code: def get_classification_result(
      hyp_file, ref_file, hyp_write, ref_write
  ):
      hyp_lines = [line for line in hyp_file]
      ref_lines = [line for line in ref_file]
  
      error = 0
      for line_count in range(len(hyp_lines)):
          hyp_intent = (
              hyp_lines[line_count].split("\t")[0].split(" ")[0]
          )
          ref_intent = (
              ref_lines[line_count].split("\t")[0].split(" ")[0]
          )
          if hyp_intent != ref_intent:
              error += 1
          hyp_write.write(
              " ".join(
                  hyp_lines[line_count].split("\t")[0].split(" ")[1:]
              )
              + "\t"
              + hyp_lines[line_count].split("\t")[1]
          )
          ref_write.write(
              " ".join(
                  ref_lines[line_count].split("\t")[0].split(" ")[1:]
              )
              + "\t"
              + ref_lines[line_count].split("\t")[1]
          )
      return 1 - (error / len(hyp_lines))
  
imports: import argparse
  import os
  import re
  import sys
  import pandas
label_desc: Use image node_id 1 for calling a global function with example usage: get_classification_result(hyp_file, ref_file, hyp_write, ref_write) and returns: unknown