PL-500 · Question #154
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might…
The correct answer is B. No. The 'Extract most relevant words and phrases from text' model (Key Phrase Extraction) is a natural language processing model that identifies important keywords and phrases from unstructured text. It does not extract specific structured data fields such as vendor name, pricing…
Question
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. A procurement department is using email to collect large volumes of quotes from vendors. Data from quotes, including vendor data and quote terms, must be stored in Microsoft Dataverse. You need to create a solution to automate the process. Solution: Cloud flow using the Extract most relevant words and phrases from text AI Builder model Does the solution meet the goal?
Options
- AYes
- BNo
How the community answered
(30 responses)- A23% (7)
- B77% (23)
Explanation
The 'Extract most relevant words and phrases from text' model (Key Phrase Extraction) is a natural language processing model that identifies important keywords and phrases from unstructured text. It does not extract specific structured data fields such as vendor name, pricing, or quote terms in a structured, labeled format suitable for storing in Dataverse. The goal requires structured extraction of defined fields, which this model cannot reliably deliver. A model designed for custom entity/field extraction would be more appropriate.
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