Improving a Faulty Classification Prompt
Based on the principles of effective instruction design for classification, rewrite the team's instruction to solve the two main problems: conversational outputs and the lack of a neutral category. Explain the reasoning behind your changes.
0
1
Tags
Ch.1 Pre-training - Foundations of Large Language Models
Foundations of Large Language Models
Computing Sciences
Ch.3 Prompting - Foundations of Large Language Models
Foundations of Large Language Models Course
Application in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
Science
Related
Example of a Negative Input for Polarity Classification
Examples of Positive Inputs for Polarity Classification
Example of a Prompt with a Post-Input Instruction for Polarity Classification
A developer needs a language model to classify customer feedback into one of three categories: 'positive', 'negative', or 'neutral'. The primary goal is to ensure the model's output is only one of these three words, without any additional explanation or conversational text. Which of the following instruction-based prompts is most effective for this specific requirement?
Analyze the following instruction-based prompts designed for a text classification task. Match each prompt to the description that best characterizes its primary approach.
Improving a Faulty Classification Prompt