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# 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.
"""Story Cloze datasets."""
import csv
import os
import datasets
_DESCRIPTION = """
Story Cloze Test' is a commonsense reasoning framework for evaluating story understanding,
story generation, and script learning.This test requires a system to choose the correct ending
to a four-sentence story.
"""
_CITATION = """\
@inproceedings{mostafazadeh2017lsdsem,
title={Lsdsem 2017 shared task: The story cloze test},
author={Mostafazadeh, Nasrin and Roth, Michael and Louis, Annie and Chambers, Nathanael and Allen, James},
booktitle={Proceedings of the 2nd Workshop on Linking Models of Lexical, Sentential and Discourse-level Semantics},
pages={46--51},
year={2017}
}
"""
class StoryCloze(datasets.GeneratorBasedBuilder):
"""Story Cloze."""
BUILDER_CONFIGS = [
datasets.BuilderConfig(name="2016", description="Story Cloze Test Spring 2016 set"),
datasets.BuilderConfig(name="2018", description="Story Cloze Test Winter 2018 set"),
]
@property
def manual_download_instructions(self):
return (
"To use Story Cloze you have to download it manually. Please fill this "
"google form (http://goo.gl/forms/aQz39sdDrO). Complete the form. "
"Then you will receive a download link for the dataset. Load it using: "
"`datasets.load_dataset('story_cloze', data_dir='path/to/folder/folder_name')`"
)
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"story_id": datasets.Value("string"),
"input_sentence_1": datasets.Value("string"),
"input_sentence_2": datasets.Value("string"),
"input_sentence_3": datasets.Value("string"),
"input_sentence_4": datasets.Value("string"),
"sentence_quiz1": datasets.Value("string"),
"sentence_quiz2": datasets.Value("string"),
"answer_right_ending": datasets.Value("int32"),
}
),
homepage="https://cs.rochester.edu/nlp/rocstories/",
citation=_CITATION,
)
def _split_generators(self, dl_manager):
path_to_manual_folder = os.path.abspath(os.path.expanduser(dl_manager.manual_dir))
if self.config.name == "2016":
test_file = os.path.join(path_to_manual_folder, "cloze_test_test__spring2016 - cloze_test_ALL_test.csv")
val_file = os.path.join(path_to_manual_folder, "cloze_test_val__spring2016 - cloze_test_ALL_val.csv")
return [
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={
"filepath": val_file,
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"filepath": test_file,
},
),
]
else:
val_file = os.path.join(path_to_manual_folder, "cloze_test_val__winter2018-cloze_test_ALL_val - 1 - 1.csv")
return [
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={
"filepath": val_file,
},
),
]
def _generate_examples(self, filepath):
"""Generate Story Cloze examples."""
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 row and len(row) == 8:
yield id_, {
"story_id": row[0],
"input_sentence_1": row[1],
"input_sentence_2": row[2],
"input_sentence_3": row[3],
"input_sentence_4": row[4],
"sentence_quiz1": row[5],
"sentence_quiz2": row[6],
"answer_right_ending": int(row[7]),
}
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