A developer wrote the following prompt to classify the sentiment of a user comment: 'What do you think about this? Input: The new user interface is confusing and slow.' Analyze this prompt and explain two specific weaknesses that make it ineffective for a zero-shot classification task where the desired outputs are 'positive', 'negative', or 'neutral'.

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A zero-shot prompt applies a task instruction to a new input without any preceding examples. To classify the sentiment of a positive text, the prompt could be structured like this:

'Assume that the polarity of a text is a label chosen from {positive, negative, neutral}. Identify the polarity of the input.

Input: The weather here is wonderful.'

Example of a Zero-Shot Prompt for Polarity Classification (Positive Sentiment)

A developer needs to determine if a customer review is 'positive', 'negative', or 'neutral' without providing any examples in the prompt itself. Which of the following prompts is best structured to accomplish this task reliably?

You are tasked with classifying the sentiment of the following customer review: 'The user interface is confusing and difficult to navigate.' Construct a complete, self-contained prompt that instructs a language model to perform this classification without providing any examples. Your prompt must explicitly state that the output label should be chosen from the set {positive, negative, neutral}.

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