Named Entity Recognition (NER) using NLP

This project focuses on Named Entity Recognition (NER), an NLP technique used to identify and classify named entities (like people, organizations, locations, etc.) in text data. This system leverages machine learning models to extract and categorize entities from various text sources.

Features

• Extracts and classifies named entities such as people, organizations, and locations from text.
• Supports multiple entity types and customizable categories.
• Integrates with various NLP libraries and frameworks.
• User-friendly interface to visualize extracted entities and their classifications.

Installation

To set up this project on your local machine, follow these steps:

1. Clone the Repository

   git clone https://github.com/username/ner-project.git
   cd ner-project

2. Set Up Virtual Environment (Optional but Recommended)

   python3 -m venv venv
   source venv/bin/activate   # On Windows: venv\Scripts\activate

3. Install Required Packages

   pip install -r requirements.txt

Usage

To run the NER system and extract entities from your text data, use the following command:

python ner_extraction.py