Week 5

Learning Objectives

• Concepts: lexical resources Swadesh lists pronouncing dictionaries wordnets

(color key: Python/Programming NLP/CL Software Engineering)

Reading

• NLTK 2.4 – Lexical Resources
• NLTK 2.5 – WordNet (How To)

Additional Links

• Peter Norvig’s Spelling Corrector – demonstrates something cool you can do with just a little bit of Python
• ARPABET – the phonemic transcription system used by the CMU Pronouncing Dictionary
• WordNet
  • Documentation of relations: https://globalwordnet.github.io/gwadoc
  • Browse the modern English WordNet: https://en-word.net/
  • The Open Multilingual Wordnet: http://compling.hss.ntu.edu.sg/omw/

Lecture

Review/walkthrough of Homework 4

In-class review of programming concepts

Testing Your Knowledge

• Use the nltk.corpus.words wordlist to estimate the following for several text corpora:

  • what percentage of the text’s vocabularly are not in the wordlist?
  • what percentage of the wordlist are present in the text?

• Use the ARPABET transcriptions in the nltk.corpus.cmudict corpus to devise a function for identifying rhyming words (how they are identified is up to you). What are the largest clusters of rhyming words?

• Use nltk.corpus.wordnet to explore word relations.

  • What are the hyponyms of student?
  • Use the lowest_common_hypernyms() method on synsets to find what is the shared hypernym of student and professor. How about professor and lecturer?