Defining Answer Format and Semantics in Prompts
To control the output of a language model, a prompt can include explicit instructions that specify the desired answer format and define the meaning of each possible response. For a grammaticality judgment task, this could involve instructing the model to answer only with 'Yes' or 'No', and clarifying that 'Yes' confirms the sentence is grammatically correct, while 'No' indicates it contains grammatical errors.
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Ch.2 Generative Models - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
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Defining Answer Format and Semantics in Prompts
A researcher wants to test a language model's ability to judge the grammar of various sentences. They decide that for their experiment, the prompt must present the sentence to be evaluated before asking the model to make a judgment. Which of the following prompt designs meets this specific structural requirement?
Analyze the structure of each prompt template below and match it with the correct description of its format.
Improving Prompt Design for Grammaticality Judgment
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Example of Defining Answer Semantics for Grammaticality Judgment
Example of Defining Category Semantics in a Polarity Classification Prompt
A data scientist is using a language model to classify customer feedback into 'Bug Report' or 'Feature Request'. Their initial prompt is:
Feedback: 'The app crashes when I try to upload a photo.' What kind of feedback is this?They observe that the model's outputs are inconsistent, including responses like 'This is a bug report,' 'It seems like a bug,' and 'The user is reporting a problem with the app.' Which of the following revised prompts best addresses this inconsistency by explicitly defining the required output format and the meaning of the categories?Improving Prompt Specificity for Automated Data Extraction
Refining a Prompt for Feature Request Identification
Example of a Constraint-First Prompt for Grammaticality Judgment