DEFINITION
Chain of thought prompting is used to get a large language model to think about their reasoning process. It can be useful to help organise calculations, identify relationships and decompose the question into more manageable parts. This will depend on the model and the question you’re giving it. Having a longer explanation doesn’t necessarily mean the answer will be correct. It can also be important to provide clear instructions and examples, and allow the model to self validate.
Why Use Chain of Thought Prompting?
- Helps with solving complex questions with multiple steps.
- Can assist with calculations.
- Helps to decompose the problem.
- Helps to explain the reasoning process or provide explanations.
When to Use Chain of Thought Prompting?
- To solve a multi step mathematical or logical question.
- Analyze business situations with multiple conditions.
- Decompose complex data interpretation questions.
- Help provide a structured plan.
- Explain the steps in a calculation or decision.
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