Creation (Copied & adapted from https://github.com/stanford-crfm/helm/blob/0eaaa62a2263ddb94e9850ee629423b010f57e4a/src/helm/benchmark/scenarios/babi_qa_scenario.py): ```python !wget http://www.thespermwhale.com/jaseweston/babi/tasks_1-20_v1-2.tar.gz !tar -xf tasks_1-20_v1-2.tar.gz import json from typing import List tasks = list(range(1, 20)) splits = ["train", "valid", "test"] def process_path(path: str) -> str: """Turn a path string (task 19) from the original format 's,w' to a verbal model-friendly format 'south west'""" steps: List[str] = path.split(",") directions = {"s": "south", "n": "north", "e": "east", "w": "west"} path = " ".join([directions[step] for step in steps]) return path for split in splits: with open(f"babi_{split}.jsonl", "w") as f_base: for task in tasks: split_path: str = f"./tasks_1-20_v1-2/en-valid/qa{task}_{split}.txt" with open(split_path, "r") as f: facts = list(f) story: List[str] = [] for fact in facts: fid = int(fact.split(" ")[0]) if fid == 1: story = [] fact = " ".join(fact.split(" ")[1:]) is_question = "?" in fact if is_question: question, answer = fact.split("\t")[:2] question, answer = question.strip(), answer.strip() # All tasks except task 19 have a verbal single-word answer (e.g. kitchen, apple, yes). # Task 19 (path finding) has a non verbal answer format ( if task == 19: answer = process_path(answer) f_base.write(json.dumps({ "passage": "".join(story), "question": question, "answer": answer, "task": task, }) + "\n") if "?" in story: print("STORY", "".join(story)) else: story.append(fact) ```