code: def tag_verb_chains(self):
          
          if not self.is_tagged(CLAUSES):
              self.tag_clauses()
          if self.__verbchain_detector is None:
              self.__verbchain_detector = load_default_verbchain_detector()
          sentences = self.divide()
          verbchains = []
          for sentence in sentences:
              chains = self.__verbchain_detector.detectVerbChainsFromSent( sentence )
              for chain in chains:
                  # 1) Get spans for all words of the phrase
                  word_spans = [ ( sentence[idx][START], sentence[idx][END] ) \
                                   for idx in sorted( chain[PHRASE] ) ]
                  # 2) Assign to the chain
                  chain[START] = [ span[0] for span in word_spans ]
                  chain[END]   = [ span[1] for span in word_spans ]
              verbchains.extend(chains)
          self[VERB_CHAINS] = verbchains
          return self
docs: Create ``verb_chains`` layer.
             Depends on ``clauses`` layer.