Microsoft Exam AI-900 Topic 5 Question 55 Discussion

Actual exam question for Microsoft's AI-900 exam

Question #: 55
Topic #: 5

You are building a chatbot that will use natural language processing (NLP) to perform the following actions based on the text input of a user:

* Accept customer orders.

* Retrieve support documents.

* Retrieve order status updates.

Which type of NLP should you use?

Asentiment analysis

Btranslation

Clanguage modeling

Dnamed entity recognition

Show Suggested Answer

Suggested Answer: C

by Donte at Dec 08, 2023, 08:23 AM

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Susy

1 months ago

I'm going with named entity recognition. It's the clear choice to extract the critical details needed to process orders, look up support docs, and provide status updates. Anything else would be like trying to build a house with a screwdriver.

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Mitsue

1 days ago

D) named entity recognition

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Caren

3 days ago

C) language modeling

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Shannon

11 days ago

B) translation

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Rene

14 days ago

A) sentiment analysis

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Bernardine

2 months ago

Translation? Really? Unless your customers are from another planet, I don't see how that would be helpful here. Let's keep it grounded in Earth language, shall we?

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Kanisha

18 days ago

D) named entity recognition

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Osvaldo

1 months ago

C) language modeling

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Theron

1 months ago

A) sentiment analysis

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Becky

2 months ago

Sentiment analysis could be interesting, but it doesn't seem directly relevant to the core functionality the chatbot needs. I'd save that for a later enhancement.

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Rosina

2 months ago

Language modeling could be useful for understanding the overall context and intent behind the user's input. But I'm not sure it would be enough to handle all the specific actions the chatbot needs to perform.

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Cherelle

1 months ago

D) named entity recognition

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Larae

1 months ago

A) sentiment analysis

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Pearly

1 months ago

D) named entity recognition

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Kristeen

1 months ago

A) sentiment analysis

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Roselle

2 months ago

I think named entity recognition is the way to go for this chatbot. It can help identify key pieces of information like customer names, order numbers, and product details.

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