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