Improving a Prompt for a Novel Classification Task
A software development team is using a large language model to sort user feedback for their new video editing application. They want to classify each piece of feedback into one of three custom categories: 'UI/UX Suggestion', 'Bug Report', or 'Feature Request'.
The team uses the following prompt: Classify the user feedback below.
They find that the model's classifications are inconsistent and often incorrect, frequently miscategorizing bug reports as feature requests. Analyze why this prompt is ineffective for this specific task. Then, describe two distinct, specific improvements that could be made to the prompt's description to help the model perform the classification more accurately, without providing examples of classified feedback.
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Ch.3 Prompting - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Analysis in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
Science
Related
Few-Shot Learning
A data scientist wants to use a large language model to categorize internal company documents into three newly-defined, specific categories: 'Alpha Project Brief', 'Beta Project Brief', and 'Gamma Project Brief'. The model has not been specifically trained on this internal classification system. Which of the following prompts is best designed to achieve the most accurate and consistent results for this task?
Improving a Prompt for a Novel Classification Task
Evaluating a Prompt for a Custom Classification Task