docstr: 比较用户词典给出的词和原分词结果，根据打分决定是否替换
docstr_tok: ["\u6bd4\u8f83\u7528\u6237\u8bcd\u5178\u7ed9\u51fa\u7684\u8bcd\u548c\u539f\u5206\u8bcd\u7ed3\u679c\uff0c\u6839\u636e\u6253\u5206\u51b3\u5b9a\u662f\u5426\u66ff\u6362"]
code: def get_new_phrase_list(self, match_info, bound, query):
      """
      比较用户词典给出的词和原分词结果，根据打分决定是否替换
      """
      new_phrase_list = []
      phrase_left = query.ori_query_str[
          bound.left_char_bound : bound.start_index
      ]
      phrase_right = query.ori_query_str[
          bound.end_index + 1 : bound.right_char_bound + 1
      ]
      if phrase_left != "":
          phrase_left += (
              "/" + query.lac_query_list[bound.left_bound].split("/")[1]
          )
          new_phrase_list.append(phrase_left)
      new_phrase_list.append(match_info[1][0] + "/" + match_info[1][1])
      if phrase_right != "":
          phrase_right += (
              "/"
              + query.lac_query_list[bound.right_bound].split("/")[1]
          )
          new_phrase_list.append(phrase_right)
  
      new_query_list = (
          query.lac_query_list[0 : bound.left_bound]
          + new_phrase_list
          + query.lac_query_list[bound.right_bound + 1 :]
      )
      new_lm_score = self.calc_lm_score(new_query_list)
      return new_lm_score, new_phrase_list
  
imports: import io
  import numpy
  import six
label_desc: Use image node_id 6 for calling the Interventer obj's underlying member method code with example usage: obj.get_new_phrase_list(match_info, bound, query) and returns: new_lm_score,  new_phrase_list