code: def sentences(self):
          
          for sentid, ys in enumerate(self.yield_sentences()):
              sent, context_sent, context_doc, inst2ans, textid = ys
              instances = {}
              for instance in sent.findAll('instance'):
                  instid = instance['id']
                  lemma = instance['lemma']
                  word = instance.text
                  instances[instid] = Instance(instid, lemma, word)
  
              tokens = []
              for i in sent: # Iterates through BeautifulSoup object.
                  if str(i).startswith('<instance'): # BeautifulSoup.Tag
                      instid = sent.find('instance')['id']
                      inst = instances[instid]
                      answer = inst2ans[instid]
                      term = Term(instid, answer.pos, inst.lemma, answer.sensekey,
                                  type='open')
                      tokens.append(Word(instid, inst.word,
                                         sentid, textid, term))
                  else: # if BeautifulSoup.NavigableString
                      tokens+=[Word(None, w, sentid, textid, None)
                               for w in i.split()]
              yield tokens
docs: Returns the instances by sentences, and yields a list of tokens,
          similar to the pywsd.semcor.sentences.
  
          >>> coarse_wsd = SemEval2007_Coarse_WSD()
          >>> for sent in coarse_wsd.sentences():
          >>>     for token in sent:
          >>>         print token
          >>>         break
          >>>     break
          word(id=None, text=u'Your', offset=None, sentid=0, paraid=u'd001', term=None)