code: def read_sequential_tagging_file(
      file_path, ignore_line_patterns=None
  ):
      """
      Read a tab separated sequential tagging file.
      Returns a list of list of tuple of tags (sentences, words)
  
      Args:
          file_path (str): input file path
          ignore_line_patterns (list, optional): list of string patterns to ignore
  
      Returns:
          list of list of tuples
      """
      if ignore_line_patterns:
          assert isinstance(
              ignore_line_patterns, list
          ), "ignore_line_patterns must be a list"
  
      def _split_into_sentences(file_lines):
          sentences = []
          s = []
          for line in file_lines:
              if len(line) == 0:
                  sentences.append(s)
                  s = []
                  continue
              s.append(line)
          if len(s) > 0:
              sentences.append(s)
          return sentences
  
      with open(file_path, encoding="utf-8") as fp:
          data = fp.readlines()
          data = [d.strip() for d in data]
          if ignore_line_patterns:
              for s in ignore_line_patterns:
                  data = [d for d in data if s not in d]
          data = [tuple(d.split()) for d in data]
      return _split_into_sentences(data)
  
imports: import re
  import string
  import sys
  from os import path
  from typing import List, Tuple
  import spacy
  from nltk import WordNetLemmatizer
  from nltk.stem.snowball import EnglishStemmer
  from spacy.cli.download import download
  from spacy.lang.en import LEMMA_EXC, LEMMA_INDEX, LEMMA_RULES
  from spacy.lemmatizer import Lemmatizer
  from nlp_architect.utils.generic import license_prompt
  from joblib import Parallel, delayed
  from functools import partial
  from spacy.util import minibatch
  from nlp_architect.common.core_nlp_doc import CoreNLPDoc
  from pathlib import Path
label_desc: Use image node_id 6 for calling a global function with example usage: read_sequential_tagging_file(file_path, ignore_line_patterns) and returns: _split_into_sentences, sentences