Remove Sentences Online
Delete specific sentences from any text. Match by keyword (case-insensitive), by sentence index (the 1st, 3rd, every other), by length (shortest, longest), or by regex pattern. The output panel previews exactly which sentences will go. Useful for trimming AI-generated drafts, removing boilerplate, cutting filler from transcripts.
How to use the sentence remover
1. Paste your text
Drop a draft, transcript, AI-generated paragraph, or any multi-sentence string into the input. The tool segments it into individual sentences automatically.
2. Pick a match mode
Four modes available. Keyword: remove sentences containing a specific word (case-insensitive). Length: remove sentences shorter or longer than N characters (e.g. ">120" or "<80"). Index: remove the 1st, 3rd, 5th sentence (type "1,3,5" or "every-other"). Regex: provide a JS regex pattern; matching sentences will be stripped. See also: word replacer.
3. Preview before stripping
The preview panel shows every sentence color-coded: green = will stay, red strikethrough = will be removed. Scan to confirm the rule does what you intend. Adjust the keyword / length / regex until the preview matches your intent.
4. Copy the cleaned output
The output box shows the surviving sentences joined into a single paragraph. Copy and paste into your document, email, or transcript editor.
When you need to remove sentences
Trimming AI-generated drafts
AI writing tools (ChatGPT, Claude, Gemini) often produce filler sentences. "Let me know if you have any questions." "Please feel free to reach out." "I hope this helps." Strip them all with keyword mode set to "feel free" or "let me know." See also: character remover. See also: remove punctuation.
Removing boilerplate from transcripts
Interview transcripts include filler ("Yeah, totally", "Right, right, exactly"). Index mode lets you strip every other sentence if the speaker turns are predictable, or use keyword mode for specific filler phrases.
Cutting filler from podcast / video transcripts
Auto-generated transcripts include "um", "uh", "you know" all over. Regex mode handles these in bulk: pattern \b(um|uh|you know|like)\b finds every sentence containing one of those filler words.
Editing email drafts for brevity
Your email is too long. Strip the longest sentences (mode = length, set to ">160") to find which sentences are bloated. Rewrite them or remove them.
Removing customer-service boilerplate
Outbound emails often include legally-required boilerplate ("Your privacy is important to us...") that you want stripped before customer review. Keyword mode handles it in one click.
Citation removal for paraphrasing
If you have a quoted block with inline citations (Smith, 2024), regex mode with \([A-Z][a-z]+, \d{4}\) finds sentences with citations and strips them. Useful for paraphrasing prep.
The four match modes in detail
Keyword mode
Plain text matching, case-insensitive. Type a single word ("patience") to strip every sentence containing that word. Type multiple words separated by space ("thank you") to strip sentences containing the phrase "thank you" (substring match). The match is not whole-word - "patient" matches "patience". For whole-word matching, use regex mode with \bpatience\b.
Length mode
Format: a single character (> or <) followed by a number. ">120" removes sentences longer than 120 characters. "<80" removes sentences shorter than 80 characters. Use this to trim verbose drafts (remove anything >160 chars) or strip filler (remove anything <20 chars, catching "Yes." and "Right.").
Index mode
Comma-separated list of 1-indexed sentence numbers to remove. "1,3,5" removes the 1st, 3rd, and 5th sentence. The special string "every-other" removes every other sentence (2nd, 4th, 6th...). Useful for trimming alternating speaker patterns in transcripts.
Regex mode
Provide a JavaScript regex pattern (no slashes; case-insensitive flag is automatic). Examples:
\bthank you\b- sentences containing the phrase "thank you" as a whole word\d{3}-\d{3}-\d{4}- sentences containing a US-format phone number^[A-Z]+!$- sentences that are ALL CAPS exclamations\([A-Z][a-z]+, \d{4}\)- sentences containing an APA-style citation
Invalid regex patterns silently match nothing (no error). Watch the preview to confirm your pattern actually matches what you intended.
How the tool detects sentence boundaries
Sentence-splitting uses regex matching against runs of non-terminator characters followed by one or more sentence-ending punctuation marks (period, exclamation, question mark). It is a fast approximation, not a full NLP-grade sentence tokenizer. Edge cases:
- Abbreviations with periods (Mr. Smith, U.S.A.) split incorrectly - "Mr." gets treated as a sentence end. Workaround: type your text without periods inside abbreviations, then add them back after stripping.
- Quotation marks: a sentence ending inside a quote ("He said, 'Hello.' Then she left.") splits correctly because the period is the terminator.
- Run-on sentences without punctuation: get treated as one giant sentence (correctly, even if the writer didn't intend that).
- Multiple terminators: "Really?!" is one sentence; the tool handles consecutive terminators correctly.
For NLP-grade tokenization (medical, legal, multi-language text), use a server-side tool like spaCy. For routine prose, this tool is fast enough and accurate enough.
Related tools
Frequently asked questions
How does the tool detect sentence boundaries?
Regex-based: it looks for runs of text terminated by . ! or ? (one or more). It's a fast approximation, not full NLP-grade tokenization. Abbreviations with periods (Mr., U.S.A.) split incorrectly - workaround is to remove periods inside abbreviations before stripping.
Can I match multiple keywords at once?
Yes, via regex mode. Pattern \b(thank you|please|sincerely)\b matches any sentence containing 'thank you', 'please', or 'sincerely'.
What's the difference between length-mode '>120' and '<80'?
'>120' removes sentences longer than 120 characters (good for trimming bloat). '<80' removes sentences shorter than 80 characters (good for stripping filler like 'Yeah.' and 'Right.').
How does 'every-other' index mode work?
It removes the 2nd, 4th, 6th, 8th... sentences. Useful for transcripts where alternating speaker turns produce filler responses you want to strip.
Is the keyword match whole-word or substring?
Substring. Typing 'patience' matches 'patient' too. For whole-word matching, use regex mode with \bpatience\b.
Can the tool handle bulk deletion of citations like (Smith, 2024)?
Yes, via regex mode. Pattern \([A-Z][a-z]+, \d{4}\) matches sentences containing an APA-style citation. Useful for paraphrasing prep.
Will my text be sent to a server?
No. The sentence remover runs entirely in your browser. Drafts, transcripts, and any sensitive text stay in this tab.
What if my text has no sentence-ending punctuation?
The tool treats the entire input as one sentence. Length mode and regex mode still work; keyword mode applies to the whole text; index mode only has index 1.
More wordcounter.ai tools
Other tools you might find useful.