Here's a breakdown:
* Antecedent: This refers to the "prior" or "preceding" part of something. In this case, the antecedent is the initial prompt that sets the stage.
* Prompt: This is the text input given to the language model.
How it works:
1. Provide an initial prompt: You start by providing the model with a sentence or phrase that establishes the context. For example: "The cat sat on the mat."
2. Model generates text based on the prompt: The model will use the provided context to generate a continuation of the text. For example, it might generate: "The cat sat on the mat and purred."
3. Antecedent influences the output: The model's understanding of the initial prompt (the antecedent) influences the generated text, making it more relevant and coherent.
Examples of antecedent prompts:
* "Once upon a time..." (for generating a story)
* "The weather was..." (for describing a scene)
* "I went to the store and bought..." (for writing a shopping list)
Why antecedent prompts are important:
* Provide context: They help the model understand the situation and generate more relevant text.
* Control the direction of text generation: By choosing specific antecedent prompts, you can influence the output in a desired way.
* Improve coherence and consistency: Antecedent prompts can help to create more cohesive and consistent text by providing a framework for the model to follow.
In essence, antecedent prompts are like setting the stage for a story, giving the language model a starting point and a sense of direction for its output.