input: Write a function that creates a natural language processing application in Python to extract the top 10 most frequent words from a given text. The function should take a string as input and return a list of tuples where each tuple contains a word and its frequency. If the text is empty, the function should return an empty list.
  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("The quick brown fox jumps over the lazy dog. The quick brown fox jumps over the lazy dog.")==[('The', 2), ('quick', 2), ('brown', 2), ('fox', 2), ('jumps', 2), ('over', 2), ('the', 2), ('lazy', 2), ('dog.', 2)]
output: def extract_top_words(text):
      if not text:
          return []
      words = text.split()
      freq = {}
      for word in words:
          if word in freq:
              freq[word] += 1
          else:
              freq[word] = 1
      sorted_words = sorted(freq.items(), key=lambda x: x[1], reverse=True)
      return sorted_words[:10]