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NEW QUESTION # 125
Which Azure OpenAI model should you use to summarize the text from a document?
Answer: B
Explanation:
You can use ChatGPT to summarize text. This can help you understand complex information more easily, summarize the central argument of your own paper, or clarify your research question.
Reference:
https://community.openai.com/t/information-summary-by-using-api/578792
NEW QUESTION # 126
You are developing a web app that processes invoices to calculate expenses.
You need to extract structured fields, including nested values, from the invoices by using a defined schema.
What should you use?
Answer: B
Explanation:
The requirement is to extract structured fields, including nested values, from invoices by using a defined schema. In Azure Content Understanding, an analyzer is the processing unit that defines how content is analyzed, what information is extracted, and how the output is structured, including JSON fields.
Microsoft's Content Understanding document solutions documentation states that Content Understanding uses customizable analyzers to extract essential information, fields, and relationships from documents and forms. Microsoft's quickstart also shows invoice processing with the prebuilt-invoice analyzer to extract structured data from an invoice document.
Why the other options are incorrect:
A . transcription workflow in Azure Speech is for converting audio to text, not invoice field extraction.
B . OCR-only document processing can extract text but does not meet the requirement for structured fields and nested values by schema.
D . Azure AI Search is for indexing and querying content, not defining invoice extraction schemas.
Therefore, the correct answer is C. an analyzer in Azure Content Understanding in Foundry Tools.
NEW QUESTION # 127
Which Azure AI Foundry Service can be used to identify documents that contain sensitive information?
Answer: A
Explanation:
Azure AI Language can be used to identify documents containing sensitive information through its Personally Identifiable Information (PII) detection feature, which uses Named Entity Recognition (NER) to detect and categorize data like names, addresses, phone numbers, and financial details within unstructured text and native documents. This feature classifies sensitive data into predefined categories and can also redact the identified information, replacing it with asterisks to protect privacy.
Reference:
https://learn.microsoft.com/en-us/azure/ai-services/language-service/personally-identifiable- information/overview
NEW QUESTION # 128
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 129
Select the answer that correctly completes the sentence.
Answer:
Explanation:
NEW QUESTION # 130
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