By the end of this unit you should:
Read about WordNet and lexical semantic databases.
WordNet is a large lexical database of English words organized into synonym sets (synsets) that are connected by semantic relationships. Developed at Princeton University, it groups words into sets of synonyms and maps relationships between concepts like hypernymy (is-a), meronymy (part-of), and antonymy (opposite-of).
Key WordNet concepts:
Explore WordNet relationships using the interactive tool.
Enter any word to discover its semantic relationships and navigate through the lexical network.
Watch how to use WordNet programmatically with Python.
This video (10 minutes) demonstrates accessing WordNet through NLTK, exploring synsets, calculating semantic similarity, and implementing lexical analysis applications.
Calculate semantic similarity between words using WordNet metrics.
This tool computes similarity scores between word pairs using path-based distance measures in the WordNet hierarchy.
Build an interactive tool for finding word relationships.
This application helps identify synonyms, antonyms, and related words using WordNet's lexical network.
Watch how to visualize and navigate semantic networks.
This video (8 minutes) shows how to create visual representations of WordNet relationships and build interactive semantic network explorers.
Create a comprehensive lexical analysis application.
Combine WordNet features to build a complete lexical analysis tool that can process text and identify semantic relationships.
Test your understanding of WordNet and lexical semantics:
1. What is a synset in WordNet?
2. What is the relationship between "animal" and "dog"?
3. Which measures semantic similarity in WordNet?