Natural Language Processing: Python and NLTK

Disambiguating senses using Wordnet

Disambiguation is the task of distinguishing two or more of the same spellings or the same sounding words on the basis of their sense or meaning.

Following are the implementations of disambiguation or the WSD task using Python technologies:

• Lesk algorithms:
  • Original Lesk
  • Cosine Lesk (use cosines to calculate overlaps instead of using raw counts)
  • Simple Lesk (with definitions, example(s), and hyper+hyponyms)
  • Adapted/extended Lesk
  • Enhanced Lesk
• Maximizing similarity:
  • Information content
  • Path similarity
• Supervised WSD:
  • It Makes Sense (IMS)
  • SVM WSD
• Vector Space models:
  • Topic Models, LDA
  • LSI/LSA
  • NMF
• Graph-based models:
  • Babelfly
  • UKB
• Baselines:
  • Random sense
  • Highest lemma counts
  • First NLTK sense

Wordnet sense similarity in NLTK involves the ...