This text entity extractor is simple yet powerful. Here's a comprehensive guide to get you started:
Paste Your Text: Copy and paste the text you want to analyze into the input box. The tool handles any length, from a few lines to tens of thousands of words. Character and line count statistics appear below the input area.
Select Entity Types: Check the entity types you want to extract from the options below the input. By default, URLs, emails, phone numbers, IPv4 addresses, ID numbers, and dates are selected. You can also enable IPv6 addresses or bank card numbers. Use "Select All" or "Deselect All" for quick toggling.
Run Extraction: Click the "Extract All" button to scan the text and identify matching entities. Results appear in categorized tabs, each showing the extracted items and their count. Click any tab to switch between entity types.
Export Results: After extraction, click "Copy Current" to copy the active tab's results to clipboard. You can also export as a plain text file or JSON for further processing, integration with databases, or batch operations.
The text entity extractor serves professionals across many fields. Here are typical real-world scenarios:
Data Cleaning & Lead Generation: Quickly extract structured contact information from raw text sources like customer reviews, survey responses, or forum posts. Instead of manually copying emails and phone numbers one by one, this tool extracts thousands in seconds, ready for CRM import or outreach campaigns.
Log Analysis & Security Auditing: Security analysts often need to extract IP addresses and URLs from server logs or network traffic dumps. This tool instantly pulls all IPs and links, enabling rapid source analysis, blacklist compilation, or threat hunting. IPv4 and IPv6 are both supported.
Legal & Compliance Document Processing: Paralegals and compliance officers extract ID numbers and dates from contracts, court filings, or investigation reports. The tool handles both 18-digit and 15-digit Chinese ID formats, making historical document digitization straightforward.
Social Media & Content Management: Community managers extract URLs and contact details from comments, DMs, or group messages for competitor analysis, user research, or information archiving. JSON export makes it easy to feed results into databases or analytics pipelines.
How Regex Matching Works: At its core, this tool uses regular expressions—pattern-matching syntax that describes specific text structures. For example, the email pattern [a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,} matches nearly all standard email formats by requiring a username, @ symbol, domain, and TLD.
Named Entity Recognition (NER): In natural language processing, NER is a key task that identifies and classifies named entities in text into predefined categories. Modern NER systems use deep learning models like BERT. This tool takes a rule-based regex approach, trading some flexibility for speed, accuracy, and offline capability—no model download or API call required.
Privacy & Security: Because all processing happens in your browser, no data is transmitted to any server. This is critical when working with sensitive documents containing personal information, financial data, or proprietary content. We recommend closing the browser tab after processing highly sensitive text to clear any residual data from memory.
The tool supports 8 entity types: URLs (HTTP/HTTPS/FTP), email addresses, Chinese mainland mobile numbers (11 digits), IPv4 addresses, IPv6 addresses, Chinese mainland ID numbers (18 or 15 digits), dates (YYYY-MM-DD, DD/MM/YYYY and more), and bank card numbers (16-19 digits).
No. All extraction runs entirely in your browser using JavaScript regular expressions. Your text data never leaves your device, ensuring complete privacy and security.
Yes. The tool uses optimized regex matching and can process tens of thousands of words. For extremely large texts (over 100,000 characters), consider processing in chunks for best performance.
Yes. You can copy results to clipboard with one click, or export them as a plain text file or JSON format for further data processing and analysis.
The tool recognizes standard 11-digit Chinese mainland mobile numbers (starting with 1, second digit 3-9), with automatic deduplication. It handles continuous text and numbers with separators like 138-0013-8000.
Yes. The tool recognizes both 18-digit standard ID numbers (with X/x checksum) and 15-digit legacy IDs, labeling each type automatically.