class_docstr: Main class for sentiment inference execution.
  
  Attributes:
      opinion_lex: Opinion lexicon as outputted by TrainSentiment module.
      aspect_lex: Aspect lexicon as outputted by TrainSentiment module.
      intensifier_lex (dict): Pre-defined intensifier lexicon.
      negation_lex (dict): Pre-defined negation lexicon.
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docstr: Modify multiple-word aspect tkn length and start index.
  
  Args:
      index_range: The index range of the multi-word aspect.
  Returns:
      The modified aspect token.
docstr_tok: ["Modify","multiple-word","aspect","tkn","length","and","start","index",".","Args",":","index_range",":","The","index","range","of","the","multi-word","aspect",".","Returns",":","The","modified","aspect","token","."]
code: def _modify_for_multiple_word(cur_tkn, parsed_sentence, index_range):
      """Modify multiple-word aspect tkn length and start index.
  
      Args:
          index_range: The index range of the multi-word aspect.
      Returns:
          The modified aspect token.
      """
      if len(index_range) >= 2:
          cur_tkn["start"] = parsed_sentence[index_range[0]]["start"]
          cur_tkn["len"] = len(parsed_sentence[index_range[0]]["text"])
          for i in index_range[1:]:
              cur_tkn["len"] = (
                  int(cur_tkn["len"])
                  + len(parsed_sentence[i]["text"])
                  + 1
              )
      return cur_tkn
  
imports: import math
  from os import PathLike
  from pathlib import Path, PosixPath
  from typing import Union
  from nlp_architect.common.core_nlp_doc import CoreNLPDoc
  from nlp_architect.models.absa import INFERENCE_OUT
  from nlp_architect.models.absa.inference.data_types import Term, TermType, Polarity, SentimentDoc, SentimentSentence, LexiconElement
  from nlp_architect.models.absa.utils import _read_lexicon_from_csv, load_opinion_lex, _load_aspect_lexicon, parse_docs, parse_docs_bist, _load_parsed_docs_from_dir
  from tqdm import tqdm
label_desc: Use image node_id 8 for calling the SentimentInference obj's underlying member method code with example usage: obj._modify_for_multiple_word(cur_tkn, parsed_sentence, index_range) and returns: cur_tkn