Sentence Classification Portfolio Project

Overview

This repository demonstrates practical Natural Language Processing (NLP) sentence classification tasks commonly performed in AI data annotation, machine learning, and large language model (LLM) training.

The project showcases my ability to analyze written text, understand context, and assign accurate labels based on predefined classification guidelines.

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Skills Demonstrated

• Sentence Classification
• Sentiment Analysis
• Topic Classification
• Intent Classification
• Data Annotation
• Label Consistency
• NLP Quality Evaluation
• Context Understanding
• AI Training Data Preparation

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Project Structure

Sentence-Classification/
│
├── README.md
├── label-guide.md
├── LICENSE
│
├── examples/
│   ├── sentiment-analysis.md
│   ├── topic-classification.md
│   └── intent-classification.md
│
├── assets/
└── portfolio-images/

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Classification Tasks

1. Sentiment Analysis

Determine whether a sentence expresses:

• Positive
• Neutral
• Negative

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2. Topic Classification

Categorize text into subjects such as:

• Technology
• Finance
• Healthcare
• Sports
• Education
• Entertainment

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3. Intent Classification

Identify the purpose of a sentence, including:

• Refund Request
• Order Tracking
• Technical Support
• Cancellation
• General Inquiry

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Quality Principles

Each annotation follows:

• Consistency
• Accuracy
• Context awareness
• Objective labeling
• Clear reasoning

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Applications

These skills are commonly used in:

• AI Model Training
• Large Language Models (LLMs)
• Search Relevance
• Customer Support AI
• Conversational AI
• Chatbots
• Recommendation Systems

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Author

Paz Ikang

AI / NLP Portfolio

GitHub: https://github.com/zinnie1

Portfolio: https://zinnie1.github.io/ai-nlp-portfolio-v2/

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This repository is part of my growing AI and Natural Language Processing portfolio.