For a sentiment classification task (positive/negative/neutral), which prompt structure gives the MOST reliable and parseable output?
Select an answer to reveal the explanation.
Short Explanation and Infographic
For classification, constrain the output to exactly the label you need — 'respond with one word: positive, negative, or neutral' gives you machine-parseable output directly.
Full explanation below image
Full Explanation
For classification tasks in production, constrained output prompts are essential. Specifying the exact allowed output values and format (e.g., 'respond with exactly one word from: positive, negative, neutral') produces outputs that can be parsed programmatically without ambiguity. This eliminates preamble, explanation, and variation in label format. Option A generates free text requiring NLP parsing to extract sentiment — fragile. Option C produces verbose explanations instead of labels. Option D is counterproductive — high temperature introduces randomness, which is the opposite of what classification needs (low temperature is correct).