code: def _print_predictions(self, batch, gold_label_type):
      lines = []
      for datapoint in batch:
          eval_line = f"\n{datapoint.to_original_text()}\n"
  
          for relation in datapoint.get_relations(gold_label_type):
              symbol = (
                  "✓"
                  if relation.get_label(gold_label_type).value
                  == relation.get_label("predicted").value
                  else "❌"
              )
              eval_line += (
                  f' - "{relation.text}"\t{relation.get_label(gold_label_type).value}'
                  f' --> {relation.get_label("predicted").value} ({symbol})\n'
              )
  
          lines.append(eval_line)
      return lines
  
file_path: flair/flair/models/relation_extractor_model.py
imports: import logging
  from pathlib import Path
  from typing import Any, Dict, List, Optional, Set, Tuple, Union
  import torch
  import flair.embeddings
  import flair.nn
  from flair.data import Relation, Sentence
  from flair.file_utils import cached_path
label_desc: Use image node_id 4 for calling the RelationExtractor obj's underlying member method code with example usage: obj._print_predictions(batch, gold_label_type) and returns: lines