Datasets:
File size: 3,975 Bytes
7fd1d70 5bb6fd3 7fd1d70 a802c73 7fd1d70 a802c73 5bb6fd3 a802c73 7fd1d70 a802c73 7fd1d70 a802c73 7fd1d70 a802c73 7fd1d70 a802c73 7fd1d70 a802c73 7fd1d70 a802c73 7fd1d70 a802c73 7fd1d70 a802c73 7fd1d70 a802c73 7fd1d70 a802c73 7fd1d70 a802c73 7fd1d70 a802c73 7fd1d70 a802c73 7fd1d70 a802c73 7fd1d70 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 |
# 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
"""Stance prediction for Russian: data and analysis"""
import csv
import os
import datasets
logger = datasets.logging.get_logger(__name__)
_CITATION = """\
@inproceedings{lozhnikov2018stance,
title={Stance prediction for Russian: data and analysis},
author={Lozhnikov, Nikita and Derczynski, Leon and Mazzara, Manuel},
booktitle={International Conference in Software Engineering for Defence Applications},
pages={176--186},
year={2018},
organization={Springer}
}
"""
_DESCRIPTION = """\
This is a stance prediction dataset in Russian. The dataset contains comments on news articles,
and rows are a comment, the title of the news article it responds to, and the stance of the comment
towards the article.
"""
_URL = "rustance_dataset.csv"
class RuStanceConfig(datasets.BuilderConfig):
"""BuilderConfig for RuStance"""
def __init__(self, **kwargs):
"""BuilderConfig RuStance.
Args:
**kwargs: keyword arguments forwarded to super.
"""
super(RuStanceConfig, self).__init__(**kwargs)
class RuStance(datasets.GeneratorBasedBuilder):
"""RuStance dataset."""
BUILDER_CONFIGS = [
RuStanceConfig(name="rustance", version=datasets.Version("1.0.0"), description="Stance dataset in Russian"),
]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"id": datasets.Value("string"),
"text": datasets.Value("string"),
"title": datasets.Value("string"),
"stance": datasets.features.ClassLabel(
names=[
"support",
"deny",
"query",
"comment",
]
)
}
),
supervised_keys=None,
homepage="https://link.springer.com/chapter/10.1007/978-3-030-14687-0_16",
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-8") as f:
rustance_reader = csv.DictReader(f, delimiter=";", quotechar='"')
guid = 0
for instance in rustance_reader:
instance["id"] = str(guid)
if instance['Stance'] == "s":
instance['Stance'] = "support"
elif instance['Stance'] == "d":
instance['Stance'] = "deny"
elif instance['Stance'] == "q":
instance['Stance'] = "query"
elif instance['Stance'] == "c":
instance['Stance'] = "comment"
instance["text"] = instance.pop("Text")
instance["title"] = instance.pop("Title")
instance["stance"] = instance.pop("Stance")
yield guid, instance
guid += 1
|