Datasets:
riddle_sense

- {"default": {"description": "Answering such a riddle-style question is a challenging cognitive process, in that it requires \ncomplex commonsense reasoning abilities, an understanding of figurative language, and counterfactual reasoning \nskills, which are all important abilities for advanced natural language understanding (NLU). However, \nthere is currently no dedicated datasets aiming to test these abilities. Herein, we present RiddleSense, \na new multiple-choice question answering task, which comes with the first large dataset (5.7k examples) for answering \nriddle-style commonsense questions. We systematically evaluate a wide range of models over the challenge, \nand point out that there is a large gap between the best-supervised model and human performance \u2014 suggesting \nintriguing future research in the direction of higher-order commonsense reasoning and linguistic creativity towards \nbuilding advanced NLU systems. \n\n", "citation": "@InProceedings{lin-etal-2021-riddlesense,\ntitle={RiddleSense: Reasoning about Riddle Questions Featuring Linguistic Creativity and Commonsense Knowledge},\nauthor={Lin, Bill Yuchen and Wu, Ziyi and Yang, Yichi and Lee, Dong-Ho and Ren, Xiang},\njournal={Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics (ACL-IJCNLP 2021): Findings},\nyear={2021}\n\n", "homepage": "https://inklab.usc.edu/RiddleSense/", "license": "", "features": {"answerKey": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "choices": {"feature": {"label": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "riddle_sense", "config_name": "default", "version": {"version_str": "0.1.0", "description": null, "major": 0, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 720715, "num_examples": 3510, "dataset_name": "riddle_sense"}, "validation": {"name": "validation", "num_bytes": 208276, "num_examples": 1021, "dataset_name": "riddle_sense"}, "test": {"name": "test", "num_bytes": 212790, "num_examples": 1184, "dataset_name": "riddle_sense"}}, "download_checksums": {"https://inklab.usc.edu/RiddleSense/riddlesense_dataset/rs_train.jsonl": {"num_bytes": 1293825, "checksum": "d82423612b706aace65f2ee5f1f0f2b71e2f6ea27102a74864a2f9dfada2fe1f"}, "https://inklab.usc.edu/RiddleSense/riddlesense_dataset/rs_dev.jsonl": {"num_bytes": 375327, "checksum": "6680e5998bdbe65d85b02f620e64c365c52830ee5bfeb4d82c9e2a7cf4675365"}, "https://inklab.usc.edu/RiddleSense/riddlesense_dataset/rs_test_hidden.jsonl": {"num_bytes": 413970, "checksum": "ea83bfeff23fa77da7a922fdb272e7c7bc8ec628d4e54b3eb463c93bcfee60cf"}}, "download_size": 2083122, "post_processing_size": null, "dataset_size": 1141781, "size_in_bytes": 3224903}}