LLM Classification Is Feature Engineering

The article "LLM Classification Is Feature Engineering" discusses the challenges of using LLMs as classifiers, despite their often decent performance. It presents a detailed prompt template for analyzing tweets along multiple dimensions, including irony, humor, realism, and various rhetorical devices. The prompt uses a MODEL named "gemini-3.1-flash-lite" and aims to classify tweets based on 16 specific criteria, such as self-deprecation, rhetorical questions, and mock enthusiasm, to understand the author's intent and the tweet's underlying message.

This report uniquely provides a detailed, 16-point prompt template for LLM classification, unlike typical discussions that only mention the concept.