docs: def convert_trees(self, ptb_trees, representation='basic', universal=True,
                        include_punct=True, include_erased=False, **kwargs):
          """Convert a list of Penn Treebank formatted strings (ptb_trees)
          into Stanford Dependencies. The dependencies are represented
          as a list of sentences (CoNLL.Corpus), where each sentence
          (CoNLL.Sentence) is itself a list of CoNLL.Token objects.
  
          Currently supported representations are 'basic', 'collapsed',
          'CCprocessed', and 'collapsedTree' which behave the same as they
          in the CoreNLP command line tools. (note that in the online
          CoreNLP demo, 'collapsed' is called 'enhanced')
  
          Additional arguments: universal (if True, use universal
          dependencies if they're available), include_punct (if False,
          punctuation tokens will not be included), and include_erased
          (if False and your representation might erase tokens, those
          tokens will be omitted from the output).
  
          See documentation on your backend to see if it supports
          further options."""
          kwargs.update(representation=representation, universal=universal,
                        include_punct=include_punct,
                        include_erased=include_erased)
          return Corpus(self.convert_tree(ptb_tree, **kwargs)
                        for ptb_tree in ptb_trees)