"""TODO(quarel): Add a description here.""" import json import os import datasets # TODO(quarel): BibTeX citation _CITATION = """\ @inproceedings{quarel_v1, title={QuaRel: A Dataset and Models for Answering Questions about Qualitative Relationships}, author={Oyvind Tafjord, Peter Clark, Matt Gardner, Wen-tau Yih, Ashish Sabharwal}, year={2018}, journal={arXiv:1805.05377v1} } """ # TODO(quarel): _DESCRIPTION = """ QuaRel is a crowdsourced dataset of 2771 multiple-choice story questions, including their logical forms. """ _URL = "https://s3-us-west-2.amazonaws.com/ai2-website/data/quarel-dataset-v1-nov2018.zip" class Quarel(datasets.GeneratorBasedBuilder): """TODO(quarel): Short description of my dataset.""" # TODO(quarel): Set up version. VERSION = datasets.Version("0.1.0") def _info(self): # TODO(quarel): Specifies the datasets.DatasetInfo object return datasets.DatasetInfo( # This is the description that will appear on the datasets page. description=_DESCRIPTION, # datasets.features.FeatureConnectors features=datasets.Features( { # These are the features of your dataset like images, labels ... "id": datasets.Value("string"), "answer_index": datasets.Value("int32"), "logical_forms": datasets.features.Sequence(datasets.Value("string")), "logical_form_pretty": datasets.Value("string"), "world_literals": datasets.features.Sequence( {"world1": datasets.Value("string"), "world2": datasets.Value("string")} ), "question": datasets.Value("string"), } ), # If there's a common (input, target) tuple from the features, # specify them here. They'll be used if as_supervised=True in # builder.as_dataset. supervised_keys=None, # Homepage of the dataset for documentation homepage="https://allenai.org/data/quarel", citation=_CITATION, ) def _split_generators(self, dl_manager): """Returns SplitGenerators.""" # TODO(quarel): Downloads the data and defines the splits # dl_manager is a datasets.download.DownloadManager that can be used to # download and extract URLs dl_dir = dl_manager.download_and_extract(_URL) data_dir = os.path.join(dl_dir, "quarel-dataset-v1") return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, # These kwargs will be passed to _generate_examples gen_kwargs={"filepath": os.path.join(data_dir, "quarel-v1-train.jsonl")}, ), datasets.SplitGenerator( name=datasets.Split.TEST, # These kwargs will be passed to _generate_examples gen_kwargs={"filepath": os.path.join(data_dir, "quarel-v1-test.jsonl")}, ), datasets.SplitGenerator( name=datasets.Split.VALIDATION, # These kwargs will be passed to _generate_examples gen_kwargs={"filepath": os.path.join(data_dir, "quarel-v1-dev.jsonl")}, ), ] def _generate_examples(self, filepath): """Yields examples.""" # TODO(quarel): Yields (key, example) tuples from the dataset with open(filepath, encoding="utf-8") as f: for id_, row in enumerate(f): data = json.loads(row) yield id_, { "id": data["id"], "answer_index": data["answer_index"], "logical_forms": data["logical_forms"], "world_literals": { "world1": [data["world_literals"]["world1"]], "world2": [data["world_literals"]["world2"]], }, "logical_form_pretty": data["logical_form_pretty"], "question": data["question"], }