A prompt is made up of three key elements: segmentation, keywords and structuring. These elements play an essential role in AI's understanding and generation of natural language. Let's see in more detail what these elements are and how to use them.
Prompt segmentation consists of dividing a prompt into segments so that the AI better understands the request. A segment is a part of the prompt that contains information, an instruction or an indication for the AI. A segment can be a word, a phrase, or a paragraph. A segment can be separated from other segments by a punctuation mark, a line break, or a special symbol. Segmenting a prompt helps clarify, specify, and organize the query for the AI. For example, if the prompt is "A poem about love, with rhymes and metaphors", it can be divided into three segments:
1. A poem about love: the first segment indicates the type and theme of the expected content.
2. With rhymes: the second segment indicates a formal restriction of the expected content.
3. And metaphors: the third segment indicates a stylistic characteristic of the expected content.
4. Keyword identification consists of choosing relevant keywords in each segment of the prompt to guide the AI's response. A keyword is a word that has particular importance to the query, expressing an intent, request, or preference to the AI. A keyword can be a noun, a verb, an adjective or an adverb. Identifying keywords helps focus, target, and influence the AI response. For example, in the segmented prompt "A poem about love, with rhymes and metaphors", the following keywords can be identified:
a. Poem: the keyword of the first segment indicates the type of content expected, which is a poetic text.
b. Love: the keyword of the first segment indicates the theme of the expected content, which is a universal feeling.
c. Rhymes: the keyword of the second segment indicates a formal restriction of the expected content, which is the repetition of sounds at the end of the verses.
d. Metaphors: the keyword of the third segment indicates a stylistic characteristic of the expected content, which is the implicit comparison of two realities.
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