code: def split_dep_parse(text, *args, **kwargs):
      doc = nlp(text)
      chunks = []
      chunk = ""
      for token in doc:
          # append the token to the current chunk
          chunk += token.text_with_ws
  
          # decide whether to chunk at this token
          if token.pos_ in ["PUNCT", "CCONJ", "SCONJ"]:
              if token.pos_ == "PUNCT" and len(chunk.split()) == 1:
                  continue
              if chunk.strip():
                  chunks.append(chunk.strip())
                  chunk = ""
          elif token.dep_ == "ROOT":
              if chunk.strip():
                  chunks.append(chunk.strip())
                  chunk = ""
  
      # handle the last chunk
      if chunk.strip():
          chunks.append(chunk.strip())
  
      return chunks
  
imports: import spacy
label_desc: Use image node_id 4 for calling a global function with example usage: split_dep_parse(text) and returns: chunks