The paradigm of Graph Rewriting is used very little in the field of Natural Language Processing. But graphs are a natural way of representing the deep syntax and the semantics of natural languages. Deep syntax is an abstraction of syntactic dependencies towards semantics in the form of graphs and there is a compact way of representing the semantics in an underspecified logical framework also with graphs. Then, Graph Rewriting reconciles efficiency with linguistic readability for producing representations at some linguistic level by transformation of a neighbor level: from raw text to surface syntax, from surface syntax to deep syntax, from deep syntax to underspecified logical semantics and conversely.
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Application of Graph Rewriting to Natural Language Processing
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eBook - ePub
Application of Graph Rewriting to Natural Language Processing
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1
Programming with Graphs
In this chapter, we shall discuss elements of programming for graphs. Our work is based on PYTHON, a language widely used for natural language processing, as in the case of the NLTK library1 (Natural Language ToolKit), used in our work. However, the elements presented here can easily be translated into another language. Several different data structures may be used to manage graphs. We chose to use dictionaries; this structure is elementary (i.e. unencapsulated), reasonably efficient and extensible. For what follows, we recommend opening an interactive PYTHON session2.
Notes for advanced programmers: by choosing such a primitive structure, we do not have the option to use sophisticated error management mechanisms. There is no domain (or type) verification, no identifier verification, etc. Generally speaking, we shall restrict ourselves to the bare minimum in this area for reasons of time and space. Furthermore, we have chosen not to use encapsulation so that the structure remains as transparent as possible. Defining a class for graphs should make it easier to implement major projects. Readers are encouraged to take a more rigorous approach to that presented here after reading the book. Finally, note that the algorithms used here are not always optimal; once again, our primary aim is to improve readability.
Notes for “beginner” programmers: this book is not intended as an introduction to PYTHON, and we presume that readers have some knowledge of the language, specifi...
Table of contents
- Cover
- Table of Contents
- Introduction
- 1 Programming with Graphs
- 2 Dependency Syntax: Surface Structure and Deep Structure
- 3 Graph Rewriting and Transformation of Syntactic Annotations in a Corpus
- 4 From Logic to Graphs for Semantic Representation
- 5 Application of Graph Rewriting to Semantic Annotation in a Corpus
- 6 Parsing Using Graph Rewriting
- 7 Graphs, Patterns and Rewriting
- 8 Analysis of Graph Rewriting
- Appendix
- Bibliography
- Index
- End User License Agreement
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Yes, you can access Application of Graph Rewriting to Natural Language Processing by Guillaume Bonfante,Bruno Guillaume,Guy Perrier in PDF and/or ePUB format, as well as other popular books in Languages & Linguistics & Linguistics. We have over 1.5 million books available in our catalogue for you to explore.