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
  where each sentence is a list of (word, tag) tuples.
  The sentences must have already been tokenized and tagged.
  
  :param sentences: Input sentences to parse
  :type sentences: list(list(tuple(str, str)))
  :rtype: iter(iter(Tree))
docstr_tok: ["Use","StanfordParser","to","parse","multiple","sentences",".","Takes","multiple","sentences","where","each","sentence","is","a","list","of","(","word",",","tag",")","tuples",".","The","sentences","must","have","already","been","tokenized","and","tagged",".",":","param","sentences",":","Input","sentences","to","parse",":","type","sentences",":","list","(","list","(","tuple","(","str",",","str",")",")",")",":","rtype",":","iter","(","iter","(","Tree",")",")"]
code: def tagged_parse_sents(self, sentences, verbose=False):
      """
      Use StanfordParser to parse multiple sentences. Takes multiple sentences
      where each sentence is a list of (word, tag) tuples.
      The sentences must have already been tokenized and tagged.
  
      :param sentences: Input sentences to parse
      :type sentences: list(list(tuple(str, str)))
      :rtype: iter(iter(Tree))
      """
      tag_separator = "/"
      cmd = [
          self._MAIN_CLASS,
          "-model",
          self.model_path,
          "-sentences",
          "newline",
          "-outputFormat",
          self._OUTPUT_FORMAT,
          "-tokenized",
          "-tagSeparator",
          tag_separator,
          "-tokenizerFactory",
          "edu.stanford.nlp.process.WhitespaceTokenizer",
          "-tokenizerMethod",
          "newCoreLabelTokenizerFactory",
      ]
      # We don't need to escape slashes as "splitting is done on the last instance of the character in the token"
      return self._parse_trees_output(
          self._execute(
              cmd,
              "\n".join(
                  " ".join(
                      tag_separator.join(tagged) for tagged in 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 7 for calling the GenericStanfordParser obj's underlying member method code with example usage: obj.tagged_parse_sents(sentences, verbose) and returns: self