Datasets:
Tasks:
Translation
Languages:
English
Size Categories:
1K<n<10K
Annotations Creators:
no-annotation
Source Datasets:
extended|other-newstest2017
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. | |
"""Microsoft Research: Translator Human Parity Data""" | |
import os | |
import datasets | |
_DESCRIPTION = """\ | |
Translator Human Parity Data | |
Human evaluation results and translation output for the Translator Human Parity Data release, | |
as described in https://blogs.microsoft.com/ai/machine-translation-news-test-set-human-parity/. | |
The Translator Human Parity Data release contains all human evaluation results and translations | |
related to our paper "Achieving Human Parity on Automatic Chinese to English News Translation", | |
published on March 14, 2018. | |
""" | |
_LICENSE = """\ | |
See the Microsoft Research Data License Agreement. | |
""" | |
_CITATION = """\ | |
@misc{hassan2018achieving, | |
title={Achieving Human Parity on Automatic Chinese to English News Translation}, | |
author={ Hany Hassan and Anthony Aue and Chang Chen and Vishal Chowdhary and Jonathan Clark | |
and Christian Federmann and Xuedong Huang and Marcin Junczys-Dowmunt and William Lewis | |
and Mu Li and Shujie Liu and Tie-Yan Liu and Renqian Luo and Arul Menezes and Tao Qin | |
and Frank Seide and Xu Tan and Fei Tian and Lijun Wu and Shuangzhi Wu and Yingce Xia | |
and Dongdong Zhang and Zhirui Zhang and Ming Zhou}, | |
year={2018}, | |
eprint={1803.05567}, | |
archivePrefix={arXiv}, | |
primaryClass={cs.CL} | |
}""" | |
_FILE_PATHS = [ | |
["References", "Translator-HumanParityData-Reference-HT.txt"], | |
["References", "Translator-HumanParityData-Reference-PE.txt"], | |
["Translations", "Translator-HumanParityData-Combo-4.txt"], | |
["Translations", "Translator-HumanParityData-Combo-5.txt"], | |
["Translations", "Translator-HumanParityData-Combo-6.txt"], | |
["Translations", "Translator-HumanParityData-Online-A-1710.txt"], | |
] | |
_FEATURE_NAMES = ["Reference-HT", "Reference-PE", "Combo-4", "Combo-5", "Combo-6", "Online-A-1710"] | |
class MsrZhenTranslationParity(datasets.GeneratorBasedBuilder): | |
"""Microsoft Research: Translator Human Parity Data""" | |
VERSION = datasets.Version("1.0.0") | |
def manual_download_instructions(self): | |
return """\ | |
You need to go to https://msropendata.com/datasets/93f9aa87-9491-45ac-81c1-6498b6be0d0b, | |
and manually download translatorhumanparitydata2.zip (or translatorhumanparitydata2.tar.gz). | |
Once it is completed, extract its content into a directory, <path/to/folder>. | |
Within this directory, there are three subdirectories, Translations, References, and Evaluations. | |
The <path/to/folder> can e.g. be "~/Downloads/translatorhumanparitydata2", if you just double click the .zip file. | |
msr_zhen_translation_parity can then be loaded using the following command | |
`datasets.load_dataset("msr_zhen_translation_parity", data_dir="<path/to/folder>")`. | |
""" | |
def _info(self): | |
feature_names = _FEATURE_NAMES | |
return datasets.DatasetInfo( | |
description=_DESCRIPTION, | |
features=datasets.Features({k: datasets.Value("string") for k in feature_names}), | |
supervised_keys=None, | |
homepage="https://msropendata.com/datasets/93f9aa87-9491-45ac-81c1-6498b6be0d0b", | |
citation=_CITATION, | |
) | |
def _split_generators(self, dl_manager): | |
"""Returns SplitGenerators.""" | |
path_to_manual_file = os.path.abspath(os.path.expanduser(dl_manager.manual_dir)) | |
if not os.path.exists(path_to_manual_file): | |
raise FileNotFoundError( | |
f"{path_to_manual_file} does not exist. Make sure you insert a manual dir via `datasets.load_dataset('msr_zhen_translation_parity', data_dir=...)`. Manual download instructions: {self.manual_download_instructions})" | |
) | |
return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"path": path_to_manual_file})] | |
def _generate_examples(self, path=None, title_set=None): | |
data = [] | |
for fp in _FILE_PATHS: | |
filepath = os.path.join(path, fp[0], fp[1]) | |
with open(filepath, encoding="utf-8-sig") as f: | |
data.append(f.readlines()) | |
examples = len(data[0]) | |
for i in range(examples): | |
record = [x[i].rstrip("\r\n") for x in data] | |
yield i, dict(zip(_FEATURE_NAMES, record)) | |