Text Tools

Extract Mentions Examples

Review practical Extract Mentions examples so you can understand expected input, output, and common patterns faster.

Why examples matter for Extract Mentions

Use this extract mentions tool to pull @mention values from chats, drafts, social content, and copied text into a clean result list.

Example pages are especially useful for text tools because they show what good input looks like, what kind of output to expect, and how the tool behaves in common scenarios.

Extract Mentions examples

Chat text

Input

Thanks @alex and @maria for the update

Output

@alex
@maria

The tool finds all mention-style matches and lists them one per line.

Repeated mentions

Input

@john please review with @john and @anna

Output

@john
@john
@anna

Repeated mentions stay in the result in the same order.

How to use these examples

Paste or type text into the input box.
Run the tool to extract @mentions.
Review the output list.
Copy the extracted values if needed.

Compare your own input with the Extract Mentions examples below before running the tool.
Keep the input format as close as possible to the example pattern when you test a new case.
If your output looks wrong, check spacing, separators, symbols, or the exact value type first.

Common mistakes in sample input

Expecting plain names without @ to be extracted.

Fix: This tool only extracts words that start with @.

Expecting duplicates to be removed.

Fix: The tool returns matches as found. Deduplicate the result afterward if needed.

Using spaces inside mention names.

Fix: Mention extraction works on continuous mention-style tokens.

Next steps

After reviewing these examples, run the live tool with your own input. If your task involves a follow-up step, the related page can help you move to the next tool in the workflow.

Run the main tool

Open the main Extract Mentions page and test your own real input.

Open Extract Mentions