code: def get_inferred_about_data(task, opt, threshold=0.8):
      """
      Load inferred ABOUT data from teh ABOUT classifier.
      """
      root = os.path.join(
          opt["datapath"],
          "md_gender",
          "data_to_release",
          "inferred_about",
      )
      task_str = task.split(":")[-1]
      dt = opt["datatype"].split(":")[0]
      with open(
          os.path.join(root, f"{task_str}_{dt}_binary.txt"), "r"
      ) as f:
          lines = f.read().splitlines()
      examples = []
      for line in lines:
          text, label, score = line.split("\t")
          if threshold is not None and float(score) < threshold:
              # replace label with NEUTRAL
              label = f"ABOUT:{NEUTRAL}"
          if not text or not label:
              continue
          examples.append(
              {
                  "text": text,
                  "labels": [label],
                  "class_type": "about",
                  "label_candidates": ABOUT_CANDS,
                  "episode_done": True,
              }
          )
  
      return examples
  
file_path: ParlAI/parlai/tasks/md_gender/utils.py
imports: import os
  import random
  from collections import defaultdict
  from parlai.tasks.md_gender.build import build
label_desc: Use image node_id 4 for calling a global function with example usage: get_inferred_about_data(task, opt, threshold) and returns: examples