| 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) | |
| ``` |