Datasets:
Tasks:
Text Classification
Modalities:
Text
Languages:
Persian
Size:
10K<n<100K
ArXiv:
Tags:
License:
import json | |
import csv | |
import datasets | |
_CITATION = """\\ | |
@article{amirkhani2020farstail, | |
title={FarsTail: A Persian Natural Language Inference Dataset}, | |
author={Hossein Amirkhani, Mohammad Azari Jafari, Azadeh Amirak, Zohreh Pourjafari, Soroush Faridan Jahromi, and Zeinab Kouhkan}, | |
journal={arXiv preprint arXiv:2009.08820}, | |
year={2020} | |
} | |
""" | |
_DESCRIPTION = """\\\\\\\\ | |
A Persian Natural Language Inference Dataset | |
""" | |
_URL = "https://raw.githubusercontent.com/dml-qom/FarsTail/master/data/" | |
_URLS = { | |
"train": _URL + "Train-word.csv", | |
"test": _URL + "Test-word.csv", | |
"validation": _URL + "Val-word.csv" | |
} | |
class FarsTailConfig(datasets.BuilderConfig): | |
"""BuilderConfig for FarsTail.""" | |
def __init__(self, **kwargs): | |
"""BuilderConfig for FarsTail. | |
Args: | |
**kwargs: keyword arguments forwarded to super. | |
""" | |
super(FarsTailConfig, self).__init__(**kwargs) | |
class FarsTail(datasets.GeneratorBasedBuilder): | |
BUILDER_CONFIGS = [ | |
FarsTailConfig(name="FarsTail", version=datasets.Version("1.0.0"), description="persian NLI dataset"), | |
] | |
def _info(self): | |
return datasets.DatasetInfo( | |
# This is the description that will appear on the datasets page. | |
description=_DESCRIPTION, | |
# datasets.features.FeatureConnectors | |
features=datasets.Features( | |
{ | |
"premise": datasets.Value("string"), | |
"hypothesis": datasets.Value("string"), | |
"label": datasets.Value("string") | |
} | |
), | |
supervised_keys=None, | |
# Homepage of the dataset for documentation | |
homepage="https://github.com/dml-qom/FarsTail", | |
citation=_CITATION, | |
) | |
def _split_generators(self, dl_manager): | |
"""Returns SplitGenerators.""" | |
# dl_manager is a datasets.download.DownloadManager that can be used to | |
# download and extract URLs | |
urls_to_download = _URLS | |
downloaded_files = dl_manager.download_and_extract(urls_to_download) | |
return [ | |
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}), | |
datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}), | |
datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["validation"]}), | |
] | |
def _generate_examples(self, filepath): | |
try: | |
with open(filepath, encoding="utf-8") as f: | |
reader = csv.DictReader(f, delimiter="\t") | |
for idx, row in enumerate(reader): | |
yield idx, { | |
"premise": row["premise"], | |
"hypothesis": row["hypothesis"], | |
"label": row["label"], | |
} | |
except Exception as e: | |
print(e) | |