code: def process_line(
      semiotic_class: str, line: str
  ) -> Optional[Tuple[str, str, str, int]]:
      """A helper function to read the file with alignment results"""
  
      parts = line.strip().split("\t")
      if len(parts) != 6:
          return None
      freq = int(parts[0])
      if parts[1] != "good:":
          return None
  
      src, dst, leftside_align, rightside_align = (
          parts[2],
          parts[3],
          parts[4],
          parts[5],
      )
      align = rightside_align
      if semiotic_class == "letters" or semiotic_class == "plain":
          align = leftside_align
  
      return src, dst, align, freq
  
file_path: NeMo/examples/nlp/text_normalization_as_tagging/dataset_preparation/prepare_corpora_after_alignment.py
imports: import glob
  import os
  from argparse import ArgumentParser
  from collections import Counter
  from typing import Dict, Optional, TextIO, Tuple
  from nemo.collections.nlp.data.text_normalization_as_tagging.utils import get_src_and_dst_for_alignment
  from nemo.utils import logging
label_desc: Use image node_id 2 for calling a global function with example usage: process_line(semiotic_class, line) and returns: src,  dst,  align,  freq, None, None