How to set up ChatGPT to summarize 100-page whitepapers
I'm building a process to chunk and summarize large whitepapers into executive briefs using ChatGPT; need recommended chunk sizes, prompt chain patterns, and QA checks to avoid hallucinations.
Best tools for this use case
Based on the workflow in this discussion, these tools are useful starting points to review.
ChatGPT
Best all-round AI assistant for broad knowledge work and workflow acceleration.
Claude
Excellent for careful reasoning, long-form thinking and structured analysis.
Gemini
Strong AI assistant for users already working inside Google's ecosystem.
Answers
Approved replies, operator insight, and tactical follow-up from the community.
Chunk 1,500–3,000 tokens (~1–3 pages) with 100–200 token overlap; chunk by logical section headings. Prompt chain: (1) extract headings, claims and data points with page refs per chunk; (2) produce a 3-bullet micro-summary + one supporting quote; (3) merge summaries into a thematic synthesis and flag contradictions; (4) output a 200–350 word executive brief plus an evidence table. QA: require exact quotes+page numbers, run a claim-to-source checker and re-run low-confidence claims, sample 10% manual checks. For long-context work, consider Claude. Compare options: Compare Claude and ChatGPT