code: def load_pos(num_sents):
      from nltk.corpus import brown
  
      sentences = brown.tagged_sents(categories="news")[:num_sents]
  
      tag_re = re.compile(r"[*]|--|[^+*-]+")
      tag_set = set()
      symbols = set()
  
      cleaned_sentences = []
      for sentence in sentences:
          for i in range(len(sentence)):
              word, tag = sentence[i]
              word = word.lower()  # normalize
              symbols.add(word)  # log this word
              # Clean up the tag.
              tag = tag_re.match(tag).group()
              tag_set.add(tag)
              sentence[i] = (word, tag)  # store cleaned-up tagged token
          cleaned_sentences += [sentence]
  
      return cleaned_sentences, list(tag_set), list(symbols)
  
imports: import itertools
  import re
  from nltk.metrics import accuracy
  from nltk.probability import ConditionalFreqDist, ConditionalProbDist, DictionaryConditionalProbDist, DictionaryProbDist, FreqDist, LidstoneProbDist, MLEProbDist, MutableProbDist, RandomProbDist
  from nltk.tag.api import TaggerI
  from nltk.util import LazyMap, unique_list
label_desc: Use image node_id 8 for calling a global function with example usage: load_pos(num_sents) and returns: cleaned_sentences,  list,  list