class_docstr: Give a sentiment intensity score to sentences.
class_docstr_tok: ["Give","a","sentiment","intensity","score","to","sentences","."]
code: def _least_check(self, valence, words_and_emoticons, i):
      # check for negation case using "least"
      if (
          i > 1
          and words_and_emoticons[i - 1].lower() not in self.lexicon
          and words_and_emoticons[i - 1].lower() == "least"
      ):
          if (
              words_and_emoticons[i - 2].lower() != "at"
              and words_and_emoticons[i - 2].lower() != "very"
          ):
              valence = valence * N_SCALAR
      elif (
          i > 0
          and words_and_emoticons[i - 1].lower() not in self.lexicon
          and words_and_emoticons[i - 1].lower() == "least"
      ):
          valence = valence * N_SCALAR
      return valence
  
imports: import os
  import re
  import math
  import string
  import codecs
  import json
  from itertools import product
  from inspect import getsourcefile
  from io import open
label_desc: Use image node_id 6 for calling the SentimentIntensityAnalyzer obj's underlying member method code with example usage: obj._least_check(valence, words_and_emoticons, i) and returns: valence