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Constructing a Follow-Up Prompt for Incomplete Reasoning
You provide the following query to a large language model:
Initial Query: "A train leaves City A at 9:00 AM traveling at 60 mph. A second train leaves City B, 300 miles away, at the same time, traveling towards City A at 90 mph. At what time will they meet?"
The model provides the following incomplete response:
Model's Reasoning: "Let's think step by step. The two trains are moving towards each other. Their combined speed is the sum of their individual speeds. So, the combined speed is 60 mph + 90 mph = 150 mph. The total distance to cover is 300 miles."
Your task is to write the complete text for a second-round prompt that will guide the model to provide the final answer, based on the principle of combining the original query with the model's generated reasoning.
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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
Creation in Bloom's Taxonomy
Cognitive Psychology
Psychology
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A user provides the following query to a large language model: "A grocery store has 5 apples. They buy 3 more bags of apples, with 4 apples in each bag. They then sell 7 apples. How many apples do they have left?"
The model returns the following text, which includes reasoning steps but does not state the final answer: "Okay, let's break this down. First, we calculate the total number of new apples: 3 bags * 4 apples/bag = 12 apples. The store started with 5 apples, so the new total is 5 + 12 = 17 apples. Then, 7 apples are sold."
To guide the model to provide the final answer in a subsequent turn, which of the following inputs best describes the content that should be sent as the next prompt?
Constructing a Follow-Up Prompt for Incomplete Reasoning
Resolving an Incomplete LLM Response