https://github.com/vasanthakumar70/test-annotator
NER labeling tool for text annotations.
https://github.com/vasanthakumar70/test-annotator
Last synced: 10 days ago
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NER labeling tool for text annotations.
- Host: GitHub
- URL: https://github.com/vasanthakumar70/test-annotator
- Owner: vasanthakumar70
- Created: 2026-04-25T16:06:12.000Z (2 months ago)
- Default Branch: main
- Last Pushed: 2026-04-25T16:49:57.000Z (2 months ago)
- Last Synced: 2026-04-25T18:28:18.983Z (2 months ago)
- Language: JavaScript
- Homepage: https://vasanthakumar70.github.io/test-annotator/
- Size: 550 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# TextAnnotator
A clean, professional NER (Named Entity Recognition) annotation tool for text labeling. Built with React.
## What is TextAnnotator?
TextAnnotator is a web-based tool for creating training data for NLP models. Select text in a passage and label it with entity tags like PERSON, ORG, or GPE to create annotated datasets that can be used to train NER models.
## Features
- **Text Input** - Paste or type any passage text
- **Entity Labels** - Create custom labels (PERSON, ORG, GPE, etc.)
- **Visual Annotation** - See highlighted entities in the text
- **JSON Export** - Download annotations as JSON for training data
- **Keyboard Shortcuts** - Press 1, 2, 3... to quickly apply labels
- **Professional UI** - Clean interface designed for productivity
## Getting Started
### Prerequisites
- Node.js 18+
- npm or yarn
### Installation
```bash
# Clone the repository
git clone https://github.com/your-username/textannotator.git
cd textannotator
# Install dependencies
npm install
```
### Development
```bash
# Start development server
npm run dev
# Or use the start script
npm start
```
The app will open at http://localhost:3001
### Production Build
```bash
npm run build
```
Builds the app for production to the `build` folder.
## How to Use
1. **Enter text** in the Passage Input box
2. **Select text** with your mouse/cursor
3. **Click a label** (or press 1, 2, 3) to annotate
4. **Download** the JSON output for training
### JSON Output Format
```json
{
"examples": [
{
"id": "ex-1",
"content": "John works at Google in New York.",
"annotations": [
{ "start": 0, "end": 4, "tag_name": "PERSON" },
{ "start": 14, "end": 20, "tag_name": "ORG" },
{ "start": 24, "end": 32, "tag_name": "GPE" }
]
}
]
}
```
- `start` / `end` - Character positions in the text
- `tag_name` - The entity label applied