Datasets:
Tasks:
Text Classification
Sub-tasks:
fact-checking
Languages:
Arabic
Multilinguality:
monolingual
Size Categories:
1K<n<10K
Language Creators:
found
Annotations Creators:
crowdsourced
Source Datasets:
original
ArXiv:
License:
File size: 3,711 Bytes
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# Copyright 2022 Mads Kongsbak and Leon Derczynski
#
# 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.
"""A DataLoader for the AraStance dataset."""
import csv
import json
import os
import datasets
_CITATION = """\
@article{arastance,
url = {https://arxiv.org/abs/2104.13559},
author = {Alhindi, Tariq and Alabdulkarim, Amal and Alshehri, Ali and Abdul-Mageed, Muhammad and Nakov, Preslav},
title = {AraStance: A Multi-Country and Multi-Domain Dataset of Arabic Stance Detection for Fact Checking},
year = {2021},
copyright = {Creative Commons Attribution 4.0 International}
}
"""
_DESCRIPTION = """\
The AraStance dataset contains true and false claims, where each claim is paired with one or more documents. Each claim–article pair has a stance label: agree, disagree, discuss, or unrelated.
"""
_HOMEPAGE = "https://github.com/Tariq60/arastance"
_LICENSE = "cc-by-4.0"
class ARAStanceConfig(datasets.BuilderConfig):
def __init__(self, **kwargs):
super(ARAStanceConfig, self).__init__(**kwargs)
class ARAStance(datasets.GeneratorBasedBuilder):
"""The AraStance dataset made in triples of (claim, article, stance)"""
VERSION = datasets.Version("1.0.0")
BUILDER_CONFIGS = [
ARAStanceConfig(name="stance", version=VERSION, description=""),
]
def _info(self):
features = datasets.Features(
{
"id": datasets.Value("string"),
"claim": datasets.Value("string"),
"article": datasets.Value("string"),
"stance": datasets.features.ClassLabel(
names=[
"Agree",
"Disagree",
"Discuss",
"Unrelated",
]
)
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
train_text = dl_manager.download_and_extract("arastance_train.csv")
valid_text = dl_manager.download_and_extract("arastance_valid.csv")
test_text = dl_manager.download_and_extract("arastance_test.csv")
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_text, "split": "train"}),
datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": valid_text, "split": "validation"}),
datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": test_text, "split": "test"}),
]
def _generate_examples(self, filepath, split):
with open(filepath, encoding="utf-8") as f:
reader = csv.DictReader(f, delimiter=",")
guid = 0
for instance in reader:
instance["claim"] = instance.pop("claim")
instance["article"] = instance.pop("article")
instance["stance"] = instance.pop("stance")
instance['id'] = str(guid)
yield guid, instance
guid += 1 |