Remove Sentences from Text

The tool searches for keywords within sentences, not exact phrase matches. It splits your text into sentences (using periods, exclamation marks, question marks), then checks if each sentence contains any of your specified keywords. If a match is found, the entire sentence is removed. Example: Keywords: 'spam', 'advertisement'. Sentence: 'This is spam content.' → REMOVED (contains 'spam'). Sentence: 'Buy now, limited offer!' → REMOVED if 'advertisement' or related keyword. Sentence: 'Normal text here.' → KEPT (no keywords). This is much more powerful than exact phrase matching.

Match All (AND) removes sentences only if they contain ALL specified keywords. Match Any (OR - default) removes sentences if they contain ANY keyword. Examples with keywords 'spam', 'free': Match Any (OR): 'Get free stuff' → REMOVED (has 'free'). 'This is spam' → REMOVED (has 'spam'). 'Free spam offer' → REMOVED (has both). Match All (AND): 'Get free stuff' → KEPT (only has 'free', missing 'spam'). 'This is spam' → KEPT (only has 'spam', missing 'free'). 'Free spam offer' → REMOVED (has both). Use AND for precise filtering (e.g., remove only if 'urgent' AND 'action required' appear together).

The tool uses smart sentence splitting that recognizes standard sentence-ending punctuation: periods (.), exclamation marks (!), and question marks (?). It preserves the original punctuation when reconstructing the cleaned text. After removing unwanted sentences, the tool automatically cleans up extra spaces and fixes punctuation spacing. Example: 'Hello. Remove this spam. Goodbye!' → Keywords: 'spam' → Result: 'Hello. Goodbye!' (middle sentence removed, spacing fixed automatically). The algorithm maintains text flow and readability after removal.

The statistics panel shows 4 key metrics: Original: Total sentences in input. Removed: Number of sentences deleted (containing keywords). Kept: Number of sentences remaining in output. Rate: Percentage of sentences removed (indicates filtering intensity). Additionally, you get a preview of removed sentences (first 5 shown) so you can verify the correct sentences were filtered. Example: 50 original sentences, 12 removed, 38 kept = 24% removal rate. Check the preview to ensure no false positives.

Use Case Sensitive when capitalization distinguishes different meanings. Examples: Remove 'Apple' (company) but keep 'apple' (fruit). Remove 'IT' (department) but keep 'it' (pronoun). Remove 'US' (country) but keep 'us' (pronoun). Remove 'May' (month) but keep 'may' (modal verb). Leave it OFF (default) for general keyword filtering where 'Spam', 'SPAM', and 'spam' should all trigger sentence removal. Case sensitive is crucial when keywords have multiple meanings based on capitalization.

Content Moderation: Remove sentences containing profanity, slurs, or banned terms from user comments. Redaction: Delete sentences with confidential keywords ('salary', 'SSN', 'password') before sharing documents. Data Cleaning: Remove sentences containing error markers, debug logs, or unwanted metadata from scraped text. Email Filtering: Delete sentences with spam indicators ('click here', 'limited offer', 'act now'). Research: Filter out sentences containing specific topics or concepts from large text datasets. Quality Control: Remove boilerplate sentences containing template markers from generated content.

Partially. This tool operates at the sentence level, not paragraph level. If a paragraph contains multiple sentences and only one has your keyword, only that sentence is removed, leaving other sentences in the paragraph intact. For full paragraph removal, use keywords that appear in every sentence of unwanted paragraphs, or use the 'Remove Paragraphs' tool (dedicated paragraph-level filtering). This sentence-level approach is ideal for surgical removal of specific problematic statements within otherwise good content.

You can specify unlimited keywords—separate them with commas or newlines. Examples: 'spam, advertisement, promotion, click here, limited offer' (comma-separated) or list each on a new line. The tool processes all keywords efficiently even with 100+ entries. For large keyword lists (e.g., comprehensive profanity filters), upload them from a file. Each keyword is checked against every sentence. Performance remains fast even with hundreds of keywords and thousands of sentences due to optimized client-side processing.

Yes, it uses substring matching. The tool checks if keywords appear anywhere in the sentence, including as parts of words. Examples: Keyword: 'spam'. Matches: 'spam', 'spammy', 'antispam', 'spammer'. Sentence 'This is spammy content' → REMOVED (contains 'spam'). To match only whole words, add spaces around keywords: ' spam ' (with leading/trailing spaces). Or use regex-capable tools. Substring matching is powerful for catching variations but can cause false positives—always review the removed sentences preview to verify accuracy.

100% private. All sentence filtering happens entirely in your browser using JavaScript. Your text never leaves your device, isn't uploaded to servers, isn't logged, and isn't stored anywhere. Even file uploads are processed locally—no network transmission. Check your browser's Network tab to verify zero data sent. Essential for processing confidential documents like legal briefs (redacting client names), HR files (removing salary info), medical records (filtering sensitive data), proprietary reports, or any content requiring complete privacy and security before sharing.