Datasets:
Tasks:
Question Answering
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Language Creators:
expert-generated
Annotations Creators:
expert-generated
Source Datasets:
original
ArXiv:
Tags:
License:
| # Copyright 2020 The HuggingFace Datasets Authors and Cory Paik | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the 'License'); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an 'AS IS' BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| # ============================================================================== | |
| """ Physical Reasoning about Objects Through Space and Time (PROST) | |
| PROST is a probing dataset to evaluate the ability of pretrained LMs to | |
| understand and reason about the physical world. | |
| """ | |
| import json | |
| import datasets | |
| _CITATION = """\ | |
| @inproceedings{aroca-ouellette-etal-2021-prost, | |
| title = "{PROST}: {P}hysical Reasoning about Objects through Space and Time", | |
| author = "Aroca-Ouellette, St{\'e}phane and | |
| Paik, Cory and | |
| Roncone, Alessandro and | |
| Kann, Katharina", | |
| booktitle = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021", | |
| month = aug, | |
| year = "2021", | |
| address = "Online", | |
| publisher = "Association for Computational Linguistics", | |
| url = "https://aclanthology.org/2021.findings-acl.404", | |
| pages = "4597--4608", | |
| } | |
| """ | |
| _DESCRIPTION = """\ | |
| *Physical Reasoning about Objects Through Space and Time* (PROST) is a probing dataset to evaluate the ability of pretrained LMs to understand and reason about the physical world. PROST consists of 18,736 cloze-style multiple choice questions from 14 manually curated templates, covering 10 physical reasoning concepts: direction, mass, height, circumference, stackable, rollable, graspable, breakable, slideable, and bounceable. | |
| """ | |
| _HOMEPAGE = 'https://github.com/nala-cub/prost' | |
| _LICENSE = 'Apache 2.0' | |
| _URL = 'https://huggingface.co/datasets/corypaik/prost/resolve/main/data' | |
| _URLs = {'default': f'{_URL}/default.jsonl'} | |
| MC_LABELS = list('ABCD') | |
| class Prost(datasets.GeneratorBasedBuilder): | |
| VERSION = datasets.Version('1.0.1') | |
| def _info(self): | |
| features = datasets.Features({ | |
| 'A': datasets.Value('string'), | |
| 'B': datasets.Value('string'), | |
| 'C': datasets.Value('string'), | |
| 'D': datasets.Value('string'), | |
| 'context': datasets.Value('string'), | |
| 'question': datasets.Value('string'), | |
| 'ex_question': datasets.Value('string'), | |
| 'group': datasets.Value('string'), | |
| 'label': datasets.ClassLabel(names=MC_LABELS), | |
| 'name': datasets.Value('string'),}) | |
| return datasets.DatasetInfo(description=_DESCRIPTION, features=features, | |
| supervised_keys=None, homepage=_HOMEPAGE, | |
| license=_LICENSE, citation=_CITATION) | |
| def _split_generators(self, dl_manager): | |
| """ Returns SplitGenerators.""" | |
| path = dl_manager.download_and_extract(_URLs[self.config.name]) | |
| kwargs = {'path': path} | |
| return [datasets.SplitGenerator(datasets.Split.TEST, gen_kwargs=kwargs)] | |
| def _generate_examples(self, path): | |
| with open(path, 'r') as f: | |
| for _id, line in enumerate(f.readlines()): | |
| yield _id, json.loads(line) | |