text: Title: A question about document tokenization
  Body: Hi, I found a very interesting result to tokenize a document. The example code is:
  
  ```
  import spacy
  
  nlp = spacy.load("en_core_web_sm")
  # doc = nlp("Apple is looking at. startup for $1 billion.")
  # for token in doc:
  #     print(token.text, token.pos_, token.dep_)
  # Example text
  text = '''Panel C: Gene Associations in LUAD and NATs
  
  In LUAD tumors, ZNF71 is associated with JUN, SAMHD1, RNASEL, IFNGR1, IKKB, and EIF2A.
  In non-cancerous adjacent tissues (NATs), the associated genes are OAS1, MP3K7, and IFNAR2.'''
  
  # Process the text
  doc = nlp(text)
  out_sen = []
  # Iterate over the sentences
  for sent in doc.sents:
      if len(sent) != 0:
          print(sent.text)
          out_sen.append(sent)
  ```
  
  The result out_sen's length is 1, and it is treated as a whole sentence. Is this a bug or sth by default? Thanks.
  
  The spacy version is 3.7.6