Datasets:
Tasks:
Text Classification
Sub-tasks:
multi-class-classification
Size:
10K - 100K
ArXiv:
Tags:
causal-reasoning
License:
File size: 3,992 Bytes
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# coding=utf-8
# Copyright 2021 The HuggingFace Datasets Authors and Ilya Gusev
#
# 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.
"""HeadlineCause: A Dataset of News Headlines for Detecting Casualties"""
import json
import os
import datasets
_CITATION = """
@misc{gusev2021headlinecause,
title={HeadlineCause: A Dataset of News Headlines for Detecting Casualties},
author={Ilya Gusev and Alexey Tikhonov},
year={2021},
eprint={2108.12626},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
"""
_DESCRIPTION = "A Dataset of News Headlines for Detecting Casualties"
_HOMEPAGE = "https://github.com/IlyaGusev/HeadlineCause"
_URLS = {
"ru_simple": {
"train": "ru/simple/train.jsonl",
"val": "ru/simple/val.jsonl",
"test": "ru/simple/test.jsonl"
},
"ru_full": {
"train": "ru/full/train.jsonl",
"val": "ru/full/val.jsonl",
"test": "ru/full/test.jsonl"
},
"en_simple": {
"train": "en/simple/train.jsonl",
"val": "en/simple/val.jsonl",
"test": "en/simple/test.jsonl"
},
"en_full": {
"train": "en/full/train.jsonl",
"val": "en/full/val.jsonl",
"test": "en/full/test.jsonl",
}
}
class HeadlineCauseDataset(datasets.GeneratorBasedBuilder):
"""HeadlineCause Dataset"""
VERSION = datasets.Version("1.1.0")
BUILDER_CONFIGS = [
datasets.BuilderConfig(name="ru_simple", version=VERSION, description="Russian language, Simple task"),
datasets.BuilderConfig(name="en_simple", version=VERSION, description="English language, Simple task"),
datasets.BuilderConfig(name="ru_full", version=VERSION, description="Russian language, Full task"),
datasets.BuilderConfig(name="en_full", version=VERSION, description="English language, Full task"),
]
DEFAULT_CONFIG_NAME = "en_simple"
def _info(self):
features = datasets.Features(
{
"left_url": datasets.Value("string"),
"right_url": datasets.Value("string"),
"left_title": datasets.Value("string"),
"right_title": datasets.Value("string"),
"left_timestamp": datasets.Value("timestamp[s]"),
"right_timestamp": datasets.Value("timestamp[s]"),
"id": datasets.Value("string"),
"has_link": datasets.Value("bool"),
"label": datasets.Value("int8"),
"result": datasets.Value("string"),
"agreement": datasets.Value("double")
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
supervised_keys=None,
homepage=_HOMEPAGE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
downloaded_files = dl_manager.download_and_extract(_URLS[self.config.name])
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["val"]}),
]
def _generate_examples(self, filepath):
with open(filepath, encoding="utf-8") as f:
for row in f:
data = json.loads(row)
yield data["id"], data
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