class_docstr: Interface to the Stanford Parser
class_docstr_tok: ["Interface","to","the","Stanford","Parser"]
docstr: Use StanfordParser to parse multiple sentences. Takes multiple sentences as a
  list where each sentence is a list of words.
  Each sentence will be automatically tagged with this StanfordParser instance's
  tagger.
  If whitespaces exists inside a token, then the token will be treated as
  separate tokens.
  
  :param sentences: Input sentences to parse
  :type sentences: list(list(str))
  :rtype: iter(iter(Tree))
docstr_tok: ["Use","StanfordParser","to","parse","multiple","sentences",".","Takes","multiple","sentences","as","a","list","where","each","sentence","is","a","list","of","words",".","Each","sentence","will","be","automatically","tagged","with","this","StanfordParser","instance's","tagger",".","If","whitespaces","exists","inside","a","token",",","then","the","token","will","be","treated","as","separate","tokens",".",":","param","sentences",":","Input","sentences","to","parse",":","type","sentences",":","list","(","list","(","str",")",")",":","rtype",":","iter","(","iter","(","Tree",")",")"]
code: def parse_sents(self, sentences, verbose=False):
      """
      Use StanfordParser to parse multiple sentences. Takes multiple sentences as a
      list where each sentence is a list of words.
      Each sentence will be automatically tagged with this StanfordParser instance's
      tagger.
      If whitespaces exists inside a token, then the token will be treated as
      separate tokens.
  
      :param sentences: Input sentences to parse
      :type sentences: list(list(str))
      :rtype: iter(iter(Tree))
      """
      cmd = [
          self._MAIN_CLASS,
          "-model",
          self.model_path,
          "-sentences",
          "newline",
          "-outputFormat",
          self._OUTPUT_FORMAT,
          "-tokenized",
          "-escaper",
          "edu.stanford.nlp.process.PTBEscapingProcessor",
      ]
      return self._parse_trees_output(
          self._execute(
              cmd,
              "\n".join(" ".join(sentence) for sentence in sentences),
              verbose,
          )
      )
  
imports: import os
  import tempfile
  import warnings
  from subprocess import PIPE
  from nltk.internals import _java_options, config_java, find_jar_iter, find_jars_within_path, java
  from nltk.parse.api import ParserI
  from nltk.parse.dependencygraph import DependencyGraph
  from nltk.tree import Tree
label_desc: Use image node_id 3 for calling the GenericStanfordParser obj's underlying member method code with example usage: obj.parse_sents(sentences, verbose) and returns: self