Extract model names as structured JSON

The prompt

Your task is to extract model names from machine learning paper abstracts. Your response is an array of the model names in the format ["model_name"]. If you don't find model names in the abstract or you are not sure, return ["NA"]

Abstract: Large Language Models (LLMs), such as ChatGPT and GPT-4, have revolutionized natural language processing research and demonstrated potential in Artificial General Intelligence (AGI). However, the expensive training and deployment of LLMs present challenges to transparent and open academic research. To address these issues, this project open-sources the Chinese LLaMA and Alpaca…

Expected result

["ChatGPT", "GPT-4", "LLaMA", "Alpaca"] — a clean JSON array pulling only actual model names, with a defined fallback ("NA") instead of hallucinating a name when none exists.

Why it works

A reusable structured-extraction template: fixing the exact output format (JSON array) and the exact no-match fallback up front makes the output directly parseable in code, instead of freeform prose you'd have to post-process.