code: def load_entity_dict(logger, params, is_zeshel):
      if is_zeshel:
          return load_entity_dict_zeshel(logger, params)
  
      path = params.get("entity_dict_path", None)
      assert path is not None, "Error! entity_dict_path is empty."
  
      entity_list = []
      logger.info("Loading entity description from path: " + path)
      with open(path, "rt") as f:
          for line in f:
              sample = json.loads(line.rstrip())
              title = sample["title"]
              text = sample.get("text", "").strip()
              entity_list.append((title, text))
              if params["debug"] and len(entity_list) > 200:
                  break
  
      return entity_list
  
imports: import argparse
  import json
  import logging
  import os
  import torch
  from tqdm import tqdm
  from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset
  from pytorch_transformers.tokenization_bert import BertTokenizer
  from blink.biencoder.biencoder import BiEncoderRanker
  import blink.biencoder.data_process
  import blink.biencoder.nn_prediction
  import blink.candidate_ranking.utils
  from blink.biencoder.zeshel_utils import WORLDS, load_entity_dict_zeshel, Stats
  from blink.common.params import BlinkParser
label_desc: Use image node_id 1 for calling a global function with example usage: load_entity_dict(logger, params, is_zeshel) and returns: entity_list, load_entity_dict_zeshel