class_docstr: Language dependent tokenizer of text document.
class_docstr_tok: ["Language","dependent","tokenizer","of","text","document","."]
code: def to_sentences(self, paragraph):
      if hasattr(self._sentence_tokenizer, "_params"):
          extra_abbreviations = self.LANGUAGE_EXTRA_ABREVS.get(
              self._language, []
          )
          self._sentence_tokenizer._params.abbrev_types.update(
              extra_abbreviations
          )
      sentences = self._sentence_tokenizer.tokenize(
          to_unicode(paragraph)
      )
      return tuple(map(unicode.strip, sentences))
  
imports: from __future__ import absolute_import
  from __future__ import division, print_function, unicode_literals
  import re
  import string
  import zipfile
  import nltk
  from .._compat import to_string, to_unicode, unicode
  from ..utils import normalize_language
label_desc: Use image node_id 5 for calling the Tokenizer obj's underlying member method code with example usage: obj.to_sentences(paragraph) and returns: tuple