Datasets:
Tags:
License:
| import json | |
| import datasets | |
| import os | |
| _CITATION = """\ | |
| @article{huggingface:dataset, | |
| title = {ParsiNLU: A Suite of Language Understanding Challenges for Persian}, | |
| authors = {Khashabi, Daniel and Cohan, Arman and Shakeri, Siamak and Hosseini, Pedram and Pezeshkpour, Pouya and Alikhani, Malihe and Aminnaseri, Moin and Bitaab, Marzieh and Brahman, Faeze and Ghazarian, Sarik and others}, | |
| year={2020} | |
| journal = {arXiv e-prints}, | |
| eprint = {2012.06154}, | |
| } | |
| """ | |
| # You can copy an official description | |
| _DESCRIPTION = """A Persian multiple choice task.""" | |
| _HOMEPAGE = "https://github.com/persiannlp/parsinlu/" | |
| _LICENSE = "CC BY-NC-SA 4.0" | |
| _URL = "https://raw.githubusercontent.com/persiannlp/parsinlu/master/data/multiple-choice/" | |
| _URLs = { | |
| "train": _URL + "train.jsonl", | |
| "val": _URL + "valid.jsonl", | |
| "test": _URL + "test.jsonl", | |
| } | |
| class ParsinluMultipleChoice(datasets.GeneratorBasedBuilder): | |
| """ParsiNLU Persian multiple choice task.""" | |
| VERSION = datasets.Version("1.0.0") | |
| BUILDER_CONFIGS = [ | |
| datasets.BuilderConfig( | |
| name="parsinlu-repo", version=VERSION, description="Here the task is to pick a correct answer among 3-5 given candidate answers" | |
| ),] | |
| def _info(self): | |
| features = datasets.Features( | |
| { | |
| "answer": datasets.Value("int32"), | |
| "candidates": datasets.features.Sequence(feature=datasets.Value(dtype='string', id=None), length=-1), | |
| "category": datasets.Value("string"), | |
| "question": datasets.Value("string"), | |
| "id": datasets.Value("string") | |
| } | |
| ) | |
| return datasets.DatasetInfo( | |
| # This is the description that will appear on the datasets page. | |
| description=_DESCRIPTION, | |
| # This defines the different columns of the dataset and their types | |
| features=features, # Here we define them above because they are different between the two configurations | |
| # 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=_HOMEPAGE, | |
| # License for the dataset if available | |
| license=_LICENSE, | |
| # Citation for the dataset | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| data_dir = dl_manager.download_and_extract(_URLs) | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| # These kwargs will be passed to _generate_examples | |
| gen_kwargs={ | |
| "filepath": data_dir["train"], | |
| "split": "train", | |
| }, | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TEST, | |
| # These kwargs will be passed to _generate_examples | |
| gen_kwargs={ | |
| "filepath": data_dir["test"], | |
| "split": "test"}, | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.VALIDATION, | |
| # These kwargs will be passed to _generate_examples | |
| gen_kwargs={ | |
| "filepath": data_dir["val"], | |
| "split": "validation", | |
| }, | |
| ), | |
| ] | |
| def _generate_examples(self, filepath, split): | |
| def get_answer_index(passage, answer): | |
| return passage.index(answer) if answer in passage else -1 | |
| with open(filepath, encoding="utf-8") as f: | |
| for id_, row in enumerate(f): | |
| data = json.loads(row) | |
| yield id_, { | |
| "answer": int(data["answer"]), | |
| "candidates": data["candidates"], | |
| "category": data["category"], | |
| "question": data["question"], | |
| "id": data['id'] | |
| } |