code: def reprocess_lines(processed_lines):
      """
      Reprocesses lines using pythainlp to cut up sentences into shorter sentences.
  
      Many of the lines in BEST seem to be multiple Thai sentences concatenated, according to native Thai speakers.
  
      Input: a list of lines, where each line is a list of words.  Space characters can be included as words
      Output: a new list of lines, resplit using pythainlp
      """
      reprocessed_lines = []
      for line in processed_lines:
          text = "".join(line)
          try:
              chunks = sent_tokenize(text)
          except NameError as e:
              raise NameError(
                  "Sentences cannot be reprocessed without first installing pythainlp"
              ) from e
          # Check that the total text back is the same as the text in
          if sum(len(x) for x in chunks) != len(text):
              raise ValueError(
                  "Got unexpected text length: \n{}\nvs\n{}".format(
                      text, chunks
                  )
              )
  
          chunk_lengths = [len(x) for x in chunks]
  
          current_length = 0
          new_line = []
          for word in line:
              if len(word) + current_length < chunk_lengths[0]:
                  new_line.append(word)
                  current_length = current_length + len(word)
              elif len(word) + current_length == chunk_lengths[0]:
                  new_line.append(word)
                  reprocessed_lines.append(new_line)
                  new_line = []
                  chunk_lengths = chunk_lengths[1:]
                  current_length = 0
              else:
                  remaining_len = chunk_lengths[0] - current_length
                  new_line.append(word[:remaining_len])
                  reprocessed_lines.append(new_line)
                  word = word[remaining_len:]
                  chunk_lengths = chunk_lengths[1:]
                  while len(word) > chunk_lengths[0]:
                      new_line = [word[: chunk_lengths[0]]]
                      reprocessed_lines.append(new_line)
                      word = word[chunk_lengths[0] :]
                      chunk_lengths = chunk_lengths[1:]
                  new_line = [word]
                  current_length = len(word)
          reprocessed_lines.append(new_line)
      return reprocessed_lines
  
imports: import os
  import random
label_desc: Use image node_id 4 for calling a global function with example usage: reprocess_lines(processed_lines) and returns: reprocessed_lines