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Example of a Name:Content Prompt for Task Specification
The 'name:content' format can be extended to outline complex task specifications. For example, a machine translation task can be formally described by defining its parameters: Task: Translation, Source language: English, Target language: Chinese, and Style: Formal text. This is followed by the actual prompt template, such as Template: Translate the following sentence: {*sentence*}. This clear, field-based structure helps guide the language model accurately.
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Foundations of Large Language Models
Ch.3 Prompting - Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
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Example of a Name:Content Prompt for Question-Answering
Example of a Code-like Prompt for Machine Translation
Storing Prompt Data in Key-Value Formats like JSON
Example of a Code-Style Demonstration for English-to-German Translation
Examples of Key-Value Pairs in a Code-Style Translation Prompt
A developer is building a system to extract structured information from customer support emails. Their initial prompt, 'From the following email, extract the customer's name, order number, and the core issue,' often results in the language model producing a long, narrative paragraph that mixes the requested information with other details. Which of the following best explains why adopting a
name:contentformatting style, where the model is prompted to complete fields likecustomer_name:,order_number:, andissue_summary:, would be a more effective strategy?Designing a Structured Prompt for Recipe Generation
A developer is creating a few-shot prompt to teach a language model how to convert informal user requests into a structured JSON object for an internal API. The goal is to extract the user's name and the item they want to order. Which of the following prompts most effectively uses a clear, key-value formatting style to structure the task and guide the model toward a reliable output?
Example of a Name:Content Prompt for Task Specification