dates exceed the maximum entity length

Answer

The language detection is incorrectly identifying the locale

Answer

The model is overfitting to invoice numbers

Question 12

Which TWO actions should you take to ensure that an Azure AI Language Service custom entity recognition model complies with data privacy regulations?

Accepted Answer

Configure data retention policies to delete data after processing. The correct answers are B and D. B ensures that training data does not contain PII that could be exposed. D ensures that processed data is not stored longer than necessary. A (enabling logging) does not directly address privacy. C (using prebuilt models) may not be relevant. E (increasing compute) is unrelated.

Answer

Use prebuilt entity recognition models instead of custom

Answer

Increase the number of training epochs

Answer

Enable diagnostic logging for audit trails

Question 13

Which THREE components are required to build a custom question-answering solution using Azure AI Language Service?

Accepted Answer

A bot channel registration or web app to interact with users. The correct answers are A, C, and E. A provides the knowledge base. C is the service required. E provides the interface for users to ask questions. B (Azure AI Search) is not required because Custom Question Answering has its own index. D (Azure Functions) is optional.

Answer

An Azure AI Search index

Answer

An Azure Functions app for serverless compute

Question 14

Which TWO Azure AI services can be used to analyze sentiment in text data?

Accepted Answer

Azure AI Language Service. The correct answers are A and C. A (Azure AI Language Service) includes sentiment analysis. C (Azure AI Content Safety) can detect harmful content, which includes sentiment aspects. B (Azure AI Vision) is for images. D (Azure AI Speech) is for audio. E (Azure AI Translator) is for translation.

Answer

Azure AI Translator

Answer

Azure AI Vision

Answer

Azure AI Speech

Question 15

Refer to the exhibit. You send this request to the Azure AI Language Service for custom entity recognition. The response returns no entities. What is the most likely reason?

Accepted Answer

The projectName and deploymentName are missing from the body parameters. The correct answer is D because the request is missing the 'projectName' and 'deploymentName' under the 'parameters' of the body. The exhibit shows them at the top level but not inside the body parameters. The API requires these inside the body. A (language mismatch) is not the issue because 'en' is correct. B (text too short) is not the cause. C (model version) is set to 'latest'.

Answer

The text input is too short for entity recognition

Answer

The language parameter is set incorrectly

Answer

The model version is not specified

AI-102 Implement natural language processing solutions Practice Test 4 — 15 Questions

Exhibit

AI-102 Implement natural language processing solutions Practice Test 4 — 15 Questions

Exhibit