NLP Explorer

🧑‍💻 Overview

NLP Explorer is a web-based application built with Streamlit that allows users to explore various Natural Language Processing (NLP) techniques. It provides an intuitive interface to perform multiple NLP tasks, including:

• Tokenization: Splits text into individual words or sentences.
• POS Tagging: Assigns part-of-speech labels to words in a sentence.
• Stemming: Reduces words to their root form.
• Lemmatization: Converts words to their base form using contextual analysis.
• Named Entity Recognition (NER): Identifies and categorizes named entities in the text.

The application aims to provide a hands-on experience with NLP and can be used to better understand the key concepts in text processing and analysis.

🚀 Features

• Interactive Web Interface: Built using Streamlit for easy interaction and text processing.
• Multiple NLP Tasks: Users can choose from Tokenization, POS Tagging, Stemming, Lemmatization, and NER.
• Real-time Results: See the results of each NLP technique immediately after applying it to your text.
• Preprocessing: Text is preprocessed before analysis to remove irrelevant characters like URLs, emails, etc.

📌 Installation

1. Clone the repository

Start by cloning the repository to your local machine:

git clone https://github.com/arya-io/nlp-explorer.git

2. Install dependencies

Install the required Python packages:

pip install -r requirements.txt

requirements.txt includes the necessary dependencies such as:

• streamlit
• nltk

3. Download NLTK Data

The project uses the nltk library, which requires additional data downloads. You can download the necessary datasets by running:

python -c "import nltk; nltk.download('punkt'); nltk.download('wordnet'); nltk.download('omw-1.4'); nltk.download('averaged_perceptron_tagger'); nltk.download('maxent_ne_chunker'); nltk.download('words'); nltk.download('stopwords')"

🚀 Usage

1. Run the Streamlit app

After installing the dependencies and downloading the NLTK data, you can start the Streamlit app by running the following command:

streamlit run app.py

This will open a new tab in your default web browser with the NLP Explorer interface.

2. Using the App

• Input Text: Type or paste any text into the text input box.
• Choose NLP Tasks: Check the boxes for the NLP tasks you want to apply (Tokenization, POS Tagging, Stemming, Lemmatization, NER).
• Analyze: Click the "Analyze Text" button to see the results of the selected NLP techniques.
• View Results: Results for each NLP task will be displayed below the input text area.

🧑‍🤝‍🧑 Contributing

We welcome contributions to the NLP Explorer project! Here’s how you can help:

Fork the repository and clone it to your local machine. Create a new branch for your changes. Make your changes to the code. Commit your changes with clear messages. Push your changes to your forked repository. Create a pull request to the main repository. Please make sure your code follows Python’s PEP 8 style guidelines and includes comments where necessary. Additionally, add tests for any new functionality.

🛠️ Built With

• Streamlit: Framework for building interactive web apps.
• NLTK: Natural Language Toolkit for performing various NLP tasks.
• Python: Programming language used for the development of the app.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.