input: Write a function to extract all the verbs from a given sentence. The function should tokenize the sentence, tag each token with its part of speech, and then extract and return only the verbs.
  import nltk
  
  def extract_verbs(sentence):
      tokens = nltk.word_tokenize(sentence)
      tags = nltk.pos_tag(tokens)
      verbs = [word for word, pos in tags if pos.startswith('V')]
      return verbs
  
  sentence = "The cat jumped over the moon."
  verbs = extract_verbs(sentence)
  assert verbs == ['jumped']
  
  sentence = "She ate the pizza quickly."
  verbs = extract_verbs(sentence)
  assert verbs == ['ate', 'quickly']
  
  sentence = "Running and swimming are great exercises."
  verbs = extract_verbs(sentence)
  assert verbs == ['Running', 'swimming', 'are']
  
  sentence = "This is a simple sentence."
  verbs = extract_verbs(sentence)
  assert verbs == []
  
  sentence = "I will read the book tomorrow."
  verbs = extract_verbs(sentence)
  assert verbs == ['will', 'read', 'tomorrow']
output: import nltk
  
  def extract_verbs(sentence):
      tokens = nltk.word_tokenize(sentence)
      tags = nltk.pos_tag(tokens)
      verbs = [word for word, pos in tags if pos.startswith('V')]
      return verbs