An interactive Natural Language Processing (NLP) web application that demonstrates Tokenization, Stemming, and Lemmatization using NLTK with a Gradio interface.
Designed as an educational NLP playground to visualize core text-processing techniques used in real-world AI pipelines.
K. Siddhartha — AI / NLP Developer
🔗 GitHub: https://github.com/k-siddhartha-ai 🤗 Hugging Face: https://huggingface.co/Siddhartha001
This project allows users to enter text and observe classical NLP preprocessing steps in real time.
The application performs:
- Word Tokenization
- Sentence Tokenization
- Porter Stemming
- WordNet Lemmatization
The goal is to provide a clear and interactive understanding of fundamental NLP operations before advanced transformer-based models.
Frontend: Gradio Blocks Interface NLP Engine: NLTK Library Processing Flow:
User Input → Tokenization → Stemming → Lemmatization → Structured Output Tables
- 🔹 Word Tokenization (NLTK)
- 🔹 Sentence Tokenization
- 🌱 Porter Stemmer Visualization
- 📚 WordNet Lemmatization
- 📊 Structured JSON and DataFrame Outputs
- 🖥️ Interactive Gradio Interface
- Python
- NLTK
- Gradio
pip install -r requirements.txt
python app.py
https://huggingface.co/spaces/Siddhartha001/nlp-text-processing-gradio
- Non-alphabetic tokens are filtered during stemming and lemmatization.
- Designed as an educational NLP visualization tool.
- Demonstrates classical NLP preprocessing before deep learning pipelines.
- Lightweight CPU-friendly NLP operations
- Fast response time due to rule-based processing
- No GPU required
Educational NLP project by K. Siddhartha.