class_docstr: Reader for simple part-of-speech tagged corpora.  Paragraphs are
  assumed to be split using blank lines.  Sentences and words can be
  tokenized using the default tokenizers, or by custom tokenizers
  specified as parameters to the constructor.  Words are parsed
  using ``nltk.tag.str2tuple``.  By default, ``'/'`` is used as the
  separator.  I.e., words should have the form::
  
     word1/tag1 word2/tag2 word3/tag3 ...
  
  But custom separators may be specified as parameters to the
  constructor.  Part of speech tags are case-normalized to upper
  case.
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docstr: :return: the given file(s) as a list of
      sentences or utterances, each encoded as a list of word
      strings.
  :rtype: list(list(str))
docstr_tok: [":","return",":","the","given","file","(","s",")","as","a","list","of","sentences","or","utterances",",","each","encoded","as","a","list","of","word","strings",".",":","rtype",":","list","(","list","(","str",")",")"]
code: def sents(self, fileids=None):
      """
      :return: the given file(s) as a list of
          sentences or utterances, each encoded as a list of word
          strings.
      :rtype: list(list(str))
      """
      return concat(
          [
              TaggedCorpusView(
                  fileid,
                  enc,
                  False,
                  True,
                  False,
                  self._sep,
                  self._word_tokenizer,
                  self._sent_tokenizer,
                  self._para_block_reader,
                  None,
              )
              for (fileid, enc) in self.abspaths(fileids, True)
          ]
      )
  
imports: import os
  from nltk.corpus.reader.api import *
  from nltk.corpus.reader.timit import read_timit_block
  from nltk.corpus.reader.util import *
  from nltk.tag import map_tag, str2tuple
  from nltk.tokenize import *
label_desc: Use image node_id 3 for calling the TaggedCorpusReader obj's underlying member method code with example usage: obj.sents(fileids) and returns: concat