import json import os import datasets _CITATION = """\ @InProceedings{anli, author = {Chandra, Bhagavatula and Ronan, Le Bras and Chaitanya, Malaviya and Keisuke, Sakaguchi and Ari, Holtzman and Hannah, Rashkin and Doug, Downey and Scott, Wen-tau Yih and Yejin, Choi}, title = {Abductive Commonsense Reasoning}, year = {2020} }""" _DESCRIPTION = """\ the Abductive Natural Language Generation Dataset from AI2 """ _DATA_URL = "https://storage.googleapis.com/ai2-mosaic/public/abductive-commonsense-reasoning-iclr2020/anlg.zip" _HOMEPAGE = "https://github.com/allenai/abductive-commonsense-reasoning" class ArtConfig(datasets.BuilderConfig): """BuilderConfig for Art.""" def __init__(self, **kwargs): """BuilderConfig for Art. Args: **kwargs: keyword arguments forwarded to super. """ super(ArtConfig, self).__init__(version=datasets.Version("0.1.0", ""), **kwargs) class Art(datasets.GeneratorBasedBuilder): VERSION = datasets.Version("0.1.0") BUILDER_CONFIGS = [ ArtConfig( name="anlg", description="""\ Abductive Natural Language Generation Dataset from AI2. """, ), ] def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { "gem_id": datasets.Value("string"), "observation_1": datasets.Value("string"), "observation_2": datasets.Value("string"), "label": datasets.Value("string"), } ), homepage=_HOMEPAGE, citation=_CITATION, ) def _split_generators(self, dl_manager): ds_splits = [datasets.Split.TRAIN, datasets.Split.VALIDATION, datasets.Split.TEST] splits = ["train", "dev", "test"] dl_dir = dl_manager.download_and_extract(_DATA_URL) return [ datasets.SplitGenerator( name=ds_split, gen_kwargs={ "filepath": os.path.join(dl_dir, "anlg", f"{split}-w-comet-preds.jsonl"), "split": split if split != "dev" else "validation" # adheres to GEM naming conventions }, ) for ds_split, split in zip(ds_splits, splits) ] def _generate_examples(self, filepath, split): with open(filepath, "r", encoding="utf-8") as f: data = [json.loads(line) for line in f.readlines()] for idx, row in enumerate(data): label = row[f"hyp{row['label']}"] yield idx, { "gem_id": f"GEM-ART-{split}-{idx}", "observation_1": row["obs1"], "observation_2": row["obs2"], "label": label, }