PE-MTHRFCKR
  • Prompt Engineering Guide
    • Introduction
    • LLM Settings
    • Basics of Prompting
    • Elements of a Prompt
    • General Tips for Designing Prompts
    • Examples of Prompts
    • Prompting Techniques
    • Zero-Shot Prompting
    • Few-Shot Prompting
    • Chain-of-Thought Prompting
    • Self-Consistency
    • Generated Knowledge Prompting
    • Automatic Prompt Engineer (APE)
    • Active-Prompt
    • Directional Stimulus Prompting
    • ReAct Prompting
    • Multimodal CoT Prompting
    • GraphPrompts
    • Prompting Applications
    • PAL (Program-Aided Language Models)
    • Generating Data
    • Graduate Job Classification Case Study
    • Models
    • Scaling Instruction-Finetuned Language Models
    • ChatGPT Prompt Engineering
    • Llama
    • GPT-4
    • Model Collection
    • Risks & Misuses
    • Adversarial Prompting
    • Factuality
    • Biases
    • Papers
    • Tools & Libraries
    • Prompt Engineering Notebooks
    • Datasets
    • Additional Readings
  • Complex ChatGPT Prompts
    • C–Context
    • H–Heritage
    • A–Aim
    • T–Tone
    • GPT
    • Example of ChatGPT-method
  • The Art of ChatGPT Prompting
    • Preface
    • Introduction
    • What is ChatGPT and How Does it Work?
    • The Role of Prompts in ChatGPT Conversations
    • Principles of Clear Communication
    • Constructing Effective Prompts
    • Common Mistakes to Avoid When Crafting ChatGPT Prompts
    • Troubleshooting
    • Technical Issues
    • Case Studies
    • Conclusion
  • Prompt Engineering 101
    • Include direct instructions in prompts
    • Give examples in prompts to get the best response
    • Align prompt instructions with the task’s end goal
    • Use personas to get more specific voices
    • Include acceptable responses in prompts for consistency
    • Try different prompts to find what works best
    • Summary
  • Mastering ChatGPT
    • I. Introduction
    • II. Understanding Prompts
    • III. Tips for Crafting Effective Prompts
    • IV. Advanced Hacks and Techniques
    • V. Avoiding Common Pitfalls
    • VI. Real-life ChatGPT Examples and Case Studies
    • VII. Conclusion
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  1. Prompt Engineering Guide

Elements of a Prompt

PreviousBasics of PromptingNextGeneral Tips for Designing Prompts

Last updated 2 years ago

As we cover more and more examples and applications that are possible with prompt engineering, you will notice that there are certain elements that make up a prompt.

A prompt can contain any of the following components:

Instruction - a specific task or instruction you want the model to perform

Context - can involve external information or additional context that can steer the model to better responses

Input Data - is the input or question that we are interested to find a response for

Output Indicator - indicates the type or format of the output.

Not all the components are required for a prompt and the format depends on the task at hand. We will touch on more concrete examples in upcoming guides.

Basics of Prompting
General Tips for Designing Prompts