code: def convert_lst20(paths, short_name, include_space_char=True):
      assert short_name == "th_lst20"
      SHARDS = ("train", "eval", "test")
      BASE_OUTPUT_PATH = paths["NER_DATA_DIR"]
  
      input_split = [
          (os.path.join(paths["NERBASE"], "thai", "LST20_Corpus", x), x)
          for x in SHARDS
      ]
  
      if not include_space_char:
          short_name = short_name + "_no_ws"
  
      for input_folder, split_type in input_split:
          text_list = [
              text
              for text in os.listdir(input_folder)
              if text[0] == "T"
          ]
  
          if split_type == "eval":
              split_type = "dev"
  
          output_path = os.path.join(
              BASE_OUTPUT_PATH, "%s.%s.bio" % (short_name, split_type)
          )
          print(output_path)
  
          with open(output_path, "w", encoding="utf-8") as fout:
              for text in text_list:
                  lst = []
                  with open(
                      os.path.join(input_folder, text),
                      "r",
                      encoding="utf-8",
                  ) as fin:
                      lines = fin.readlines()
  
                  for line_idx, line in enumerate(lines):
                      x = line.strip().split("\t")
                      if len(x) > 1:
                          if x[0] == "_" and not include_space_char:
                              continue
                          else:
                              word, tag = x[0], x[2]
  
                              if tag == "MEA_BI":
                                  tag = "B_MEA"
                              if tag == "OBRN_B":
                                  tag = "B_BRN"
                              if tag == "ORG_I":
                                  tag = "I_ORG"
                              if tag == "PER_I":
                                  tag = "I_PER"
                              if tag == "LOC_I":
                                  tag = "I_LOC"
                              if tag == "B" and line_idx + 1 < len(
                                  lines
                              ):
                                  x_next = (
                                      lines[line_idx + 1]
                                      .strip()
                                      .split("\t")
                                  )
                                  if len(x_next) > 1:
                                      tag_next = x_next[2]
                                      if (
                                          "I_" in tag_next
                                          or "E_" in tag_next
                                      ):
                                          tag = tag + tag_next[1:]
                                      else:
                                          tag = "O"
                                  else:
                                      tag = "O"
                              if "_" in tag:
                                  tag = tag.replace("_", "-")
                              if (
                                  "ABB" in tag
                                  or tag == "DDEM"
                                  or tag == "I"
                                  or tag == "__"
                              ):
                                  tag = "O"
  
                              fout.write("{}\t{}".format(word, tag))
                              fout.write("\n")
                      else:
                          fout.write("\n")
      convert_bio_to_json(
          BASE_OUTPUT_PATH, BASE_OUTPUT_PATH, short_name
      )
  
label_desc: Use image node_id 1 for calling a global function with example usage: convert_lst20(paths, short_name, include_space_char) without return types