Datasets:
Tasks:
Text Classification
Sub-tasks:
text-scoring
Languages:
English
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Language Creators:
crowdsourced
Source Datasets:
original
License:
# coding=utf-8 | |
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor. | |
# | |
# 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. | |
"""This is humorous headline dataset called Humicroedit introduced in the Task-7 of SemEval 2020.""" | |
import csv | |
import os | |
import datasets | |
_CITATION = """\ | |
@article{hossain2019president, | |
title={" President Vows to Cut< Taxes> Hair": Dataset and Analysis of Creative Text Editing for Humorous Headlines}, | |
author={Hossain, Nabil and Krumm, John and Gamon, Michael}, | |
journal={arXiv preprint arXiv:1906.00274}, | |
year={2019} | |
} | |
""" | |
_DESCRIPTION = """\ | |
This new dataset is designed to assess the funniness of edited news headlines. | |
""" | |
_HOMEPAGE = "https://www.cs.rochester.edu/u/nhossain/humicroedit.html" | |
_LICENSE = "" | |
_URL = "https://cs.rochester.edu/u/nhossain/semeval-2020-task-7-dataset.zip" | |
class Humicroedit(datasets.GeneratorBasedBuilder): | |
"""This is humorous headline dataset called Humicroedit introduced in the Task-7 of SemEval 2020.""" | |
VERSION = datasets.Version("1.1.0") | |
# This is an example of a dataset with multiple configurations. | |
# If you don't want/need to define several sub-sets in your dataset, | |
# just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes. | |
# If you need to make complex sub-parts in the datasets with configurable options | |
# You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig | |
# BUILDER_CONFIG_CLASS = MyBuilderConfig | |
# You will be able to load one or the other configurations in the following list with | |
# data = datasets.load_dataset('my_dataset', 'first_domain') | |
# data = datasets.load_dataset('my_dataset', 'second_domain') | |
BUILDER_CONFIGS = [ | |
datasets.BuilderConfig(name="subtask-1", description="This part of the dataset covers the data for subtask-1"), | |
datasets.BuilderConfig(name="subtask-2", description="This part of the dataset covers the data for subtask-2"), | |
] | |
def _info(self): | |
if self.config.name == "subtask-1": | |
features = datasets.Features( | |
{ | |
"id": datasets.Value("string"), | |
"original": datasets.Value("string"), | |
"edit": datasets.Value("string"), | |
"grades": datasets.Value("string"), | |
"meanGrade": datasets.Value("float"), | |
# These are the features of your dataset like images, labels ... | |
} | |
) | |
else: | |
features = datasets.Features( | |
{ | |
"id": datasets.Value("string"), | |
"original1": datasets.Value("string"), | |
"edit1": datasets.Value("string"), | |
"grades1": datasets.Value("string"), | |
"meanGrade1": datasets.Value("float"), | |
"original2": datasets.Value("string"), | |
"edit2": datasets.Value("string"), | |
"grades2": datasets.Value("string"), | |
"meanGrade2": datasets.Value("float"), | |
"label": datasets.ClassLabel(names=["equal", "sentence1", "sentence2"]), | |
} | |
) | |
return datasets.DatasetInfo( | |
description=_DESCRIPTION, | |
features=features, | |
supervised_keys=None, | |
homepage=_HOMEPAGE, | |
license=_LICENSE, | |
citation=_CITATION, | |
) | |
def _split_generators(self, dl_manager): | |
"""Returns SplitGenerators.""" | |
data_dir = dl_manager.download_and_extract(_URL) | |
ROOT = "semeval-2020-task-7-dataset" | |
return [ | |
datasets.SplitGenerator( | |
name=datasets.Split.TRAIN, | |
# These kwargs will be passed to _generate_examples | |
gen_kwargs={ | |
"filepath": os.path.join(data_dir, ROOT, self.config.name, "train.csv"), | |
"split": "train", | |
}, | |
), | |
datasets.SplitGenerator( | |
name=datasets.Split.TEST, | |
# These kwargs will be passed to _generate_examples | |
gen_kwargs={"filepath": os.path.join(data_dir, ROOT, self.config.name, "test.csv"), "split": "test"}, | |
), | |
datasets.SplitGenerator( | |
name=datasets.Split.VALIDATION, | |
# These kwargs will be passed to _generate_examples | |
gen_kwargs={ | |
"filepath": os.path.join(data_dir, ROOT, self.config.name, "dev.csv"), | |
"split": "dev", | |
}, | |
), | |
datasets.SplitGenerator( | |
name=datasets.Split("funlines"), | |
# These kwargs will be passed to _generate_examples | |
gen_kwargs={ | |
"filepath": os.path.join(data_dir, ROOT, self.config.name, "train_funlines.csv"), | |
"split": "funlines", | |
}, | |
), | |
] | |
def _generate_examples(self, filepath, split): | |
"""Yields examples.""" | |
label_names = ["equal", "sentence1", "sentence2"] | |
with open(filepath, encoding="utf-8") as csv_file: | |
csv_reader = csv.reader( | |
csv_file, quotechar='"', delimiter=",", quoting=csv.QUOTE_ALL, skipinitialspace=True | |
) | |
next(csv_reader) | |
for id_, row in enumerate(csv_reader): | |
if self.config.name == "subtask-1": | |
row_id, original, edit, grades, meanGrade = row | |
yield id_, { | |
"id": row_id, | |
"original": original, | |
"edit": edit, | |
"grades": grades, | |
"meanGrade": meanGrade, | |
} | |
else: | |
row_id, original1, edit1, grades1, meanGrade1, original2, edit2, grades2, meanGrade2, label = row | |
yield id_, { | |
"id": row_id, | |
"original1": original1, | |
"edit1": edit1, | |
"grades1": grades1, | |
"meanGrade1": meanGrade1, | |
"original2": original2, | |
"edit2": edit2, | |
"grades2": grades2, | |
"meanGrade2": meanGrade2, | |
"label": label_names[int(label)], | |
} | |