pySBD
Sentence detector
A Python package for out-of-the-box sentence boundary detection using rule-based algorithms.
🐍💯pySBD (Python Sentence Boundary Disambiguation) is a rule-based sentence boundary detection that works out-of-the-box.
821 stars
12 watching
85 forks
Language: Python
last commit: 6 months ago pythonrule-basedsegmentationsentencesentence-boundary-detectionsentence-tokenizer
Related projects:
Repository | Description | Stars |
---|---|---|
| A tool for automatically detecting sentence boundaries in natural language text using machine learning and handcrafted features. | 90 |
| A C# implementation of sentence boundary detection with rule-based approach. | 33 |
| A rule-based sentence boundary detection gem that works across many languages | 559 |
| A Ruby port of the NLTK algorithm to detect sentence boundaries in unstructured text | 92 |
| Tools for detecting the language of unstructured text in Elixir applications | 116 |
| A system designed to identify the language of an arbitrary text string using machine learning and multiple data sources. | 2 |
| Automatically detects obfuscated code and other complex code constructs in binaries to aid reverse engineering. | 580 |
| An end-to-end outlier detection system that integrates machine learning algorithms with database support | 252 |
| An object detection system using a novel receptive field block module to enhance feature discriminability and robustness. | 1,416 |
| A Python package implementing an interpretable machine learning model for text classification with visualization tools | 336 |
| A plugin for Sublime Text that detects and applies syntax to unknown file types in specific project contexts. | 343 |
| Recurrent neural network designed to detect code blocks in text. | 12 |
| Provides an implementation of a neural network for detecting lines in images and videos | 156 |
| A tool that analyzes Python projects to detect their application features through static analysis | 7 |
| An executable detection tool using PE parsing and machine learning signatures to identify packed samples. | 30 |