code: def convert_dataset(
      base_input_path,
      base_output_path,
      short_name,
      download_method=DownloadMethod.DOWNLOAD_RESOURCES,
  ):
      nlp_hy = stanza.Pipeline(
          lang="hy",
          processors="tokenize",
          download_method=download_method,
      )
      paragraphs = read_data(
          os.path.join(base_input_path, "ArmNER-HY.json1")
      )
      tagged_sentences = format_sentences(paragraphs, nlp_hy)
      beios_sentences = convert_to_bioes(tagged_sentences)
      train_test_dev_split(
          beios_sentences, base_output_path, short_name
      )
  
file_path: stanza/stanza/utils/datasets/ner/convert_hy_armtdp.py
imports: import argparse
  import os
  import json
  import re
  import stanza
  import random
  from tqdm import tqdm
  from stanza import DownloadMethod, Pipeline
  import stanza.utils.default_paths
label_desc: Use image node_id 8 for calling a global function with example usage: convert_dataset(base_input_path, base_output_path, short_name, download_method) without return types