Constructing a Contextual Prompt for a Multi-Step Problem
Based on the provided scenario, construct the complete and ideal input that should be provided to the language model to solve the second sub-problem. Your constructed input must ensure the model has the necessary context from the first step to continue the problem-solving process.
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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
Application in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
Science
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Example of Sequential Sub-Problem Solving: Environmental Study Duration
A problem is being solved in sequential steps. The overall goal is to 'Calculate the total profit from selling 200 widgets.' The first step was to ask, 'What is the revenue from selling 200 widgets if each widget sells for $15?', to which a model answered, 'The revenue is $3000.' Now, to solve the next part of the problem, you need to ask the model, 'What is the total cost of producing 200 widgets if the production cost per widget is $8?'. Which of the following is the most effective and complete prompt to send to the model for this second step?
Constructing a Contextual Prompt for a Multi-Step Problem
Analyzing a Flawed Multi-Step Prompt