text-classification-GUI

This Python project provides a graphical user interface (GUI) for annotating research paper sentences based on multiple sentiment layers. It allows the user to classify sentences from a text document into categories like sentiment polarity, section aspects, subjective polarity, and major comments.

Features

• Sentence Tokenization: The program tokenizes the input text into sentences for classification.
• Four Sentiment Layers:
  1. Sentiment Layer: Classifies sentences as Positive, Introspective, Summary, or Yes.
  2. Section Aspect: Identifies the section of the research paper (e.g., Introduction, Related Work, Experiments, etc.).
  3. Subjective Polarity: Classifies sentences into Summary, Suggestion, Deficit, Appreciation, Discussion, or Question.
  4. Major Comment: Allows users to mark comments as Major or Not.
• User Interface: A GUI built with wxPython for intuitive sentence classification.
• Annotations: After classification, the sentences are annotated with the user's choices and saved into a new text file.

Requirements

• Python 3.x
• wxPython (for GUI)
• nltk (for text tokenization)