class_docstr: RAFT: A Real-World Few-Shot Text Classification Benchmark
  https://arxiv.org/abs/2109.14076
  
  Official website for RAFT dataset:
  https://raft.elicit.org/
  
  Dataset summary:
  https://huggingface.co/datasets/ought/raft/blob/main/README.md
  
  Prompts are adapted from:
  https://github.com/oughtinc/raft-baselines/tree/master/example_prompts
  
  Subsets:
  
  - ade_corpus_v2
  - banking_77
  - neurips_impact_statement_risks
  - one_stop_english
  - overruling
  - semiconductor_org_types
  - systematic_review_inclusion
  - tai_safety_research
  - terms_of_service
  - tweet_eval_hate
  - twitter_complaints
  
  Prompt format
  
      Sentence: <sentence>
      Label: <label>
  
  Examples from ADE corpus (adverse drug effect):
  
      Sentence: No regional side effects were noted.
      Label: not ADE-related
code: def load_prompt_construction_settings(self):
      # Load from prompt construction settings
      cache_dir = str(Path(self.output_path) / "data")
      return get_raft_prompt_settings(self.subset, cache_dir)
  
file_path: H2O/h2o_hf/helm/src/helm/benchmark/scenarios/raft_scenario.py
imports: import random
  import os
  import json
  import tempfile
  import datasets
  from pathlib import Path
  from typing import List, Dict
  from helm.common.general import ensure_file_downloaded, ensure_directory_exists
  from .scenario import Scenario, Instance, Reference, CORRECT_TAG, TRAIN_SPLIT, TEST_SPLIT, Input, Output
label_desc: Use image node_id 2 for calling the RAFTScenario obj's underlying member method code with example usage: obj.load_prompt_construction_settings() and returns: get_raft_prompt_settings