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Designing Annotation Guidelines for Prompt Creation
Imagine you are managing a project to create prompts for a large language model. The goal is to have the model perform sentiment analysis on customer product reviews, classifying them as 'Positive', 'Negative', or 'Neutral'. Your task is to design a set of clear annotation guidelines for the human writers who will be creating these prompts. What key sections and instructions would you include in these guidelines to ensure the prompts are high-quality and consistent?
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Ch.4 Alignment - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Creation in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
Science
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Evaluating a Prompt Generation Workflow
A team is developing prompts for a text summarization task. They provide annotators with examples of source texts and their corresponding high-quality summaries. Despite this, the prompts created by different annotators are inconsistent in their phrasing and structure, causing the language model to produce summaries of varying quality. What is the most critical element missing from their prompt creation management process?
Designing Annotation Guidelines for Prompt Creation