Package nltk_lite :: Package wordnet
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Package wordnet

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Wordnet interface, based on Oliver Steele's Pywordnet, together
with an implementation of Ted Pedersen's Wordnet::Similarity package.

Usage
-----

    >>> from nltk_lite.wordnet import *

Retrieve words from the database

    >>> N['dog']
    dog(n.)
    >>> V['dog']
    dog(v.)
    >>> ADJ['clear']
    clear(adj.)
    >>> ADV['clearly']
    clearly(adv.)

Examine a word's senses and pointers:

    >>> N['dog'].getSenses()
    ('dog' in {noun: dog, domestic dog, Canis familiaris}, 'dog' in {noun: frump, dog}, 'dog' in {noun: dog}, 'dog' in {noun: cad, bounder, blackguard, dog, hound, heel}, 'dog' in {noun: frank, frankfurter, hotdog, hot dog, dog, wiener, wienerwurst, weenie}, 'dog' in {noun: pawl, detent, click, dog}, 'dog' in {noun: andiron, firedog, dog, dog-iron})

Extract the first sense:

    >>> N['dog'][0] # aka N['dog'].getSenses()[0]
    'dog' in {noun: dog, domestic dog, Canis familiaris}

Get the first five pointers (relationships) from dog to other synsets:

    >>> N['dog'][0].getPointers()[:5]
    (hypernym -> {noun: canine, canid}, member meronym -> {noun: Canis, genus Canis}, member meronym -> {noun: pack}, hyponym -> {noun: pooch, doggie, doggy, barker, bow-wow}, hyponym -> {noun: cur, mongrel, mutt})

Get those synsets of which 'dog' is a member meronym:

    >>> N['dog'][0].getPointerTargets(MEMBER_MERONYM)
    [{noun: Canis, genus Canis}, {noun: pack}]

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