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Summarization shrinks long text into a short version that keeps the key points. There are two main strategies, and knowing both helps you pick the right tool. 📝

An extractive summary copies the most important sentences straight out of the source. Nothing is reworded, so the output is always faithful to the original.

An abstractive summary writes brand-new sentences that paraphrase the meaning. It reads more naturally, much like a human would summarize a story.

The core difference is simple: extractive methods select existing text, while abstractive methods generate fresh text. One picks, the other paraphrases.

Because it reuses original sentences, extractive summarization rarely invents facts. That makes it a safe choice for legal, medical, or financial text.

Abstractive models can merge ideas from several sentences into one smooth line. The result is more concise and readable than a stack of copied sentences.

Because it generates new words, an abstractive model can sometimes state facts that were never in the source. This mistake is called a hallucination. ⚠️

A basic extractive approach scores each sentence, then keeps the top ones. Here we just take the first two sentences as a quick baseline.

Today's transformer summarizers are mostly abstractive. They read the whole text, then write a fresh, human-sounding summary from scratch.

Need guaranteed faithfulness? Choose extractive. Need a fluent, natural read and can verify facts? Reach for abstractive instead.

Either approach only works well on clean, well-structured text. Garbled input leads to confusing or misleading summaries every time.

Which approach writes brand-new sentences instead of copying them?

You learned the two summarization styles: extractive copies key sentences and stays faithful, while abstractive paraphrases for fluency but can hallucinate. 🎯