# nupunkt Overview

nupunkt is a Python library for sentence boundary detection based on the Punkt algorithm. It's designed to be lightweight, fast, and accurate, with a focus on handling the complexities of real-world text.

## What is Punkt?

The Punkt algorithm, originally developed by Tibor Kiss and Jan Strunk, is an unsupervised approach to sentence boundary detection. It uses statistical methods to learn which periods indicate sentence boundaries versus those that are part of abbreviations, ellipses, or other non-terminal uses.

## Key Features

- **Zero runtime dependencies**: nupunkt is designed to work with minimal dependencies
- **Pre-trained models**: Comes with a default model ready for use
- **Customizable**: Can be trained on domain-specific text
- **Ellipsis handling**: Special handling for various ellipsis patterns
- **Performance optimized**: Efficient implementation for processing large text volumes
- **Fully typed**: Complete type annotations for better IDE integration

## How It Works

nupunkt's approach to sentence boundary detection involves:

1. **Tokenization**: Breaking text into tokens
2. **Abbreviation detection**: Identifying abbreviations that end with periods
3. **Collocation identification**: Finding word pairs that tend to occur together across sentence boundaries
4. **Sentence starter recognition**: Learning which words typically start sentences
5. **Orthographic context analysis**: Using capitalization patterns to identify sentence boundaries

The algorithm works in multiple passes to annotate tokens with sentence breaks, abbreviations, and other features, ultimately producing accurate sentence boundaries even in challenging text.

## When to Use nupunkt

nupunkt is particularly useful for:

- Natural language processing pipelines
- Text preprocessing for machine learning
- Extracting sentences from large text corpora
- Legal and scientific text processing where abbreviations are common
- Any application requiring accurate sentence boundary detection

## Comparison with Other Tools

Unlike many other tokenizers, nupunkt:

- Doesn't rely on hand-crafted rules or large language models
- Can adapt to domain-specific abbreviations and patterns through training
- Handles ellipses and other complex punctuation patterns
- Has minimal dependencies while maintaining high accuracy