Selecting what matters
Summarization takes a long document, report, or conversation and condenses the important parts into a shorter, clearer form. Asking an assistant to give you a three-line version of an article, or to pull out only the decisions from a meeting, is the everyday case.
It is not truncation. It requires judging what is important and preserving how the parts connect while reducing the volume. Because the right summary depends on the reader, the purpose, and the length, one source text has no single correct summary.
Extractive and abstractive
Extractive summarization picks important sentences from the original and presents them as they are. Nothing is rewritten, so it is easy to check against the source, but the result can read disjointedly.
Abstractive summarization has the model understand the content and write new prose. It produces something short and natural, but it can add explanation that was not in the original, or alter numbers and names.
Asking well
- Say who the summary is for
- Specify length, number of lines, or bullet format
- Name what must survive — conclusions, decisions, figures
- Instruct it to use only the source and not add inference
- Ask for the original page or section alongside key points
“Summarize this” works, but “200 words for a beginner, keep proper nouns and figures” produces something far more usable.
What a summary loses
Exceptions, preconditions, dissenting views, and nuance are exactly what gets dropped. For contracts, medical information, or financial filings, do not decide from the summary alone.
Summaries can also hallucinate or misread. Check figures, dates, names, and quotations against the original. And if a long document does not fit the context window, the model may have summarized only part of it.