code: def normalize_pos(word, in_pos):
      if in_pos is None:
          return POS.OTHER
      if word.lower() in PRONOUNS_LIST and in_pos.startswith("PR"):
          return POS[PRONOUNS_LIST[word.lower()]]
      if in_pos == "CC":
          return POS.CONJ
      if in_pos == "CD":
          return POS.NUM
      if in_pos == "DT":
          return POS.DET
      if in_pos == "EX":
          return POS.EX
      if in_pos == "FW":
          return POS.FW
      if in_pos == "IN":
          return POS.PREP
      if in_pos == "TO":
          return POS.PREP
      if in_pos.startswith("JJ"):
          return POS.ADJ
      if in_pos == "LS":
          return POS.LS
      if in_pos == "MD":
          return POS.MD
      if in_pos.startswith("NN"):
          return POS.NN
      if in_pos == "PDT":
          return POS.DET
      if in_pos == "POS":
          return POS.POS
      if in_pos.startswith("PR"):
          return POS.PRON
      if in_pos.startswith("RB"):
          return POS.ADV
      if in_pos == "RP":
          return POS.RP
      if in_pos == "SYM":
          return POS.SYM
      if in_pos == "UH":
          return POS.INTERJ
      if in_pos.startswith("VB"):
          return POS.VB
      if in_pos == "WDT":
          return POS.WH_DET
      if in_pos.startswith("WP"):
          return POS.WH_PROP
      if in_pos == "WRB":
          return POS.WH_ADV
      return POS.OTHER
  
imports: import csv
  from enum import Enum
  from os import PathLike
  from nlp_architect.models.absa import TRAIN_LEXICONS
label_desc: Use image node_id 2 for calling a global function with example usage: normalize_pos(word, in_pos) and returns: POS, POS, POS, POS, POS, POS, POS, POS, POS, POS, POS, POS, POS, POS, POS, POS, POS, POS, POS, POS, POS, POS, POS, POS, POS