Datasets:
ai2_arc

Languages: English
Multilinguality: monolingual
Size Categories: 1K<n<10K
Language Creators: found
Annotations Creators: found
Source Datasets: original
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Update files from the datasets library (from 1.0.0)

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Release notes: https://github.com/huggingface/datasets/releases/tag/1.0.0

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ai2_arc.py ADDED
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+ """TODO(arc): Add a description here."""
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+
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+ from __future__ import absolute_import, division, print_function
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+
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+ import json
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+ import os
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+
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+ import datasets
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+
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+
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+ # TODO(ai2_arc): BibTeX citation
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+ _CITATION = """\
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+ @article{allenai:arc,
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+ author = {Peter Clark and Isaac Cowhey and Oren Etzioni and Tushar Khot and
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+ Ashish Sabharwal and Carissa Schoenick and Oyvind Tafjord},
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+ title = {Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge},
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+ journal = {arXiv:1803.05457v1},
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+ year = {2018},
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+ }
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+ """
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+
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+ # TODO(ai2_arc):
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+ _DESCRIPTION = """\
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+ A new dataset of 7,787 genuine grade-school level, multiple-choice science questions, assembled to encourage research in
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+ advanced question-answering. The dataset is partitioned into a Challenge Set and an Easy Set, where the former contains
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+ only questions answered incorrectly by both a retrieval-based algorithm and a word co-occurrence algorithm. We are also
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+ including a corpus of over 14 million science sentences relevant to the task, and an implementation of three neural baseline models for this dataset. We pose ARC as a challenge to the community.
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+ """
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+
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+ _URL = "https://s3-us-west-2.amazonaws.com/ai2-website/data/ARC-V1-Feb2018.zip"
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+
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+
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+ class Ai2ArcConfig(datasets.BuilderConfig):
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+ """BuilderConfig for Ai2ARC."""
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+
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+ def __init__(self, **kwargs):
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+ """BuilderConfig for Ai2Arc.
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+
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+ Args:
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+ **kwargs: keyword arguments forwarded to super.
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+ """
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+ super(Ai2ArcConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
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+
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+
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+ class Ai2Arc(datasets.GeneratorBasedBuilder):
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+ """TODO(arc): Short description of my dataset."""
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+
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+ # TODO(arc): Set up version.
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+ VERSION = datasets.Version("1.0.0")
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+ BUILDER_CONFIGS = [
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+ Ai2ArcConfig(
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+ name="ARC-Challenge",
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+ description="""\
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+ Challenge Set of 2590 “hard” questions (those that both a retrieval and a co-occurrence method fail to answer correctly)
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+ """,
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+ ),
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+ Ai2ArcConfig(
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+ name="ARC-Easy",
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+ description="""\
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+ Easy Set of 5197 questions
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+ """,
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+ ),
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+ ]
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+
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+ def _info(self):
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+ # TODO(ai2_arc): Specifies the datasets.DatasetInfo object
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+ return datasets.DatasetInfo(
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+ # This is the description that will appear on the datasets page.
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+ description=_DESCRIPTION,
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+ # datasets.features.FeatureConnectors
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+ features=datasets.Features(
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+ {
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+ "id": datasets.Value("string"),
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+ "question": datasets.Value("string"),
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+ "choices": datasets.features.Sequence(
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+ {"text": datasets.Value("string"), "label": datasets.Value("string")}
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+ ),
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+ "answerKey": datasets.Value("string")
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+ # These are the features of your dataset like images, labels ...
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+ }
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+ ),
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+ # If there's a common (input, target) tuple from the features,
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+ # specify them here. They'll be used if as_supervised=True in
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+ # builder.as_dataset.
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+ supervised_keys=None,
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+ # Homepage of the dataset for documentation
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+ homepage="https://allenai.org/data/arc",
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+ citation=_CITATION,
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+ )
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+
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+ def _split_generators(self, dl_manager):
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+ """Returns SplitGenerators."""
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+ # TODO(ai2_arc): Downloads the data and defines the splits
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+ # dl_manager is a datasets.download.DownloadManager that can be used to
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+ # download and extract URLs
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+ dl_dir = dl_manager.download_and_extract(_URL)
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+ data_dir = os.path.join(dl_dir, "ARC-V1-Feb2018-2")
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+ return [
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+ datasets.SplitGenerator(
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+ name=datasets.Split.TRAIN,
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+ # These kwargs will be passed to _generate_examples
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+ gen_kwargs={"filepath": os.path.join(data_dir, self.config.name, self.config.name + "-Train.jsonl")},
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+ ),
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+ datasets.SplitGenerator(
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+ name=datasets.Split.TEST,
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+ # These kwargs will be passed to _generate_examples
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+ gen_kwargs={"filepath": os.path.join(data_dir, self.config.name, self.config.name + "-Test.jsonl")},
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+ ),
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+ datasets.SplitGenerator(
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+ name=datasets.Split.VALIDATION,
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+ # These kwargs will be passed to _generate_examples
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+ gen_kwargs={"filepath": os.path.join(data_dir, self.config.name, self.config.name + "-Dev.jsonl")},
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+ ),
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+ ]
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+
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+ def _generate_examples(self, filepath):
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+ """Yields examples."""
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+ # TODO(ai2_arc): Yields (key, example) tuples from the dataset
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+ with open(filepath, encoding="utf-8") as f:
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+ for row in f:
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+ data = json.loads(row)
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+ answerkey = data["answerKey"]
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+ id_ = data["id"]
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+ question = data["question"]["stem"]
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+ choices = data["question"]["choices"]
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+ text_choices = [choice["text"] for choice in choices]
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+ label_choices = [choice["label"] for choice in choices]
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+ yield id_, {
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+ "id": id_,
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+ "answerKey": answerkey,
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+ "question": question,
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+ "choices": {"text": text_choices, "label": label_choices},
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+ }
dataset_infos.json ADDED
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+ {"ARC-Challenge": {"description": "A new dataset of 7,787 genuine grade-school level, multiple-choice science questions, assembled to encourage research in\n advanced question-answering. The dataset is partitioned into a Challenge Set and an Easy Set, where the former contains\n only questions answered incorrectly by both a retrieval-based algorithm and a word co-occurrence algorithm. We are also\n including a corpus of over 14 million science sentences relevant to the task, and an implementation of three neural baseline models for this dataset. We pose ARC as a challenge to the community.\n", "citation": "@article{allenai:arc,\n author = {Peter Clark and Isaac Cowhey and Oren Etzioni and Tushar Khot and\n Ashish Sabharwal and Carissa Schoenick and Oyvind Tafjord},\n title = {Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge},\n journal = {arXiv:1803.05457v1},\n year = {2018},\n}\n", "homepage": "https://allenai.org/data/arc", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "choices": {"feature": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "answerKey": {"dtype": "string", "id": null, "_type": "Value"}}, "supervised_keys": null, "builder_name": "ai2_arc", "config_name": "ARC-Challenge", "version": {"version_str": "1.0.0", "description": "", "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 377740, "num_examples": 1172, "dataset_name": "ai2_arc"}, "train": {"name": "train", "num_bytes": 351888, "num_examples": 1119, "dataset_name": "ai2_arc"}, "validation": {"name": "validation", "num_bytes": 97254, "num_examples": 299, "dataset_name": "ai2_arc"}}, "download_checksums": {"https://s3-us-west-2.amazonaws.com/ai2-website/data/ARC-V1-Feb2018.zip": {"num_bytes": 680841265, "checksum": "6d2d5ab50b2ceec6ba5f79c921be77cf2de712ea25a2b3f4fff3acc101cecfa0"}}, "download_size": 680841265, "dataset_size": 826882, "size_in_bytes": 681668147}, "ARC-Easy": {"description": "A new dataset of 7,787 genuine grade-school level, multiple-choice science questions, assembled to encourage research in\n advanced question-answering. The dataset is partitioned into a Challenge Set and an Easy Set, where the former contains\n only questions answered incorrectly by both a retrieval-based algorithm and a word co-occurrence algorithm. We are also\n including a corpus of over 14 million science sentences relevant to the task, and an implementation of three neural baseline models for this dataset. We pose ARC as a challenge to the community.\n", "citation": "@article{allenai:arc,\n author = {Peter Clark and Isaac Cowhey and Oren Etzioni and Tushar Khot and\n Ashish Sabharwal and Carissa Schoenick and Oyvind Tafjord},\n title = {Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge},\n journal = {arXiv:1803.05457v1},\n year = {2018},\n}\n", "homepage": "https://allenai.org/data/arc", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "choices": {"feature": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "answerKey": {"dtype": "string", "id": null, "_type": "Value"}}, "supervised_keys": null, "builder_name": "ai2_arc", "config_name": "ARC-Easy", "version": {"version_str": "1.0.0", "description": "", "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 661997, "num_examples": 2376, "dataset_name": "ai2_arc"}, "train": {"name": "train", "num_bytes": 623254, "num_examples": 2251, "dataset_name": "ai2_arc"}, "validation": {"name": "validation", "num_bytes": 158498, "num_examples": 570, "dataset_name": "ai2_arc"}}, "download_checksums": {"https://s3-us-west-2.amazonaws.com/ai2-website/data/ARC-V1-Feb2018.zip": {"num_bytes": 680841265, "checksum": "6d2d5ab50b2ceec6ba5f79c921be77cf2de712ea25a2b3f4fff3acc101cecfa0"}}, "download_size": 680841265, "dataset_size": 1443749, "size_in_bytes": 682285014}}
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