AI-102 Implement natural language processing solutions Practice Test 9 — 15 Questions

Question 1

Refer to the exhibit. You are designing a Data Factory pipeline to perform sentiment analysis on a text column. The pipeline fails with a 'BadRequest' error. What is the most likely issue?

Accepted Answer

The input format is incorrect; it should be a JSON array of documents. The Cognitive Service activity expects a specific format for the input, typically a JSON structure with 'documents' array. The current input is just the text value, which is incorrect. The linked service name is correct. The activity type is appropriate. The output reference is not causing the error.

Answer

The output variable 'sentimentResult' is not defined

Answer

The activity type should be 'AzureFunction'

Answer

The linked service name is misspelled

Question 2

Refer to the exhibit. You are calling the Azure AI Language NER API. The response returns no entities. What is the most likely reason?

Accepted Answer

The text does not contain any recognized entities. The text 'The quick brown fox jumps over the lazy dog.' contains no named entities like people, places, or organizations. The API version and endpoint appear correct. The document format is fine.

Answer

The API version is incorrect

Answer

The document language should be 'es' for Spanish

Answer

The endpoint URL is for the wrong region

Question 3

You are building a chatbot that must handle customer inquiries about order status. The solution must use Azure AI Language and support multiple languages. You need to configure the project to detect language automatically from user input. Which setting should you enable?

Accepted Answer

Enable multi-lingual detection in the project language settings.. Option B is correct because enabling multi-lingual detection in the language settings allows the project to automatically detect the input language. Option A is wrong because enabling only the primary language will not detect others. Option C is wrong because that setting is for spelling correction, not language detection. Option D is wrong because that setting is for conversation summarization.

Answer

Set the primary language to English only.

Answer

Use the conversation summarization feature.

Answer

Enable spelling correction in the project settings.

Question 4

You are designing a solution that must extract specific entities from customer emails, such as product names, order numbers, and dates. The solution must be able to learn from a small set of labeled examples and improve over time. Which Azure AI service should you use?

Accepted Answer

Custom Entity Extraction. Option C is correct because Custom Entity Extraction in Azure AI Language allows you to train a model with a small set of labeled data to extract custom entities. Option A is wrong because Pre-built Entity Extraction only works with predefined entity types. Option B is wrong because Text Analytics for health is specialized for medical data. Option D is wrong because the QnA Maker is for question answering, not entity extraction.

Answer

QnA Maker

Answer

Pre-built Entity Extraction

Answer

Text Analytics for health

Question 5

Your organization needs to analyze customer feedback from social media posts to determine the sentiment (positive, negative, neutral). The solution must process up to 10,000 posts per day and provide a confidence score for each sentiment. Which Azure AI service should you use?

Accepted Answer

Azure AI Language Service. Option A is correct because Azure AI Language provides sentiment analysis with confidence scores as a built-in feature. Option B is wrong because the Translator service translates text, it does not analyze sentiment. Option C is wrong because the Speech service processes audio, not text. Option D is wrong because the Language Understanding service (LUIS) is for intent and entity extraction, not sentiment analysis.

Answer

Azure AI Speech Service

Answer

Azure AI Translator

Answer

Azure AI Language Understanding (LUIS)

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 have a custom Named Entity Recognition (NER) model trained using Azure AI Language. The model is performing poorly on new data. You need to improve its accuracy. Which action should you take first?

Accepted Answer

Review the test set results and add more labeled examples for entities with low precision/recall.. Option B is correct because the first step to improve model accuracy is to review the test set results and identify errors, then add more labeled examples for those failing patterns. Option A is wrong because reducing the number of entities might lose important distinctions. Option C is wrong because retraining with the same data will not fix issues. Option D is wrong because increasing epochs may lead to overfitting without better data.

Answer

Increase the training epochs.

Answer

Retrain the model using the same training data.

Answer

Reduce the number of entity types in the model.

Question 8

You need to build a solution that can answer questions based on a set of PDF documents, such as product manuals. The solution should allow users to ask questions in natural language and receive answers with citations. Which Azure AI service should you use?

Accepted Answer

Azure AI Custom Question Answering. Option B is correct because Azure AI custom question answering (part of Azure AI Language) allows you to create a knowledge base from PDFs and provides answers with citations. Option A is wrong because Azure Cognitive Search provides search results, not direct answers. Option C is wrong because Form Recognizer extracts text, but does not answer questions. Option D is wrong because the Text Analytics service provides sentiment, key phrases, etc., not question answering.

Answer

Azure AI Text Analytics

Answer

Azure Cognitive Search

Answer

Azure AI Document Intelligence (formerly Form Recognizer)

Question 9

You are deploying a Conversational Language Understanding (CLU) model to production. You need to monitor the model's performance and detect when retraining is needed due to concept drift. Which metric should you monitor?

Accepted Answer

Average confidence scores of predictions. Option A is correct because a significant drop in confidence scores for predictions may indicate concept drift, as the model becomes less certain. Option B is wrong because the number of utterances is a volume metric, not performance. Option C is wrong because response time is a performance metric, not related to model accuracy. Option D is wrong because endpoint calls is a usage metric.

Answer

Response time for each prediction

Answer

Number of endpoint calls

Answer

Number of utterances processed per day

Question 10

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

Question 11

You want to use the Azure AI Language service to summarize long customer support conversations into a short summary. Which feature should you use?

Accepted Answer

Conversational Summarization. Option C is correct because Conversational Summarization is designed to summarize conversations between multiple participants. Option A is wrong because Key Phrase Extraction extracts key phrases, not a summary. Option B is wrong because Entity Extraction identifies entities. Option D is wrong because Sentiment Analysis determines sentiment, not a summary.

Answer

Sentiment Analysis

Answer

Entity Extraction

Answer

Key Phrase Extraction

Question 12

You are building a solution that must translate customer chat messages from Spanish to English in real-time. The solution must also detect the language of incoming messages to handle cases where users write in other languages. Which TWO Azure AI service features should you use?

Accepted Answer

Azure AI Translator - Language Detection. Options A and D are correct because the Azure AI Translator service provides both translation and language detection. Option B is wrong because the Speech service is for audio, not text. Option C is wrong because the LUIS is for intent recognition, not translation. Option E is wrong because the QnA Maker is for question answering, not translation.

Answer

Azure AI Speech - Speech Translation

Answer

Azure AI Language Understanding (LUIS)

Answer

Azure AI Custom Question Answering

Question 13

You are developing a custom text classification model using Azure AI Language. You have labeled 2000 documents across 10 categories. You need to evaluate the model's performance before deploying to production. Which THREE metrics should you examine?

Accepted Answer

Recall. Options A, B, and D are correct because precision, recall, and F1 score are the standard metrics for classification models. Option C is wrong because BLEU is for machine translation. Option E is wrong because Word Error Rate is for speech recognition.

Answer

Word Error Rate

Answer

BLEU Score

Question 14

You are using the Azure AI Language service to process customer reviews. You need to extract the following insights: overall sentiment, key phrases, and entity types (such as product names). Which THREE operations should you call?

Accepted Answer

Key Phrase Extraction. Options A, B, and C are correct because Sentiment Analysis, Key Phrase Extraction, and Entity Recognition are the operations that provide the required insights. Option D is wrong because Language Detection detects the language, not needed here. Option E is wrong because PII Detection detects personal information, not needed here.

Answer

Language Detection

Answer

PII Detection

Question 15

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".

AI-102 Implement natural language processing solutions Practice Test 9 — 15 Questions

Exhibit

AI-102 Implement natural language processing solutions Practice Test 9 — 15 Questions

Exhibit