Modeling Language

Summary

This chapter covers how to model language and text in graphs. We explore word-level modeling with WordNet, NLP techniques for entity extraction, document modeling at sentence, paragraph, and document levels, and linguistic relationships like synonyms and antonyms.

Concepts Covered

Language in Graphs
Words in Graphs
WordNet
NLP Basics
Entity Extraction
Sentence Modeling
Paragraph Modeling
Document Modeling
Document Pipelines
Synonyms
Synonym Rings
Antonyms

Learning Objectives

By the end of this chapter, students will be able to:

Model words and their relationships using graph structures
Apply NLP techniques to extract entities from text
Design document models at multiple granularity levels
Build document processing pipelines with graph outputs
Implement synonym rings and antonym relationships
Connect WordNet concepts to domain-specific models