Testing ../../nltk/test/wordnet.doctest...

  [Line 7] from nltk.corpus import wordnet
  [Line 11] from nltk.corpus import wordnet as wn
  [Line 20] wn.synsets('dog') # doctest: +ELLIPSIS +NORMALIZE_WHITESPACE
  [Line 23] wn.synsets('dog', pos=wn.VERB)
  [Line 29] wn.synset('dog.n.01')
  [Line 31] wn.synset('dog.n.01').definition
  [Line 33] wn.synset('dog.n.01').examples
  [Line 35] wn.synset('dog.n.01').lemmas
  [Line 37] [lemma.name for lemma in wn.synset('dog.n.01').lemmas]
  [Line 39] wn.lemma('dog.n.01.dog').synset
  [Line 49] dog = wn.synset('dog.n.01')
  [Line 50] dog.hypernyms()
  [Line 52] dog.hyponyms() # doctest: +ELLIPSIS
  [Line 54] dog.member_holonyms()
  [Line 56] dog.root_hypernyms()
  [Line 64] good = wn.synset('good.a.01')
  [Line 65] good.antonyms()
  [Line 69] good.lemmas[0].antonyms()
  [Line 80] eat = wn.lemma('eat.v.03.eat')
  [Line 81] eat
  [Line 83] eat.key
  [Line 85] eat.count()
  [Line 87] wn.lemma_from_key(eat.key)
  [Line 89] wn.lemma_from_key(eat.key).synset
  [Line 91] wn.lemma_from_key('feebleminded%5:00:00:retarded:00')
  [Line 93] for lemma in wn.synset('eat.v.03').lemmas:
  [Line 98] for lemma in wn.lemmas('eat', 'v'):
  [Line 110] vocal = wn.lemma('vocal.a.01.vocal')
  [Line 111] vocal.derivationally_related_forms()
  [Line 113] vocal.pertainyms()
  [Line 115] vocal.antonyms()
  [Line 124] wn.synset('think.v.01').frame_ids
  [Line 126] for lemma in wn.synset('think.v.01').lemmas:
  [Line 138] wn.synset('stretch.v.02').frame_ids
  [Line 140] for lemma in wn.synset('stretch.v.02').lemmas:
  [Line 154] dog = wn.synset('dog.n.01')
  [Line 155] cat = wn.synset('cat.n.01')
  [Line 165] dog.path_similarity(cat)
  [Line 176] dog.lch_similarity(cat)
  [Line 195] dog.wup_similarity(cat)
  [Line 202] from nltk.corpus import wordnet_ic
  [Line 203] brown_ic = wordnet_ic.ic('ic-brown.dat')
  [Line 204] semcor_ic = wordnet_ic.ic('ic-semcor.dat')
  [Line 209] from nltk.corpus import genesis
  [Line 210] genesis_ic = wn.ic(genesis, False, 0.0)
  [Line 221] dog.res_similarity(cat, brown_ic)
  [Line 223] dog.res_similarity(cat, genesis_ic)
  [Line 233] dog.jcn_similarity(cat, brown_ic)
  [Line 235] dog.jcn_similarity(cat, genesis_ic)
  [Line 245] dog.lin_similarity(cat, semcor_ic)
  [Line 255] for synset in list(wn.all_synsets('n'))[:10]:
  [Line 271] wn.synsets('dog') # doctest: +ELLIPSIS
  [Line 273] wn.synsets('dog', pos='v')
  [Line 278] from itertools import islice
  [Line 279] for synset in islice(wn.all_synsets('n'), 5):
  [Line 295] wn.morphy('denied', wn.NOUN)
  [Line 296] wn.morphy('denied', wn.VERB)
  [Line 298] wn.synsets('denied', wn.NOUN)
  [Line 300] wn.synsets('denied', wn.VERB) # doctest: +NORMALIZE_WHITE...
  [Line 311] wn.synsets('book', wn.NOUN)
  [Line 313] wn.synsets('book', wn.ADJ)
  [Line 315] wn.morphy('book', wn.NOUN)
  [Line 317] wn.morphy('book', wn.ADJ)
  [Line 321] t = wn.synsets('titan')[1]
  [Line 322] m = wn.synsets('male')[1]
  [Line 323] t.wup_similarity(m)
  [Line 326] t = wn.synsets('titan')[1]
  [Line 327] s = wn.synsets('say', wn.VERB)[0]
  [Line 328] t.wup_similarity(s)
  [Line 333] a = wn.synsets("writings")[0]
  [Line 334] b = wn.synsets("scripture")[0]
  [Line 335] brown_ic = wordnet_ic.ic('ic-brown.dat')
  [Line 336] wn.jcn_similarity(a, b, brown_ic)
  [Line 341] from nltk.corpus.reader.wordnet import information_content
  [Line 342] s = wn.synsets('say', wn.VERB)[0]
  [Line 343] information_content(s, brown_ic)
  [Line 348] k = wn.synsets("jefferson")[0].lemmas[0].key
  [Line 349] wn.lemma_from_key(k)
  [Line 351] wn.lemma_from_key(k.upper())
  [Line 356] from nltk.corpus import wordnet as wn
  [Line 357] for s in wn.all_synsets(wn.NOUN):
  [Line 365] tow = wn.synset('tow.v.01')
  [Line 366] shlep = wn.synset('shlep.v.02')
  [Line 367] from nltk.corpus import wordnet_ic
  [Line 368] brown_ic =  wordnet_ic.ic('ic-brown.dat')
  [Line 369] wn.jcn_similarity(tow,shlep, brown_ic)  All examples passed

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