input: Write a function to create a natural language processing application in Python that extracts the top 10 most frequent words from a given text. Use the `Counter` class from the `collections` module to find the most frequent words. If the input text is empty, the function should return an empty list. 
  
  def extract_top_words(text):
      from collections import Counter
      if not text:
          return []
      words = text.split()
      counter = Counter(words)
      top_words = counter.most_common(10)
      return top_words
  
  assert extract_top_words("Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.") == [('dolor', 1), ('Lorem', 1), ('ipsum', 1), ('amet', 1), ('consectetur', 1), ('adipiscing', 1), ('elit,', 1), ('sed', 1), ('do', 1), ('eiusmod', 1)]
  assert extract_top_words("") == []
  assert extract_top_words("apple banana apple cherry banana cherry apple") == [('apple', 3), ('banana', 2), ('cherry', 2)]
  assert extract_top_words("word word word word word") == [('word', 5)]
output: def extract_top_words(text):
      from collections import Counter
      if not text:
          return []
      words = text.split()
      counter = Counter(words)
      top_words = counter.most_common(10)
      return top_words