Datasets:
piqa

- {"plain_text": {"description": "To apply eyeshadow without a brush, should I use a cotton swab or a toothpick?\nQuestions requiring this kind of physical commonsense pose a challenge to state-of-the-art\nnatural language understanding systems. The PIQA dataset introduces the task of physical commonsense reasoning\nand a corresponding benchmark dataset Physical Interaction: Question Answering or PIQA.\n\nPhysical commonsense knowledge is a major challenge on the road to true AI-completeness,\nincluding robots that interact with the world and understand natural language.\n\nThe dataset focuses on everyday situations with a preference for atypical solutions.\nThe dataset is inspired by instructables.com, which provides users with instructions on how to build, craft,\nbake, or manipulate objects using everyday materials.\n\nThe underlying task is formualted as multiple choice question answering:\ngiven a question `q` and two possible solutions `s1`, `s2`, a model or\na human must choose the most appropriate solution, of which exactly one is correct.\nThe dataset is further cleaned of basic artifacts using the AFLite algorithm which is an improvement of\nadversarial filtering. The dataset contains 16,000 examples for training, 2,000 for development and 3,000 for testing.\n", "citation": "@inproceedings{Bisk2020,\n author = {Yonatan Bisk and Rowan Zellers and\n Ronan Le Bras and Jianfeng Gao\n and Yejin Choi},\n title = {PIQA: Reasoning about Physical Commonsense in\n Natural Language},\n booktitle = {Thirty-Fourth AAAI Conference on\n Artificial Intelligence},\n year = {2020},\n}\n", "homepage": "https://yonatanbisk.com/piqa/", "license": "", "features": {"goal": {"dtype": "string", "id": null, "_type": "Value"}, "sol1": {"dtype": "string", "id": null, "_type": "Value"}, "sol2": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 2, "names": ["0", "1"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "builder_name": "piqa", "config_name": "plain_text", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 4104026, "num_examples": 16113, "dataset_name": "piqa"}, "test": {"name": "test", "num_bytes": 761521, "num_examples": 3084, "dataset_name": "piqa"}, "validation": {"name": "validation", "num_bytes": 464321, "num_examples": 1838, "dataset_name": "piqa"}}, "download_checksums": {"https://storage.googleapis.com/ai2-mosaic/public/physicaliqa/physicaliqa-train-dev.zip": {"num_bytes": 1824009, "checksum": "54d32a04f59a7e354396f321723c8d7ec35cc6b08506563d8d1ffcc15ce98ddd"}, "https://yonatanbisk.com/piqa/data/tests.jsonl": {"num_bytes": 814616, "checksum": "402f1e2e61347db773e6e5e0a6b24f97396b59f6fd046dcdcbc12f483ac8553b"}}, "download_size": 2638625, "post_processing_size": null, "dataset_size": 5329868, "size_in_bytes": 7968493}}