class_docstr: Interface to the CoreNLP Parser.
docstr: Parse multiple sentences.
  
  Takes multiple sentences as a list of strings. Each sentence will be
  automatically tokenized and tagged.
  
  :param sentences: Input sentences to parse.
  :type sentences: list(str)
  :rtype: iter(iter(Tree))
docstr_tok: ["Parse","multiple","sentences",".","Takes","multiple","sentences","as","a","list","of","strings",".","Each","sentence","will","be","automatically","tokenized","and","tagged",".",":","param","sentences",":","Input","sentences","to","parse",".",":","type","sentences",":","list","(","str",")",":","rtype",":","iter","(","iter","(","Tree",")",")"]
code: def raw_parse_sents(
      self, sentences, verbose=False, properties=None, *args, **kwargs
  ):
      """Parse multiple sentences.
  
      Takes multiple sentences as a list of strings. Each sentence will be
      automatically tokenized and tagged.
  
      :param sentences: Input sentences to parse.
      :type sentences: list(str)
      :rtype: iter(iter(Tree))
  
      """
      default_properties = {
          # Only splits on '\n', never inside the sentence.
          "ssplit.eolonly": "true"
      }
  
      default_properties.update(properties or {})
  
      """
          for sentence in sentences:
              parsed_data = self.api_call(sentence, properties=default_properties)
  
              assert len(parsed_data['sentences']) == 1
  
              for parse in parsed_data['sentences']:
                  tree = self.make_tree(parse)
                  yield iter([tree])
          """
      parsed_data = self.api_call(
          "\n".join(sentences), properties=default_properties
      )
      for parsed_sent in parsed_data["sentences"]:
          tree = self.make_tree(parsed_sent)
          yield iter([tree])
  
imports: import json
  import os
  import re
  import socket
  import time
  from typing import List, Tuple
  from nltk.internals import _java_options, config_java, find_jar_iter, java
  from nltk.parse.api import ParserI
  from nltk.parse.dependencygraph import DependencyGraph
  from nltk.tag.api import TaggerI
  from nltk.tokenize.api import TokenizerI
  from nltk.tree import Tree
label_desc: Use image node_id 5 for calling the GenericCoreNLPParser obj's underlying member method code with example usage: obj.raw_parse_sents(sentences, verbose, properties) without return types