code: def _preprocess_data(data, cfg):
      relation_data = load_csv(
          os.path.join(cfg.cwd, cfg.data_path, "relation.csv"),
          verbose=False,
      )
      rels = _handle_relation_data(relation_data)
      _lm_serialize(data, cfg)
      return data, rels
  
file_path: DeepKE/example/triple/cnschema/predict.py
imports: import hydra
  import os
  import torch
  import logging
  from hydra import utils
  import json
  from pyld import jsonld
  from preprocess import _handle_relation_data, _lm_serialize
  from utils import load_csv
  from LMModel import LM
  from InferBert import InferNer
label_desc: Use image node_id 1 for calling a global function with example usage: _preprocess_data(data, cfg) and returns: data,  rels