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# 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.
"""WMT21 Metrics Shared Task: Segment-Level Data"""
import datasets
import csv
_CITATION = """\
@inproceedings{freitag-etal-2021-results,
title = {Results of the WMT21 Metrics Shared Task: Evaluating Metrics with Expert-based Human Evaluations on TED and News Domain},
author = {Freitag, Markus and Rei, Ricardo and Mathur, Nitika and Lo, Chi-kiu and Stewart, Craig and Foster, George and Lavie, Alon and Bojar, Ondrej}",
booktitle = {Proceedings of the Sixth Conference on Machine Translation},
month = {nov},
year = {2021},
address = {Online},
publisher = {Association for Computational Linguistics},
url = {https://aclanthology.org/2021.wmt-1.73},
pages = {733--774}
}
"""
_DESCRIPTION = """\
This shared task will examine automatic evaluation metrics for machine translation. We will
provide you with MT system outputs along with source text and the human reference translations.
We are looking for automatic metric scores for translations at the system-level, and segment-level.
We will calculate the system-level, and segment-level correlations of your scores with human judgements.
We invite submissions of reference-free metrics in addition to reference-based metrics.
"""
_HOMEPAGE = "https://www.statmt.org/wmt21/metrics-task.html"
_LICENSE = "Unknown"
_LANGUAGE_PAIRS = [('bn', 'hi'), ('hi', 'bn'), ('xh', 'zu'), ('zu', 'xh'), ('cs', 'en'), ('de', 'en'), ('de', 'fr'), ('en', 'cs'), ('en', 'de'), ('en', 'ha'),
('en', 'is'), ('en', 'ja'), ('en', 'ru'), ('en', 'zh'), ('fr', 'de'), ('ha', 'en'), ('is', 'en'), ('ja', 'en'), ('ru', 'en'), ('zh', 'en')]
_URL_BASE = "https://huggingface.co/datasets/muibk/wmt21_metrics_task/resolve/main/"
_URLs = {f"{src_lg}-{trg_lg}": f"{_URL_BASE}{src_lg}-{trg_lg}/train.csv" for src_lg, trg_lg in _LANGUAGE_PAIRS}
class WmtMetricsTaskConfig(datasets.BuilderConfig):
"""BuilderConfig for WMT Metrics Shared Task."""
def __init__(self, src_lg, tgt_lg, **kwargs):
super(WmtMetricsTaskConfig, self).__init__(**kwargs)
self.src_lg = src_lg
self.tgt_lg = tgt_lg
class Wmt21MetricsTask(datasets.GeneratorBasedBuilder):
"""WMT Metrics Shared Task."""
BUILDER_CONFIGS = [
WmtMetricsTaskConfig(
name=f"{src_lg}-{tgt_lg}",
version=datasets.Version("1.1.0"),
description=f"WMT 2021 Metrics Task: {src_lg} - {tgt_lg}",
src_lg=src_lg,
tgt_lg=tgt_lg,
)
for (src_lg, tgt_lg) in _LANGUAGE_PAIRS
]
BUILDER_CONFIG_CLASS = WmtMetricsTaskConfig
def _info(self):
# define feature types
features = datasets.Features(
{
#'source' : datasets.Value("string"),
#'system_output':datasets.Value("string"),
'translation': datasets.Translation(languages=(self.config.src_lg, self.config.tgt_lg)),
'mt_system':datasets.Value("string"),
'mqm':datasets.Value("float32"),
'wmt-raw':datasets.Value("float32"),
'wmt-z':datasets.Value("float32"),
'pair':datasets.Value("string"),
'dataset':datasets.Value("string"),
'sent_id':datasets.Value("int32"),
'doc_name':datasets.Value("string"),
'doc_ref':datasets.Value("string"),
'ref-A':datasets.Value("string"),
'ref-B':datasets.Value("string"),
'ref-C':datasets.Value("string"),
'ref-D':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):
"""Returns SplitGenerators."""
pair = f"{self.config.src_lg}-{self.config.tgt_lg}" # string identifier for language pair
url = _URLs[pair] # url for download of pair-specific train.csv
data_file = dl_manager.download_and_extract(url) # extract downloaded data and store path in data_file
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"filepath": data_file,
"source_lg": self.config.src_lg,
"target_lg": self.config.tgt_lg,
}
)
]
def _generate_examples(self, filepath, source_lg, target_lg):
with open(filepath, encoding="utf-8") as f:
reader = csv.DictReader(f, delimiter=";") # read each line into dict
for id_, row in enumerate(reader):
row["translation"] = {source_lg : row["source"], target_lg: row["system_output"]} # create translation json
for key in ["source", "system_output"]: # remove obsolete columns
row.pop(key)
row = {k: None if not v else v for k, v in row.items()} # replace empty values
yield id_, row
# to test the script, go to the root folder of the repo (wmt21_metrics_task) and run:
# datasets-cli test wmt21_metrics_task --save_infos --all_configs
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