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Best Prompt Fix for Sarcasm Detection with Claude API Examples?
Providing labeled sarcastic examples outperforms vague instructions for teaching Claude to detect sarcasm in social posts, ensuring accurate negative sentiment labeling every time.
Question
Claude keeps missing sarcastic comments when analyzing social media posts. What’s the best way to fix this?
A. Ask it to guess when something might be sarcastic
B. Provide examples showing sarcastic posts labeled as negative
C. Tell it to “be more careful about sarcasm”
D. Make the prompt longer with more instructions
Answer
B. Provide examples showing sarcastic posts labeled as negative
Explanation
Few-shot prompting with concrete examples—such as “Post: ‘Wow, great job breaking everything again ‘ Label: negative (sarcastic)”—best fixes Claude missing sarcasm in social media analysis by demonstrating the exact mismatch between literal positive words and implied negative sentiment, training the model in-context to recognize subtle cues like exaggeration, emojis, or irony without vagueness.
Asking to “guess” (A) introduces unreliability, vague warnings like “be more careful” (C) lack specificity Claude ignores under load, and longer instructions (D) dilute focus without demonstration—examples provide precise pattern-matching calibration for consistent detection across varied posts.