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This Jupyter notebook is an interactive tool for processing natural language text. It segments text into sentences, performs word tokenization, counts word frequencies, timestamps each entry, and saves the results in JSON format. Ideal for NLP studies and text analysis

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Interactive Text Processing Notebook

Overview

This Jupyter notebook is an interactive tool for natural language processing. It enables users to input text, segment it into sentences, tokenize these sentences into words, count word frequencies, timestamp the processing, and save the results for further analysis. ui

Features

  • Sentence Segmentation: Decomposes text into its constituent sentences.
  • Word Tokenization: Segments sentences into individual words while filtering out punctuation.
  • Word Frequency Count: Tallies the number of occurrences for each word within the input text.
  • Timestamping: Attaches a timestamp to each processed block of text, marking when it was analyzed.
  • Data Persistence: Saves the processed data in JSON format to a designated folder for persistent storage.
  • Interactive UI: Provides a user-friendly interface for easy text input and immediate display of processed data.

Running the Notebook Execute the cells in the notebook from top to bottom. Input your text into the text area widget and press the "Process Text" button to see the output displayed below.

Built With NLTK - The Natural Language Toolkit for Python ipywidgets - Interactive HTML widgets for Jupyter notebooks

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This Jupyter notebook is an interactive tool for processing natural language text. It segments text into sentences, performs word tokenization, counts word frequencies, timestamps each entry, and saves the results in JSON format. Ideal for NLP studies and text analysis

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