I started this after my dad and I spent 45 minutes arguing over an immigration article where we were both citing different sources reporting the same statistic at different numbers, and neither of us could figure out who was right because we couldn’t agree on which source to trust. My first instinct was a binary fact-checker that returns TRUE or FALSE, but the first time I prompted Claude that way I got confident verdicts with no sources and realized immediately that a confidently wrong answer with no citations is worse than no answer at all. I tried GPT-4 for claim extraction and kept getting paragraph-length analysis instead of a JSON array, then switched to Claude and got clean structured output on the first attempt once I tightened the prompt.

Extract factual claims from the article below. Return ONLY a JSON array of strings.
No explanation before the array. No explanation after. No markdown fences.

I finished the session with a Python script that takes pasted article text and returns a JSON array of 5-8 discrete factual claims, all traceable to specific sentences in the article.