Datasets:
Tasks:
Text2Text Generation
Modalities:
Text
Formats:
parquet
Sub-tasks:
text-simplification
Languages:
English
Size:
1K - 10K
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. | |
"""TURKCorpus: a dataset for sentence simplification evaluation""" | |
import datasets | |
_CITATION = """\ | |
@article{Xu-EtAl:2016:TACL, | |
author = {Wei Xu and Courtney Napoles and Ellie Pavlick and Quanze Chen and Chris Callison-Burch}, | |
title = {Optimizing Statistical Machine Translation for Text Simplification}, | |
journal = {Transactions of the Association for Computational Linguistics}, | |
volume = {4}, | |
year = {2016}, | |
url = {https://cocoxu.github.io/publications/tacl2016-smt-simplification.pdf}, | |
pages = {401--415} | |
} | |
} | |
""" | |
_DESCRIPTION = """\ | |
TURKCorpus is a dataset for evaluating sentence simplification systems that focus on lexical paraphrasing, | |
as described in "Optimizing Statistical Machine Translation for Text Simplification". The corpus is composed of 2000 validation and 359 test original sentences that were each simplified 8 times by different annotators. | |
""" | |
_HOMEPAGE = "https://github.com/cocoxu/simplification" | |
_LICENSE = "GNU General Public License v3.0" | |
_URL_LIST = [ | |
( | |
"test.8turkers.tok.norm", | |
"https://raw.githubusercontent.com/cocoxu/simplification/master/data/turkcorpus/test.8turkers.tok.norm", | |
), | |
( | |
"tune.8turkers.tok.norm", | |
"https://raw.githubusercontent.com/cocoxu/simplification/master/data/turkcorpus/tune.8turkers.tok.norm", | |
), | |
] | |
_URL_LIST += [ | |
( | |
f"{spl}.8turkers.tok.turk.{i}", | |
f"https://raw.githubusercontent.com/cocoxu/simplification/master/data/turkcorpus/{spl}.8turkers.tok.turk.{i}", | |
) | |
for spl in ["tune", "test"] | |
for i in range(8) | |
] | |
_URLs = dict(_URL_LIST) | |
class Turk(datasets.GeneratorBasedBuilder): | |
VERSION = datasets.Version("1.0.0") | |
BUILDER_CONFIGS = [ | |
datasets.BuilderConfig( | |
name="simplification", | |
version=VERSION, | |
description="A set of original sentences aligned with 8 possible simplifications for each.", | |
) | |
] | |
def _info(self): | |
features = datasets.Features( | |
{ | |
"original": datasets.Value("string"), | |
"simplifications": datasets.Sequence(datasets.Value("string")), | |
} | |
) | |
return datasets.DatasetInfo( | |
description=_DESCRIPTION, | |
features=features, | |
supervised_keys=None, | |
homepage=_HOMEPAGE, | |
license=_LICENSE, | |
citation=_CITATION, | |
) | |
def _split_generators(self, dl_manager): | |
data_dir = dl_manager.download_and_extract(_URLs) | |
return [ | |
datasets.SplitGenerator( | |
name=datasets.Split.VALIDATION, | |
gen_kwargs={ | |
"filepaths": data_dir, | |
"split": "valid", | |
}, | |
), | |
datasets.SplitGenerator( | |
name=datasets.Split.TEST, | |
gen_kwargs={"filepaths": data_dir, "split": "test"}, | |
), | |
] | |
def _generate_examples(self, filepaths, split): | |
"""Yields examples.""" | |
if split == "valid": | |
split = "tune" | |
files = [open(filepaths[f"{split}.8turkers.tok.norm"], encoding="utf-8")] + [ | |
open(filepaths[f"{split}.8turkers.tok.turk.{i}"], encoding="utf-8") for i in range(8) | |
] | |
for id_, lines in enumerate(zip(*files)): | |
yield id_, {"original": lines[0].strip(), "simplifications": [line.strip() for line in lines[1:]]} | |