# 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