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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.
"""BiSECT is a Split and Rephrase corpus created via bilingual pivoting."""
import os
import datasets
_CITATION = """\
@inproceedings{kim-etal-2021-bisect,
title = "{B}i{SECT}: Learning to Split and Rephrase Sentences with Bitexts",
author = "Kim, Joongwon and
Maddela, Mounica and
Kriz, Reno and
Xu, Wei and
Callison-Burch, Chris",
booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing",
month = nov,
year = "2021",
address = "Online and Punta Cana, Dominican Republic",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.emnlp-main.500",
pages = "6193--6209"
}
"""
_DESCRIPTION = """\
BiSECT is a Split and Rephrase corpus created via bilingual pivoting.
"""
_HOMEPAGE = "https://github.com/mounicam/BiSECT"
_URL = "https://raw.githubusercontent.com/mounicam/BiSECT/main/"
_URL_MAIN = _URL + "bisect/"
_URL_CHALLENGE = _URL + "bisect_challenge/"
_URLs = {
datasets.Split.TRAIN: {
"src": _URL_MAIN + "train.src.gz",
"dst": _URL_MAIN + "train.dst.gz",
},
datasets.Split.VALIDATION: {
"src": _URL_MAIN + "valid.src.gz",
"dst": _URL_MAIN + "valid.dst.gz",
},
datasets.Split.TEST: {
"src": _URL_MAIN + "test.src.gz",
"dst": _URL_MAIN + "test.dst.gz",
},
"challenge_hsplit": {
"src": "https://raw.githubusercontent.com/cocoxu/simplification/master/data/turkcorpus/test.8turkers.tok.norm",
"dst": "https://raw.githubusercontent.com/eliorsulem/HSplit-corpus/master/HSplit/HSplit2_full",
},
"challenge_bisect": {
"src": _URL_CHALLENGE + "challenge_test.src",
"dst": _URL_CHALLENGE + "challenge_test.dst",
},
}
class BiSECT(datasets.GeneratorBasedBuilder):
"""The BiSECT Split and Rephrase corpus."""
VERSION = datasets.Version("1.1.0")
BUILDER_CONFIGS = [
datasets.BuilderConfig(
name="en",
version=VERSION,
description="English data described in the BiSECT paper",
),
datasets.BuilderConfig(
name="de",
version=VERSION,
description="German data described in the BiSECT paper",
),
datasets.BuilderConfig(
name="es",
version=VERSION,
description="Spanish data described in the BiSECT paper",
),
datasets.BuilderConfig(
name="fr",
version=VERSION,
description="French data described in the BiSECT paper",
),
]
DEFAULT_CONFIG_NAME = "en"
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"gem_id": datasets.Value("string"),
"source": datasets.Value("string"),
"target": datasets.Value("string"),
"references": [datasets.Value("string")],
}
),
supervised_keys=None,
homepage=_HOMEPAGE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
if self.config.name == "en":
data_dir = dl_manager.download_and_extract(_URLs)
return [
datasets.SplitGenerator(
name=split_name,
gen_kwargs={"filepath": data_dir[split_name], "split": split_name},
)
for split_name in data_dir
]
else:
lang = self.config.name
url = _URL + "bisect_multilingual/" + f"bisect_{lang}.gz"
data_dir = dl_manager.download_and_extract(url)
return [
datasets.SplitGenerator(
name=f"{split}",
gen_kwargs={
"filepath": os.path.join(data_dir, lang),
"split": split,
},
)
for split in (
datasets.Split.TRAIN,
datasets.Split.VALIDATION,
datasets.Split.TEST,
)
]
def _generate_examples(self, filepath, split):
"""Yields examples as (key, example) tuples."""
if self.config.name == "en":
source_filepath = filepath["src"]
target_filepath = filepath["dst"]
else:
source_filepath = os.path.join(filepath, f"{split}.complex")
target_filepath = os.path.join(filepath, f"{split}.simple")
with open(source_filepath, encoding="utf-8") as f:
source_lines = [line.strip() for line in f if line.strip()]
with open(target_filepath, encoding="utf-8") as f:
target_lines = [
line.strip().replace(" <SEP>", "") for line in f if line.strip()
]
for id_ in range(len(source_lines)):
yield id_, {
"gem_id": f"BiSECT_{self.config.name}-{split}-{id_}",
"source": source_lines[id_],
"target": target_lines[id_],
"references": [target_lines[id_]],
}
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