code: def generate_examples(
      lang_id,
      list_of_files,
      splits=(0.8, 0.1, 0.1),
      min_window=10,
      max_window=50,
      eval_length=10,
      data_format="ud",
  ):
      """
      Generate train/dev/test examples for a given language
      """
      examples = []
      for ud_file in list_of_files:
          sentences = sentences_from_file(
              ud_file, data_format=data_format
          )
          for sentence in sentences:
              sentence = clean_sentence(sentence)
              if validate_sentence(sentence, min_window):
                  examples += sentence_to_windows(
                      sentence,
                      min_window=min_window,
                      max_window=max_window,
                  )
      shuffle(examples)
      train_idx = int(splits[0] * len(examples))
      train_set = [
          example_json(lang_id, example)
          for example in examples[:train_idx]
      ]
      dev_idx = int(splits[1] * len(examples)) + train_idx
      dev_set = [
          example_json(lang_id, example, eval_length=eval_length)
          for example in examples[train_idx:dev_idx]
      ]
      test_set = [
          example_json(lang_id, example, eval_length=eval_length)
          for example in examples[dev_idx:]
      ]
      return train_set, dev_set, test_set
  
imports: import argparse
  import json
  import logging
  import os
  import re
  import sys
  from pathlib import Path
  from random import randint, random, shuffle
  from string import digits
  from tqdm import tqdm
  from stanza.models.common.constant import treebank_to_langid
label_desc: Use image node_id 5 for calling a global function with example usage: generate_examples(lang_id, list_of_files, splits, min_window, max_window, eval_length, data_format) and returns: train_set,  dev_set,  test_set