Implement natural language processing solutions

You have a Conversational Language Understanding (CLU) project in Azure AI Language. Users frequently type utterances such as 'Book a flight from Seattle to Tokyo next Friday for two people.' The solution must extract the origin city, destination city, date, and passenger count as separate structured values so the booking system can act on them. You need to configure the project to capture these values. What should you do?

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?

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?

Which TWO capabilities are provided by the Azure AI Language service?

A retailer wants to analyze thousands of product reviews per day and needs to know which aspects of the products customers mention, such as battery life or screen quality, and whether sentiment toward each aspect is positive or negative. The reviews are already stored as text in an Azure SQL Database. Which Azure AI Language feature should you use?

You are building a custom named entity recognition (NER) model using Azure AI Language. After labeling 200 documents, you train the model and achieve 85% precision but only 60% recall. Which action is most likely to improve recall?

You are using Azure AI Language's custom question answering feature. Your knowledge base contains 500 FAQ pairs. Users report that the bot returns irrelevant answers when their questions are phrased differently from the stored FAQs. You want to improve the bot's ability to match paraphrased questions without retraining a full model. Which action should you take?

Refer to the exhibit. You called the Named Entity Recognition API on a document. Which entity type is "Seattle"?

You are building a solution that uses Azure AI Language to analyze transcribed call-center conversations. The transcripts are stored as plain text in Azure Blob Storage. You need to identify the specific products, dates, and monetary amounts mentioned in each conversation while distinguishing them from generic nouns. You also need to return the character offset and length for each detected mention so the UI can highlight them. Which Azure AI Language feature should you use?

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?

You are building an Azure AI Language solution that analyzes customer support emails. You need to detect the language of each email before routing it to the correct translation pipeline. You call the Language Detection API with the following request body: {"kind": "LanguageDetection", "analysisInput": {"documents": [{"id": "1", "text": "Bonjour, je besoin d'aide avec mon compte."}]}}. What will the response contain?

You are deploying an Azure AI Language custom text classification model. You need to ensure the model meets performance requirements before promoting it to production. Which two actions should you take? (Choose two.)

A company wants to build a solution that can identify and redact personally identifiable information (PII) from customer support transcripts. The solution must handle multiple languages. Which Azure AI service should be used?

You need to build a solution that extracts the main topics discussed in recorded customer service calls. The audio is already transcribed to text, and you must return the most salient phrases without any predefined categories. Which Azure AI Language feature should you use?

A financial services company uses Azure AI Language's custom text classification to categorize loan applications as 'Approved', 'Denied', or 'Review Required'. The model is trained on historical data but is producing poor accuracy on new applications. The data scientist suspects data leakage between training and test sets. What should the data scientist do to validate this?

A healthcare company uses Azure AI Language's custom question answering to build a bot that answers patient FAQs. The knowledge base contains documents with sensitive information. The company needs to ensure that the bot only returns answers from documents that the user is authorized to access. What should they implement?

You are deploying a question answering solution using Azure AI Language. The solution must be able to provide answers from a set of frequently asked questions (FAQs) in PDF format. What should you do?

You are building an Azure AI Language solution that ingests support tickets and routes each ticket to the correct department. Each ticket must be assigned exactly one department, and departments are defined only by the examples you label in Language Studio. You need to build the model with the fewest labeling and configuration steps. Which project type and configuration should you use?

Your company uses Azure AI Language to analyze customer feedback. You need to extract key phrases from reviews in multiple languages. Which feature should you use?

Which TWO capabilities are provided by Azure AI Language's pre-built entity recognition?

A team is developing a solution to automatically summarize long documents using Azure AI Language. Which feature should they use?

Based on the exhibit, which entity should you focus on improving by adding more labeled examples?

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

Refer to the exhibit. You submit this request to Azure AI Language's conversational language understanding (CLU) for the 'FlightBooking' project. The model correctly identifies the intent as 'BookFlight' and extracts entities: 'Seattle' as FromCity, 'New York' as ToCity, and 'June 15th' as Date. What is the next step for the application?

A developer is building a multilingual chatbot using Azure AI Language. The bot must detect the user's language automatically and route the query to the appropriate language-specific model. Which Azure AI Language feature should the developer use?

You are developing an Azure AI Language solution to analyze customer support tickets. Each ticket has a subject and a description. You need to automatically classify tickets into categories (e.g., 'billing', 'technical', 'account') and extract the product name mentioned. You have a labeled dataset of 10,000 tickets with category labels and product name annotations. The solution must be cost-effective and easy to retrain as new categories emerge. You want to use a single Azure AI Language resource. Which approach should you use?

You notice a spike in errors (HTTP 429) on a specific day. What is the most likely cause?

You are building a custom text classification solution in Azure AI Language. You have a dataset with 10 categories and 1000 labeled documents. You need to choose the best project type. What should you use?

Which TWO components are required to create a custom text classification model in Azure AI Language?

A company wants to build a conversational interface that can understand user intents and extract key information from utterances, such as booking a flight to a specific city on a specific date. They need to implement this using Azure AI Language. Which feature should they use?

You are a developer at a global e-commerce company. You are building a multilingual chatbot using Azure AI Language that supports English, French, German, and Spanish. The chatbot must answer frequently asked questions about order status, returns, and shipping. You plan to use Custom Question Answering with a single project containing questions and answers in all four languages. However, during testing, you notice that queries in French and German often return incorrect answers or no answer, while English and Spanish work well. You need to ensure accurate answers across all four languages. What should you do?

You need to analyze customer call transcripts to identify positive and negative sentiment. Which Azure AI Language feature should you use?

A legal firm uses Azure AI Language's custom NER to extract party names, dates, and clauses from contracts. The model performs well on English contracts but poorly on French contracts. The firm wants to improve performance without retraining from scratch. What is the most efficient approach?

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?

Refer to the exhibit. You have created a Text Analytics resource and retrieved its keys. You want to use the key1 to call the Sentiment Analysis API from a Python application. Which endpoint URL should you use?

You are using Azure AI Language to analyze customer reviews. You need to determine whether each review expresses a positive, negative, or neutral sentiment. Which API should you call?

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?

Refer to the exhibit. You are defining a custom entity recognition model in Azure AI Language. The exhibit shows a partial configuration. What is the relationship between 'Laptop' and 'Electronics'?

A company uses Azure AI Language's custom text classification to categorize support tickets. The model was trained with 5000 labeled examples and achieves 90% accuracy. However, for a specific category (e.g., 'billing'), the model frequently misclassifies tickets that contain both billing and technical issues. Which action should you take to improve classification for this category?

You are a solution architect at a media company. The company uses Azure AI Speech to generate subtitles for videos. The current solution uses the batch transcription API and takes several hours to process a 1-hour video. The business requires near-real-time subtitles for live streaming events. You need to design a new solution that provides low-latency transcription. You have the following options: Option A: Use the batch transcription API with a higher priority queue. Option B: Use the Speech-to-text REST API for real-time streaming with the Speech SDK. Option C: Use the Azure AI Language API to transcribe audio from a file. Option D: Use Azure AI Video Indexer to generate subtitles.

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?

You need to analyze customer feedback to determine whether the sentiment is positive, negative, or neutral. Which Azure AI service should you use?

Which TWO actions should you take to optimize a custom text classification model in Azure Cognitive Service for Language?

A research organization uses Azure AI Language to process large volumes of scientific papers. They need to extract specific entities such as gene names, protein names, and chemical compounds. The entity types are highly specialized and not covered by prebuilt models. The organization has a labeled dataset of 10,000 documents. You need to recommend the most efficient approach to build the entity extraction solution. What should you do?

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

Refer to the exhibit. A developer is configuring a QnA Maker skill for a bot. The skill fails to respond to queries. What is the most likely issue?

Your organization uses Azure AI Language for custom text classification. You have deployed a model to a dedicated endpoint. After updating the training data, you retrain and redeploy the model. Users report that the endpoint still returns predictions from the old model. What is the most likely cause?

Which THREE factors should be considered when choosing between Azure AI Language's pre-built sentiment analysis and custom sentiment analysis for a specialized domain?

A company wants to build a solution that summarizes long support call transcripts into concise paragraphs. The transcripts are stored as plain text in Azure Blob Storage. You plan to use the summarization feature in Azure AI Language. Which summarization type should you use to generate a short paragraph that captures the main points of each transcript?

Which THREE actions should an engineer take when deploying a custom question answering project in Azure Cognitive Service for Language?

Refer to the exhibit. You deployed a custom model for Language service. Which command should you run to check if the deployment is ready to accept inference requests?

You are building a solution that analyzes customer feedback in real-time using Azure AI Language. The feedback is streamed from a web app and must be processed within 1 second. You need to extract sentiment and key phrases. Which service should you use?

You need to translate a large volume of documents from English to French while preserving the original formatting. Which Azure service should you use?

Which THREE factors should you consider when choosing between a pre-built model and a custom model in Azure AI Language?

You need to use Azure AI Language to analyze customer feedback. Which THREE analysis types are available in the Text Analytics API?

You are building a custom question answering solution using Azure AI Language. The knowledge base contains a large number of question-answer pairs. You need to ensure that the solution returns the most relevant answer for a user's query, even when the query contains synonyms not present in the knowledge base. What should you do?

You are developing a solution that uses Azure AI Language to analyze customer feedback. You need to determine whether the sentiment of a given sentence is positive, negative, or neutral. Which Azure AI Language feature should you use?

You are building an ASP.NET Core web app that must analyze the sentiment of user-submitted product reviews in real time. The app is deployed to an Azure App Service web app. You want to avoid managing API keys in code and prefer to use the app's managed identity for authentication to the Azure AI Language resource. What should you do to enable the app to call the sentiment analysis API securely?

A development team is using Azure Cognitive Service for Language to extract key phrases from customer reviews. They notice that some reviews are not being processed, and the API returns a 400 error code. What is the most likely cause?

You are developing a chatbot for a retail company using Azure AI Language's custom question answering. The chatbot must provide answers from a knowledge base of 500 FAQ documents. Users often ask the same question in different wording, and the chatbot fails to return an answer for paraphrased queries. What is the most effective solution?

A logistics company receives shipping manifests as PDF documents. They need to extract the shipper name, consignee, and total weight from each document. The documents have a consistent layout. Which Azure AI service should they use?

A company wants to use Azure AI Translator to translate customer emails from English to French. They need to ensure that the translation preserves the tone and formality of the original text. What should they configure in the request?

You need to summarize a large document using Azure AI Language. Which feature should you use?

A healthcare portal must summarize patient feedback stored in Azure Blob Storage. Documents are plain UTF-8 text and the summaries must be generated without sending content to a public endpoint. You are building the pipeline with Azure AI Language and a private network. Which configuration should you use to call extractive summarization while meeting the network requirement?

You plan to deploy a custom named entity recognition (NER) project in Azure AI Language. The project must extract supplier names and contract identifiers from procurement documents. You need to prepare the project so that the model can be trained and evaluated before deployment. Which two actions should you perform? (Choose two.)

You are implementing a conversational language understanding (CLU) project in Azure AI Language. Your utterances include entities that are sometimes a single word and sometimes a multi-word phrase, such as 'New York' and 'San Francisco'. You need the model to correctly capture these multi-word entities during training and prediction. Which entity component type should you use?

A news organization wants to automatically summarize long articles into short, coherent summaries. The solution must preserve the original meaning and key points. Which Azure AI service should be used?

You are developing a solution that uses Azure AI Language's custom named entity recognition (NER) to extract product names from technical support tickets. After training a model, you notice it performs well on the training set but poorly on new tickets. You need to improve the model's ability to generalize. What should you do?

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

A company uses Azure AI Speech for real-time captioning during live events. They notice a delay of 5 seconds between speech and caption display. Which action should they take to reduce latency?

You deploy the ARM template shown in the exhibit. After deployment, you need to allow access to the Language service from your on-premises application. What should you do?

You are designing a solution that uses Azure AI Language's conversational language understanding (CLU) to interpret user requests in a banking app. The app must handle utterances like 'Transfer $500 from savings to checking' and extract the amount, source account, and destination account. Which two actions should you perform when creating the CLU project? (Choose two.)

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

You are deploying a custom question answering solution in Azure AI Language. You need to ensure that the knowledge base can handle synonyms and alternative phrasings for questions. Which THREE strategies should you implement? (Select THREE.)

You are building a solution that uses Azure AI Language's question answering (custom question answering) to create a bot that answers employee HR questions. You have created a project and added a knowledge base with 50 question-answer pairs. You need to ensure the bot provides accurate answers and can handle paraphrased questions. Which two actions should you perform? (Choose two.)

A company is using Azure Cognitive Service for Language to analyze customer support transcripts. They want to identify custom categories (e.g., 'billing', 'technical support') using a custom text classification model. After training and deploying the model, they receive many false positives for the 'billing' category. What is the best first step to improve model accuracy?

Refer to the exhibit. A developer is testing the Text Analytics sentiment analysis API and receives a 401 error. What is the most likely cause?

A developer is using Azure Cognitive Service for Language to perform sentiment analysis on customer reviews. The service returns sentiment labels (positive, negative, neutral) and confidence scores. For a particular review, the service returns 'positive' with a confidence score of 0.55. The developer wants to ensure that only high-confidence results are used. What should the developer do?

You are developing a conversational language understanding (CLU) project in Azure AI Language. You have defined intents and entities for a banking bot. During testing, you notice that utterances containing the phrase 'transfer funds' are sometimes predicted as the 'CheckBalance' intent instead of 'TransferMoney'. You have already added 20 labeled examples for 'TransferMoney' and 20 for 'CheckBalance'. What should you do to improve the model's ability to distinguish between these intents?

A multinational corporation uses Azure AI Language to analyze customer feedback in multiple languages. The solution must detect the language of incoming text and then perform sentiment analysis. Which approach minimizes latency and cost?

A financial services firm uses Azure AI Language to analyze earnings call transcripts. They need to extract key phrases and identify sentiment for each speaker's turn. Which approach should they use?

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?

You are building a solution that uses Azure AI Language to summarize long customer support emails. The emails are in English, and each email can be up to 10,000 characters. You need to generate a concise summary that preserves the most important sentences and returns the summary along with the original sentences it selected. Which feature and approach should you use?

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

Your application needs to extract key phrases from customer reviews to identify common topics. Which Azure AI Language feature should you use?

Your company uses Azure AI Document Intelligence to process invoices. You need to extract the invoice date and total amount. Which model should you use?

You are using Azure AI Language's custom question answering feature to build a FAQ bot. The knowledge base contains many question-and-answer pairs. Users sometimes ask questions that are paraphrases of the stored questions. You need to improve the likelihood that the bot returns the correct answer for paraphrased questions. Which action should you take?

Which TWO Azure services can be used to implement a conversational AI solution that understands user intent and responds appropriately?

You are developing a solution that uses Azure AI Language to detect the language of incoming text messages. The messages may contain mixed languages within a single document. You need to ensure the API returns the detected language and a confidence score for each document. Which request should you make?

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?

A developer is deploying a custom text classification model in Azure AI Language. The model must be accessible via a REST API with low latency. Which TWO actions should the developer take?

You are building a chatbot using Azure AI Language and need to handle user intents that are not covered by the predefined intents. What should you implement?

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

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?

A company uses Azure AI Language to analyze customer reviews. They need to detect sentiment, extract key phrases, and identify named entities. Which THREE capabilities should they combine?

You are building an application that must detect and redact personally identifiable information (PII) from free-text support tickets before storing them. The tickets are written in English, and you need to identify entities such as names, phone numbers, and email addresses, and replace them with asterisks. You plan to use the Azure AI Language service. Which API endpoint should you call?

A healthcare organization needs to redact personally identifiable information (PII) from patient records before using them for research. They have large volumes of unstructured text in multiple languages. Which Azure AI service should they use?

A healthcare organization is building a clinical decision support system that must extract medical entities (e.g., symptoms, diagnoses, medications) from unstructured clinical notes. The solution must be able to detect relationships between entities, such as 'medication X treats symptom Y'. Which Azure AI service should be used?

You are building a solution that must detect the sentiment polarity (positive, negative, neutral, or mixed) of incoming customer support tickets written in English and German. You want to use a single Azure AI Language resource and avoid maintaining separate models per language. Which approach should you use?

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?

A company is building a chatbot using Azure OpenAI Service to handle customer inquiries. The bot sometimes responds with incorrect or fabricated information. The team wants to ground the model responses using their own product documentation stored in Azure Cognitive Search. Which configuration should they implement?

You are developing a solution that uses Azure AI Translator to translate documents from English to French. You need to ensure that the translated text maintains the original formatting, such as HTML tags. Which feature should you use?

You are designing a solution that uses Azure AI Language custom question answering. The knowledge base contains 200 question-answer pairs. Users report that the bot sometimes returns answers to questions that are semantically similar but not actually asked. You need to reduce these false positives while maintaining the ability to answer paraphrased questions. What should you configure?

You are designing a conversational AI solution using Microsoft Copilot Studio. The exhibit shows part of a topic configuration. What is the purpose of the 'triggers' section?

Your organization uses Azure AI Language to perform sentiment analysis and opinion mining on product reviews. You notice that the sentiment scores are often neutral even when the review text contains clearly positive or negative opinions. You suspect the model is not capturing the nuances. Which three actions could improve the sentiment analysis accuracy? (Choose three.)

You need to transcribe customer service calls into text for analysis. Which Azure service should you use?

A company is building a chatbot using Azure Bot Service and Language Understanding (LUIS). The chatbot needs to handle user intents for booking flights and checking flight status. After testing, the chatbot frequently fails to distinguish between the two intents when users mention flight numbers. Which action should the engineer take to improve intent recognition?

You are building a multilingual customer support chatbot using Azure AI Language. The bot must understand user intents in English, Spanish, and French. You have pre-existing labeled data in English only. The solution should minimize manual labeling effort. Which approach should you recommend?

A company uses Azure AI Speech to provide real-time transcription for customer support calls. The solution must handle multiple languages and filter out profanity. Which THREE configurations are needed?

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

You are using Azure AI Language's question answering feature to build a bot that answers employee questions from a set of HR policy documents. You need to ensure the bot provides accurate answers and can handle follow-up questions. Which two actions should you take? (Choose two.)

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?

You are building an Azure AI Language solution that must extract named entities from support tickets and classify each entity as a person, organization, or location. The tickets are stored as UTF-8 text files. You need to call the REST API for Named Entity Recognition (NER) and ensure the response includes entity categories. Which request should you send?

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?

Your Azure AI Language custom question answering project answers product questions from a knowledge base. Users report that the bot returns the same generic answer regardless of how they phrase a question, even when the knowledge base contains the correct information. You need to diagnose why the model is not matching semantically similar user phrasings to the right answer. What should you do first?

You are building a solution to extract key phrases from customer reviews using Azure AI Language. Which feature should you use?

A travel agency wants its web app to summarize long customer complaint emails into a short paragraph that preserves the main points. The emails are in English and average 800 words. You need to use the extractive summarization feature of Azure AI Language and control how long the summary is. Which request parameter should you configure?

You deploy an Azure AI Services resource using the ARM template shown in the exhibit. You need to test the Language service API from your local machine. What should you do first?

You are developing a conversational language understanding (CLU) project in Azure AI Language. The project must recognize user intents and extract entities from utterances. You have trained and deployed the model. You need to call the prediction API from a client application. The deployment name is 'prod' and the project name is 'HRBot'. Which URL should you use to send an utterance for prediction?

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?

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?

You are building a solution that uses Azure AI Language's sentiment analysis to monitor customer feedback. The feedback includes text in multiple languages, and you need to obtain sentiment scores at both the document level and the sentence level. Which API endpoint should you call?

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?

A developer is creating a custom text classification model using Azure AI Language. The dataset has 10,000 documents across 50 categories. Which method is most suitable for labeling the data efficiently?

You are using Azure AI Language to analyze customer feedback. You need to identify the sentiment of each sentence within a review, not just the overall document sentiment. Which feature should you use?

A company uses Azure AI Language's custom named entity recognition (NER) to extract product names from support tickets. They have trained a model with 500 labeled entities across 200 documents. During evaluation, they notice the model has high precision but low recall for a specific product category. What should they do to improve recall for that category?

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?

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

A developer is creating a custom question answering project in Azure AI Language. The knowledge base contains product manuals in PDF format. Which step is essential before importing the PDFs?

You are building a conversational language understanding (CLU) project in Azure AI Language. You need to ensure the model can correctly interpret user utterances that include both an intent and multiple entities. Which two actions should you perform? (Choose two.)

You are building a chatbot that must understand user intents from free-text input. You have a small set of labeled examples. Which Azure AI Language feature should you use to classify intents with minimal effort?

A financial services company uses Azure AI Language to analyze customer support transcripts. They want to identify the main topics discussed in each conversation and generate a summary of the key points. The solution must minimize development effort and use prebuilt functionality. You need to recommend the appropriate Azure AI Language features. What should you use?

A support team wants to build a bot that answers employee questions by using a set of internal HR policy documents. The team does not want to author question-and-answer pairs manually and needs the bot to return the most relevant passage from the documents, with the source cited. The documents are in English and are updated frequently in a blob container. Which Azure AI Language feature should the team use?

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?

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?

You are deploying a conversational language understanding project in Azure AI Language for a banking chatbot. Testing shows the model frequently confuses the intents TransferFunds and PayBill because both utterances contain similar wording about moving money. You need to improve the model's ability to distinguish these two intents. What should you do?

A legal compliance team needs to automatically redact personally identifiable information (PII) from legal documents before sharing them with external auditors. The documents are stored in Azure Blob Storage. The solution must use Azure AI Language to detect PII and then redact the identified entities. The redaction must be performed on the original documents, and the redacted versions must be saved to a separate container. You need to design a serverless solution with minimal latency. What should you do?

A company wants to use Azure AI Language to automatically summarize large documents. The summarization must extract the most important sentences from each document. Which feature should they use?

You are building a multilingual chatbot using Azure AI Language. For a given user utterance, you need to first detect the language, then route to the appropriate language-specific intent model. Which combination of Azure AI Language features should you use?

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?

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?

You are building a customer feedback dashboard with Azure AI Language. Analysts need to see, for each document, the overall sentiment and the sentiment expressed toward specific aspects such as shipping speed and product quality within the same request. The documents are short English reviews. Which feature and configuration should you use?

A developer is building a multilingual translation solution using Azure AI Translator. The solution must translate text to French, German, and Spanish. Which parameter should the developer set to specify the target language?

You are designing a multilingual chatbot using Azure AI Language. The chatbot must support English, Spanish, and French. You need to minimize development effort and ensure consistent intent recognition across languages. What should you do?

You are building a custom entity extraction solution using Azure AI Language. You have a small dataset (50 documents) with annotated entities. You need to train a model that can extract similar entities from new documents. What is the best approach?

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

A company wants to analyze customer reviews to determine whether sentiment is positive, negative, or neutral. The solution must also extract key phrases such as 'great battery life' and 'poor camera quality'. Which Azure AI feature should be used?

You are building a multilingual chatbot using Azure AI Language. The chatbot must handle English, Spanish, and French. You need to configure the LUIS (Language Understanding) model to support multiple languages efficiently. What is the best practice?

Your organization needs to analyze customer call transcripts to extract key insights, including sentiment, issues, and resolution. Which THREE Azure AI Language features should you use?

You are developing a chat application that uses Azure OpenAI GPT-4 to answer customer questions. You need to ensure the model does not generate harmful content. Which configuration should you set?

You are using Azure AI Language to analyze social media comments. You need to identify the language of each comment and then extract key phrases. Which TWO features should you use? (Select TWO.)

Which TWO Azure AI services can be used to build a multilingual question-answering bot that retrieves answers from a knowledge base of documents?

You are building a solution that must summarize long documents in real time as they are uploaded to Azure Blob Storage. The summaries must be concise and capture the main points. You want to use Azure AI Language. Which feature should you use?

A support organization uses Azure AI Language custom named entity recognition (custom NER) to extract product codes from warranty emails. The model performs well in production, but a new product line introduced codes formatted as two letters, a hyphen, and six digits, and the model misses them. You need the model to recognize the new format while keeping existing extraction quality. What should you do?

You need to analyze the sentiment of social media posts in real time using Azure AI Language. Which approach should you use?

You are developing a solution that uses Azure AI Language to perform sentiment analysis on multilingual product reviews. The reviews are in English, German, and Japanese. You need to ensure that the sentiment score is accurate for each language. What should you do?