AIF-C01 · Question #59
A company wants to use a large language model (LLM) on Amazon Bedrock for sentiment analysis. The company wants to classify the sentiment of text passages as positive or negative. Which prompt…
The correct answer is A. Provide examples of text passages with corresponding positive or negative labels in the prompt. Providing examples of text passages with corresponding positive or negative labels in the prompt followed by the new text passage to be classified is the correct prompt engineering strategy for using a large language model (LLM) on Amazon Bedrock for sentiment analysis.
Question
A company wants to use a large language model (LLM) on Amazon Bedrock for sentiment analysis. The company wants to classify the sentiment of text passages as positive or negative. Which prompt engineering strategy meets these requirements?
Options
- AProvide examples of text passages with corresponding positive or negative labels in the prompt
- BProvide a detailed explanation of sentiment analysis and how LLMs work in the prompt.
- CProvide the new text passage to be classified without any additional context or examples.
- DProvide the new text passage with a few examples of unrelated tasks, such as text summarization
How the community answered
(48 responses)- A81% (39)
- B4% (2)
- C4% (2)
- D10% (5)
Explanation
Providing examples of text passages with corresponding positive or negative labels in the prompt followed by the new text passage to be classified is the correct prompt engineering strategy for using a large language model (LLM) on Amazon Bedrock for sentiment analysis.
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