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A prompt for a grammar correction task can be structured to guide a Large Language Model by defining its persona, the nature of the input, and the expected output. For instance, a complete prompt might look like this:

`You are a helpful assistant, and are great at grammar correction.`

`You will be provided with a sentence in English. The task is to output the correct sentence.`

`Input: She don’t like going to the park.`

This example first establishes the model's role as a grammar expert, then specifies the task, and finally provides the actual input sentence, clearly labeled with the 'Input:' field.

Example of a Persona-based Prompt for Grammar Correction

When presenting examples of prompts, visual formatting such as colored text can be used to distinguish different structural parts, known as fields. For instance, field labels like 'Input:' might be displayed in gray to separate them from the actual content of the prompt.

Using Visual Cues to Differentiate Prompt Fields

A user is trying to get a language model to correct grammar but is receiving inconsistent and sometimes unhelpful responses. The user's current instruction is simply: `Fix this: i goes to the store yesterday`.

Based on the principles of structuring effective instructions, analyze the user's current approach. Identify its primary weakness and rewrite the instruction to be more effective by clearly defining the model's role, the task, and the input.

Improving a Flawed Prompt for Grammar Correction

A user wants to rephrase the sentence 'I think we should totally do this' to sound more professional for a business email. Construct a complete, well-structured prompt to guide a language model to perform this task. Your prompt should include a role for the model to adopt, a clear instruction, and the specific text to be changed.

Constructing a Prompt for Text Rephrasing

A user wants a language model to summarize a short paragraph into a single sentence. Considering the goal of creating a clear and effective set of instructions, which of the following prompts is better structured to guide the model towards the desired output?

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