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Split Sentences

Split prose into individual sentences using natural-language analysis. Great as a chain primitive — feed each sentence to translate, summarize, or sentiment downstream.

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About Split Sentences

Split Sentences breaks a block of prose into individual sentences using natural-language analysis, handling abbreviations and edge cases better than a naive split on periods. It's especially handy as a chain primitive — split first, then feed each sentence into translate, summarize, or sentiment downstream. It runs in your browser on plain text in, plain text out.

Category
text
Input
Accepts: text/plain.
Output
Outputs: text/plain.
Cost
Free, runs in your browser
Memory
low
Privacy: Split Sentences runs entirely on your device. Files you provide never leave your browser — no uploads, no server, no tracking. The page works offline once loaded.

Common uses

  • Break an article into one-sentence-per-line form before translating each line individually
  • Prepare text for sentence-level sentiment or classification in a tool chain
  • Split a paragraph into sentences to review them one at a time while editing
  • Generate flashcard-style lines from a study passage
  • Segment a transcript into sentences before further processing
  • Count or sample sentences from a document for a writing analysis

Frequently asked questions

How does it decide where a sentence ends?

It uses natural-language analysis rather than splitting blindly on every period, so common abbreviations and decimals are handled more sensibly than a simple find-and-split.

What goes in and what comes out?

Plain text in, plain text out — one sentence per line, ready to feed into another tool.

Does it send my text anywhere?

No. The analysis runs entirely in your browser, so the text stays on your device.

Is there a length limit?

It's built for ordinary prose; very large documents may be slower since everything runs locally, but there's no upload step.

Why use this instead of splitting on periods myself?

Naive splitting mishandles abbreviations, decimals, and quotes. This produces cleaner sentence boundaries, which matters when each sentence feeds a downstream tool.

Keywords

  • sentences
  • split
  • tokenize
  • segment
  • nlp
  • compromise

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