input: Write a python function to find all coreferences that have not been resolved and their antecedents, and overwrite the doc's coref attribute with the newly created clusters using Spacy.
  assert find_coreferences("John went to the store. He bought an apple.")== [('John', 'He'), ('the store', 'He')]
  assert find_coreferences("Alice loves programming. She writes code every day.")== [('Alice', 'She')]
  assert find_coreferences("Bob and Tom are friends. They play football together.")== [('Bob and Tom', 'They')]
output: import spacy
  from spacy.tokens import Span
  
  def find_coreferences(text):
      nlp = spacy.load("en_core_web_sm")
      doc = nlp(text)
      
      corefs = []
      for cluster in doc._.coref_clusters:
          main_mention = cluster.main.text
          for mention in cluster.mentions:
              if mention != cluster.main:
                  corefs.append((main_mention, mention.text))
                  
      return corefs