NLTK: The Natural Language Toolkit
Edward Loper, Steven Bird
TL;DR
NLTK presents a Python-based open-source toolkit designed to streamline practical NLP education by providing modular, well-documented components, GUI visualization, and a suite of tutorials and problem sets. The authors justify Python for its ease of use, rapid prototyping, readability, and GUI support, and define design criteria emphasizing usability, consistency, extensibility, documentation, simplicity, and modularity. They outline a modular architecture with core data structures, parsing, tagging, FSA, visualization, and classification components, complemented by extensive tutorials, reference docs, and technical reports to support assignments and class demonstrations. The approach aims to reduce integration overhead and enable hands-on NLP learning across courses, from basic experiments to implementing new modules.
Abstract
NLTK, the Natural Language Toolkit, is a suite of open source program modules, tutorials and problem sets, providing ready-to-use computational linguistics courseware. NLTK covers symbolic and statistical natural language processing, and is interfaced to annotated corpora. Students augment and replace existing components, learn structured programming by example, and manipulate sophisticated models from the outset.