Learn Before
Prompt Field Labeling for Clarity and Structure
To improve the clarity and readability of prompts while reducing ambiguity, it is a common practice to format them with distinct fields. These fields are identified by labels (e.g., SYSTEM, USER, Input:, Output:) that structure the prompt and clarify the role of each piece of information for the language model.
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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
Related
Prompt Field Labeling for Clarity and Structure
Code-like Prompt Templates
An engineer is tasked with creating a prompt that instructs a language model to summarize a given text. Below are two versions of the prompt they are considering.
Prompt A: "Please summarize the following text for me. The summary should be exactly two sentences long and maintain a formal tone. The text to summarize is: The quick brown fox jumps over the lazy dog."
Prompt B: "INSTRUCTIONS: Summarize the provided text.
CONSTRAINTS:
- Length: Exactly 2 sentences.
- Tone: Formal.
Refining a Prompt for Clarity
Evaluating Prompt Structure for a Chatbot
Learn After
A developer is creating a prompt to have a language model summarize a news article. The initial prompt, shown below, often results in the model confusing the instructions with the article content itself.
Initial Prompt:
Summarize the following text into three paragraphs. It's about a new AI chip. A new AI chip was announced today by a major tech company. It promises to be 10x faster than previous models...Which of the following revised prompts best uses distinct fields to resolve this ambig
Constructing a Structured Prompt for a Classification Task
Diagnosing Inconsistent LLM Behavior