Datasets:
Languages:
Czech
Multilinguality:
monolingual
Size Categories:
1K<n<10K
Annotations Creators:
found
Source Datasets:
extended|other-san-francisco-restaurants
ArXiv:
License:
File size: 3,804 Bytes
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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.
"""Czech restaurant information dataset for NLG"""
import json
import datasets
# Find for instance the citation on arxiv or on the dataset repo/website
_CITATION = """\
@article{DBLP:journals/corr/abs-1910-05298,
author = {Ondrej Dusek and
Filip Jurcicek},
title = {Neural Generation for Czech: Data and Baselines},
journal = {CoRR},
volume = {abs/1910.05298},
year = {2019},
url = {http://arxiv.org/abs/1910.05298},
archivePrefix = {arXiv},
eprint = {1910.05298},
timestamp = {Wed, 16 Oct 2019 16:25:53 +0200},
biburl = {https://dblp.org/rec/journals/corr/abs-1910-05298.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
"""
_DESCRIPTION = """\
This is a dataset for NLG in task-oriented spoken dialogue systems with Czech as the target language. It originated as
a translation of the English San Francisco Restaurants dataset by Wen et al. (2015).
"""
_LICENSE = "Creative Commons 4.0 BY-SA"
_URLs = {
"CSRestaurants": "https://raw.githubusercontent.com/UFAL-DSG/cs_restaurant_dataset/master/",
}
class CSRestaurants(datasets.GeneratorBasedBuilder):
"""Czech restaurant information dataset for NLG"""
VERSION = datasets.Version("1.0.0")
BUILDER_CONFIGS = [datasets.BuilderConfig(name="CSRestaurants", description="NLG data for Czech")]
DEFAULT_CONFIG_NAME = "CSRestaurants"
def _info(self):
features = datasets.Features(
{
"da": datasets.Value("string"),
"delex_da": datasets.Value("string"),
"text": datasets.Value("string"),
"delex_text": datasets.Value("string"),
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
supervised_keys=None,
homepage="https://github.com/UFAL-DSG/cs_restaurant_dataset",
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
master_url = _URLs[self.config.name]
train_path = dl_manager.download_and_extract(master_url + "train.json")
valid_path = dl_manager.download_and_extract(master_url + "devel.json")
test_path = dl_manager.download_and_extract(master_url + "test.json")
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_path}),
datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": valid_path}),
datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": test_path}),
]
def _generate_examples(self, filepath):
"""Yields examples."""
with open(filepath, encoding="utf8") as f:
data = json.load(f)
for id_, instance in enumerate(data):
yield id_, {
"da": instance["da"],
"delex_da": instance["delex_da"],
"text": instance["text"],
"delex_text": instance["delex_text"],
}
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