Evaluating and Improving a Prompt for Sentiment Analysis
A marketing analyst is using a large language model to sort customer reviews for a new smartphone. They need to classify each review as 'Positive', 'Negative', or 'Neutral' without providing the model with any pre-labeled examples. The analyst's current prompt is failing to produce consistent results. Analyze the provided prompt and case details, explain why the prompt is ineffective, and then construct a revised prompt that would be more successful for this task.
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Ch.1 Pre-training - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Evaluation in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
Science
Related
A software developer needs to categorize user feedback as either a 'bug report' or a 'feature request' using a language model. The developer has no pre-labeled examples to show the model. Which of the following prompts is the most effective and appropriate way to instruct the model to perform this task?
Constructing a Zero-Shot Prompt for Ticket Classification
Evaluating and Improving a Prompt for Sentiment Analysis