input: Write a python function to identify adjectives in a text and replace them with a phrase using a word from a predefined list.
  assert replace_adjectives("This painting is an amazing representation of the beauty of nature.") == ["amazing, Explore the Wonder of Nature"]
  assert replace_adjectives("The quick brown fox jumps over the lazy dog.") == ["quick, Witness the Wonder of Nature", "lazy, Captivate the Wonder of Nature"]
  assert replace_adjectives("She has a beautiful and charming smile.") == ["beautiful, Embrace the Wonder of Nature", "charming, Discover the Wonder of Nature"]
output: import nltk
  from nltk.corpus import wordnet
  from nltk.tokenize import word_tokenize, sent_tokenize
  from nltk.tag import pos_tag
  
  nltk.download('averaged_perceptron_tagger')
  nltk.download('punkt')
  nltk.download('wordnet')
  
  predefined_phrases = [
      "Explore the Wonder of Nature",
      "Witness the Wonder of Nature",
      "Captivate the Wonder of Nature",
      "Embrace the Wonder of Nature",
      "Discover the Wonder of Nature"
  ]
  
  def get_synonyms(word):
      synonyms = set()
      for syn in wordnet.synsets(word):
          for lemma in syn.lemmas():
              synonyms.add(lemma.name())
      return synonyms
  
  def replace_adjectives(text):
      words = word_tokenize(text)
      pos_tags = pos_tag(words)
      adjectives = [word for word, pos in pos_tags if pos == 'JJ']
  
      results = []
      for i, adj in enumerate(adjectives):
          if adj in get_synonyms(adj):
              phrase = predefined_phrases[i % len(predefined_phrases)]
              results.append(f"{adj}, {phrase}")
      
      return results