Named Entity Recognizer
This project is designed to help user extract and categorize named entities from text using state-of-the-art NLP models like dslim/bert-base-NER and Spacy's en_core_web_sm model.
Named Entity Recognition (NER) is a key task in natural language processing that involves identifying and classifying key information (entities) in text into predefined categories. This can include names of people, organizations, locations, expressions of times, quantities, monetary values, percentages, etc.
The web application of this project is built with Streamlit to provide an interactive web interface for performing NER on user-input text.