code: def _create_examples(self, lines, set_type):
      examples = []
      for i, (sentence, label) in enumerate(lines):
          guid = "%s-%s" % (set_type, i)
          text_a = " ".join(sentence)
          text_b = None
          label = label
          examples.append(
              InputExample(
                  guid=guid, text_a=text_a, text_b=text_b, label=label
              )
          )
      return examples
  
imports: import pandas
  import os
  import torch
  from pathlib import Path
  import pickle
  from torch.utils.data import TensorDataset, DataLoader, RandomSampler, SequentialSampler
  from torch.utils.data.distributed import DistributedSampler
  from transformers import WEIGHTS_NAME, BertConfig, BertForSequenceClassification, BertTokenizer, XLMConfig, XLMForSequenceClassification, XLMTokenizer, XLNetConfig, XLNetForSequenceClassification, XLNetTokenizer
label_desc: Use image node_id 6 for calling the NERTextProcessor obj's underlying member method code with example usage: obj._create_examples(lines, set_type) and returns: examples