Paraphrase Similarity

Compare two passages to see how closely they match—even when wording changes. Paraphrase Similarity estimates overlap and meaning-level similarity between Text A and Text B, then summarizes the result into a score, confidence, and risk level. It’s useful for checking whether a revision is truly distinct, evaluating potential reuse, or verifying that a paraphrase still reflects the original meaning. Similarity is contextual: a high score may be expected for definitions or technical descriptions, while a high score in narrative text may require attribution or rewriting. Use the tool to guide review, then inspect the overlapping sections yourself.

Note
This is an automated similarity estimate (lexical overlap + semantic embeddings). Use it to compare drafts and spot overlap to review; it does not determine intent, policy violations, or authorship.
Paraphrase Similarity Report
Generated: 2/28/2026, 2:32:48 PM

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About

Paraphrase Similarity compares two texts and estimates how similar they are. It is designed for revision checks and reuse review.

How it works

Provide Text A and Text B, then run the check. The tool computes similarity signals and summarizes them as a score, confidence, and risk level.

  • Compares two inputs
  • Summarizes overlap and similarity signals
  • Helps identify whether changes are substantial
Result interpretation

A higher score indicates the two texts are closer in wording or meaning. Confidence reflects internal signal agreement; short texts reduce reliability.

Use cases

Use it to compare drafts, check whether a paraphrase is sufficiently distinct, or review suspected reuse between two passages.

  • Draft-to-draft comparisons
  • Paraphrase review
  • Internal compliance checks
Limitations

Similarity depends on length and domain. Two short sentences can appear highly similar. Deep paraphrases may still require manual review.

Best practices

Compare meaningful sections (multiple paragraphs when possible). If similarity is high, rewrite structure—not just synonyms—and add attribution when required.

Related reading

Useful when similarity “feels wrong” — often it’s a mode/expectation mismatch.

FAQ

What similarity is “too high”?
It depends on the use case. Look at overlapping sections and whether attribution is required.
Can it detect paraphrasing?
It can help, but subtle paraphrases may require manual review.

Integrity and privacy

Integrity
  • Designed to report similarity signals for review and revision.
  • Best used alongside manual inspection of overlapping sections.
Privacy
  • Inputs are sent to the API to compute results. Avoid pasting sensitive personal data.
  • When comparing confidential drafts, use only the passages needed for review.
Last updated: Dec 07, 2025