Datasets:
Tasks:
Text Classification
Sub-tasks:
sentiment-analysis
Languages:
Danish
Size:
n<1K
Tags:
stance-detection
License:
File size: 3,834 Bytes
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# coding=utf-8
# Copyright 2020 HuggingFace Datasets Authors.
#
# 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.
# Lint as: python3
"""Political Stance in Danish"""
import csv
import os
import datasets
logger = datasets.logging.get_logger(__name__)
_CITATION = """\
@inproceedings{lehmann2019political,
title={Political Stance in Danish},
author={Lehmann, Rasmus and Derczynski, Leon},
booktitle={Proceedings of the 22nd Nordic Conference on Computational Linguistics},
pages={197--207},
year={2019}
}
"""
_DESCRIPTION = """\
Political stance in Danish. Examples represent statements by
politicians and are annotated for, against, or neutral to a given topic/article.
"""
_URL = "https://raw.githubusercontent.com/StrombergNLP/Political-Stance-in-Danish/master/Scraper/resources/parsedQuotes/quote_db.csv"
class PolStanceConfig(datasets.BuilderConfig):
"""BuilderConfig for PolStance"""
def __init__(self, **kwargs):
"""BuilderConfig PolStance.
Args:
**kwargs: keyword arguments forwarded to super.
"""
super(PolStanceConfig, self).__init__(**kwargs)
class PolStance(datasets.GeneratorBasedBuilder):
"""PolStance dataset."""
BUILDER_CONFIGS = [
PolStanceConfig(name="PolStance", version=datasets.Version("1.0.0"), description="Political Stance in Danish"),
]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
# quoteID;party;politician;date;quote;falsePositive;subTopic;fan;articleID;topic
{
"id": datasets.Value("string"),
"topic": datasets.Value("string"),
"quote": datasets.Value("string"),
"label": datasets.features.ClassLabel(
names=["a", "n", "f"]
),
"quoteID": datasets.Value("string"),
"party": datasets.Value("string"),
"politician": datasets.Value("string"),
"quoteID": datasets.Value("string"),
}
),
supervised_keys=None,
homepage="https://stromberg.ai/publication/politicalstanceindanish/",
citation=_CITATION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
downloaded_file = dl_manager.download_and_extract(_URL)
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_file}),
]
def _generate_examples(self, filepath):
logger.info("⏳ Generating examples from = %s", filepath)
with open(filepath, encoding="utf-16") as f:
PolStance_reader = csv.DictReader(f, delimiter=";", quotechar='"')
guid = 0
for instance in PolStance_reader:
if not instance["fan"]:
continue
instance["topic"] = instance["topic"].rstrip()
instance["id"] = str(guid)
instance["label"] = instance.pop("fan")
for dropfield in ('falsePositive', 'subTopic', 'date', 'articleID'):
instance.pop(dropfield)
yield guid, instance
guid += 1
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