Overview
Introduction
Leftover lorem-ipsum placeholder sentences sometimes survive into a draft after real copy is written around them, and hunting them down by eye is tedious.
This tool finds and removes them automatically, leaving your genuine sentences untouched.
What Is Fake Text Remover?
A cleanup tool that splits text into sentences, measures how much of each sentence's vocabulary overlaps with the standard lorem-ipsum word pool, and removes any sentence over your chosen threshold.
It runs entirely client-side as part of this site's String Tools collection, so nothing you paste is ever uploaded to a server.
How Fake Text Remover Works
The tool splits the input on sentence-ending punctuation, lowercases and tokenizes each sentence's words, and computes the percentage of those words found in the fixed lorem-ipsum word pool; sentences at or above the threshold are dropped and the rest are rejoined.
The transformation happens synchronously in JavaScript the moment you type or adjust the threshold, with no network round trip involved.
When To Use Fake Text Remover
Use it right before publishing a page or document to catch any lorem-ipsum sentences that were never replaced with real copy.
It's a fast way to get the answer without opening a code editor, a REPL, or writing a one-off script just to check.
Often used alongside Fake Text Generator, Fake Text Checker and Empty Line Remover.
Features
Advantages
- Removes whole sentences rather than individual words, keeping surrounding genuine text readable.
- Threshold is adjustable, so you can tune how aggressively it flags borderline sentences.
Limitations
- Detection is based purely on word-pool overlap, not grammar or meaning, so an unusual real sentence built mostly from short common words could theoretically be misflagged.
- Sentence splitting relies on standard punctuation and may not perfectly handle abbreviations like "e.g." inside a sentence.
Examples
Best Practices & Notes
Best Practices
- Start with the default threshold and only lower it if boilerplate sentences are slipping through.
- Run this as a final pass before publishing, after all real copy has been written.
Developer Notes
Sentences are extracted with the regex /[^.!?]+[.!?]*/g rather than a full sentence tokenizer, which is intentionally simple: it treats each run up to and including its terminating punctuation as one sentence, and keeps sentences whose lorem-ipsum word ratio falls below the threshold.
Fake Text Remover Use Cases
- Cleaning leftover lorem-ipsum sentences out of a drafted page before publishing
- Auditing a large document for stray placeholder paragraphs
- Sanitizing content pulled from a CMS template that still contains boilerplate
Common Mistakes
- Setting the threshold too low and accidentally removing genuine sentences built from very common short words.
- Assuming it can detect AI-generated or otherwise low-quality text; it only detects overlap with the specific lorem-ipsum vocabulary.
Tips
- Run the Fake Text Checker tool first to see your overall placeholder-word percentage before deciding how aggressive a threshold to use here.