Rule-Based NLP with NLP++
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ISBN: 9789365891980
eISBN: 9789365890082
Authors: David de Hilster, Amnon Meyers
Rights: Worldwide
Edition: 2026
Pages: 396
Dimension: 7.5*9.25 Inches
Book Type: Paperback
- Description
- Table of Contents
- About the Authors
Rule-Based NLP with NLP++ is a comprehensive guide to building accurate, transparent, and maintainable text analysis systems using NLP++, the only programming language created specifically for natural language processing. Authored by the creators of NLP++ and the VisualText IDE, this book guides readers through the full spectrum of rule-based NLP development, from foundational concepts to production-grade analyzers.
The book introduces the NLP++ pipeline architecture and its uniform, glass-box approach to text analysis, in contrast to opaque statistical and ML methods. Using the VisualText IDE, readers will learn to design and build multi-pass text analyzers, write grammar rules and functions, and manage hierarchical knowledge bases. Practical chapters explore example analyzers for date-time recognition, formatted text analysis, and named entity extraction with coreference resolution. An advanced English language analyzer is also documented in detail. Integration chapters cover calling NLP++ analyzers from Python, TypeScript, C++, and the HPCC Systems supercomputing platform.
Whether you are a computational linguist, software engineer, or student of NLP, this book equips you with the tools and thinking needed to build explainable, customizable, and high-performing text analysis systems that emulate human language processing.
WHAT YOU WILL LEARN
● Design multi-pass NLP++ analyzers using VisualText IDE.
● Learn to write rules and manage the parse tree and knowledge base.
● Solve real-world challenges like NER and coreference.
● Integrate analyzers into Python, C++, and HPCC Systems.
● Compare NLP++ to statistical, mission-critical AI methods.
WHO THIS BOOK IS FOR
This book is for software engineers, computational linguists, NLP researchers, and students who want to build accurate and explainable text analysis systems. Readers should have basic programming experience, ideally in Python, Typescript, or C++. No prior NLP knowledge is required.
1. Introduction to NLP++
2. NLP++ Architecture and Language
3. NLP++ Topics
4. VisualText
5. NLP++ Philosophy and Libraries
6. Developing Text Analyzers
7. Example Analyzers
8. Integrating NLP++ Analyzers
Appendix A: Resources
Appendix B: NLP++
Appendix C: Miscellaneous Topics
Appendix D: Full English Parser Reference
● David de Hilster is an adjunct professor at Northeastern University College of Engineering and co-creator of NLP++ and VisualText. He holds a bachelor’s in mathematics and a master's in linguistics from Ohio State University, has four decades of experience in NLP, and is the founder of the Natural Language Understanding Global Initiative.
● Amnon Meyers holds a master’s in computer science and a master’s in organic chemistry from UC Berkeley and a bachelor’s in biology from MIT. He spent a decade in aerospace NLP R&D at McDonnell Douglas AI Lab and TRW Space Park, as well as five years at UC Irvine AI Lab, working on DARPA and Navy projects. He is the co-creator of NLP++ and the creator of the conceptual grammar knowledge base system.