code: def pos_tagging(doc):
      pred_whole = set()
      output = {
          "text": [],
          "lemma_": [],
          "pos_": [],
          "tag_": [],
          "dep_": [],
          "shape_": [],
          "is_alpha": [],
          "is_stop": [],
      }
      for token in doc:
          output["text"].append(token.text)
          output["lemma_"].append(token.lemma_)
          output["pos_"].append(token.pos_)
          output["tag_"].append(token.tag_)
          output["dep_"].append(token.dep_)
          output["shape_"].append(token.shape_)
          output["is_alpha"].append(token.is_alpha)
          output["is_stop"].append(token.is_stop)
          pred_whole.add(
              (
                  token.text,
                  token.lemma_,
                  token.pos_,
                  token.tag_,
                  token.dep_,
                  token.shape_,
                  token.is_alpha,
                  token.is_stop,
              )
          )
      return pred_whole, output
  
file_path: mindsdb/mindsdb/integrations/handlers/spacy_handler/spacy_handler.py
imports: import spacy
  import pandas
  from mindsdb.integrations.libs.base import BaseMLEngine
  from typing import Optional
label_desc: Use image node_id 4 for calling a global function with example usage: pos_tagging(doc) and returns: pred_whole,  output