Named Entity Recognition (NER) GUI

This project is a simple desktop application built with Tkinter and Hugging Face Transformers.
It provides a graphical interface for running Named Entity Recognition (NER) on text input using a pretrained BERT model.

Features

• Desktop GUI built with Tkinter
• Uses the dslim/bert-base-NER model from Hugging Face
• Groups entities into meaningful tokens
• Shows detected entities with labels and confidence scores
• Scrollable input and output boxes for longer text

Requirements

• Python 3.8 or newer
• Tkinter (included with most Python installations)
• Hugging Face Transformers
• PyTorch (recommended)

Install dependencies:

pip install transformers torch

Usage

Clone the repository and run the script:

git clone https://github.com/your-username/ner-tkinter-gui.git
cd ner-tkinter-gui
python ner_gui.py

Steps:

1. Enter or paste text into the input box.
2. Click Run NER.
3. View extracted entities in the output box.

Example

Input:

Barack Obama was born in Hawaii and served as President of the United States.

Output:

Barack Obama → PER (0.99)
Hawaii → LOC (0.99)
United States → LOC (0.99)
President → MISC (0.85)

Project Structure

ner-tkinter-gui/
│
├── NER_prompt.py       # Main application script
└── README.md        # Project documentation

License

This project is licensed under the MIT License.