Datasets:
Languages:
English
Multilinguality:
monolingual
Language Creators:
crowdsourced
Annotations Creators:
crowdsourced
Source Datasets:
original
ArXiv:
Tags:
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. | |
"""DuoRC: A Paraphrased | |
Reading Comprehension Question Answering Dataset""" | |
from __future__ import absolute_import, division, print_function | |
import json | |
import datasets | |
_CITATION = """\ | |
@inproceedings{DuoRC, | |
author = { Amrita Saha and Rahul Aralikatte and Mitesh M. Khapra and Karthik Sankaranarayanan},\ | |
title = {{DuoRC: Towards Complex Language Understanding with Paraphrased Reading Comprehension}}, | |
booktitle = {Meeting of the Association for Computational Linguistics (ACL)}, | |
year = {2018} | |
} | |
""" | |
_DESCRIPTION = """\ | |
DuoRC contains 186,089 unique question-answer pairs created from a collection of 7680 pairs of movie plots where each pair in the collection reflects two versions of the same movie. | |
""" | |
_HOMEPAGE = "https://duorc.github.io/" | |
_LICENSE = "https://raw.githubusercontent.com/duorc/duorc/master/LICENSE" | |
_URL = "https://raw.githubusercontent.com/duorc/duorc/master/dataset/" | |
_URLs = { | |
"SelfRC": { | |
"train": _URL + "SelfRC_train.json", | |
"dev": _URL + "SelfRC_dev.json", | |
"test": _URL + "SelfRC_test.json", | |
}, | |
"ParaphraseRC": { | |
"train": _URL + "ParaphraseRC_train.json", | |
"dev": _URL + "ParaphraseRC_dev.json", | |
"test": _URL + "ParaphraseRC_test.json", | |
}, | |
} | |
class DuorcConfig(datasets.BuilderConfig): | |
"""BuilderConfig for DuoRC SelfRC.""" | |
def __init__(self, **kwargs): | |
"""BuilderConfig for DuoRC SelfRC. | |
Args: | |
**kwargs: keyword arguments forwarded to super. | |
""" | |
super(DuorcConfig, self).__init__(**kwargs) | |
class Duorc(datasets.GeneratorBasedBuilder): | |
"""DuoRC Dataset""" | |
VERSION = datasets.Version("1.0.0") | |
BUILDER_CONFIGS = [ | |
DuorcConfig(name="SelfRC", version=VERSION, description="SelfRC dataset"), | |
DuorcConfig(name="ParaphraseRC", version=VERSION, description="ParaphraseRC dataset"), | |
] | |
def _info(self): | |
return datasets.DatasetInfo( | |
# This is the description that will appear on the datasets page. | |
description=_DESCRIPTION, | |
# This defines the different columns of the dataset and their types | |
features=datasets.Features( | |
{ | |
"plot_id": datasets.Value("string"), | |
"plot": datasets.Value("string"), | |
"title": datasets.Value("string"), | |
"question_id": datasets.Value("string"), | |
"question": datasets.Value("string"), | |
"answers": datasets.features.Sequence(datasets.Value("string")), | |
"no_answer": datasets.Value("bool"), | |
} | |
), | |
supervised_keys=None, | |
homepage=_HOMEPAGE, | |
license=_LICENSE, | |
citation=_CITATION, | |
) | |
def _split_generators(self, dl_manager): | |
"""Returns SplitGenerators.""" | |
my_urls = _URLs[self.config.name] | |
downloaded_files = dl_manager.download_and_extract(my_urls) | |
return [ | |
datasets.SplitGenerator( | |
name=datasets.Split.TRAIN, | |
gen_kwargs={ | |
"filepath": downloaded_files["train"], | |
}, | |
), | |
datasets.SplitGenerator( | |
name=datasets.Split.VALIDATION, | |
gen_kwargs={ | |
"filepath": downloaded_files["dev"], | |
}, | |
), | |
datasets.SplitGenerator( | |
name=datasets.Split.TEST, | |
gen_kwargs={ | |
"filepath": downloaded_files["test"], | |
}, | |
), | |
] | |
def _generate_examples(self, filepath): | |
"""This function returns the examples in the raw (text) form.""" | |
with open(filepath, encoding="utf-8") as f: | |
duorc = json.load(f) | |
for example in duorc: | |
plot_id = example["id"] | |
plot = example["plot"].strip() | |
title = example["title"].strip() | |
for qas in example["qa"]: | |
question_id = qas["id"] | |
question = qas["question"].strip() | |
answers = [answer.strip() for answer in qas["answers"]] | |
no_answer = qas["no_answer"] | |
yield question_id, { | |
"title": title, | |
"plot": plot, | |
"question": question, | |
"plot_id": plot_id, | |
"question_id": question_id, | |
"answers": answers, | |
"no_answer": no_answer, | |
} | |