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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.
"""The text2log dataset"""
import csv
import datasets
_CITATION = """\
@INPROCEEDINGS{9401852, author={Levkovskyi, Oleksii and Li, Wei}, booktitle={SoutheastCon 2021}, title={Generating Predicate Logic Expressions from Natural Language}, year={2021}, volume={}, number={}, pages={1-8}, doi={10.1109/SoutheastCon45413.2021.9401852}}
"""
_DESCRIPTION = """\
The dataset contains about 100,000 simple English sentences selected and filtered from enTenTen15 and their translation into First Order Logic (FOL) Lambda Dependency-based Compositional Semantics using ccg2lambda.
"""
_HOMEPAGE = "https://github.com/alevkov/text2log"
_LICENSE = "none provided"
_URLS = {
"csv": "https://raw.githubusercontent.com/apergo-ai/text2log/main/dat/text2log_clean.csv",
"zip": "https://raw.githubusercontent.com/apergo-ai/text2log/main/dat/text2log_clean.zip",
}
class Text2log(datasets.GeneratorBasedBuilder):
"""Simple English sentences and FOL representations using LDbCS"""
VERSION = datasets.Version("1.0.0")
def _info(self):
features = datasets.Features(
{
"sentence": datasets.Value("string"),
"fol_translation": datasets.Value("string"),
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
supervised_keys=None,
features=features,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
test_path = dl_manager.download_and_extract(_URLS["csv"])
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": test_path}),
]
def _generate_examples(self, filepath):
"""Generate text2log dataset examples."""
with open(filepath, encoding="utf-8") as csv_file:
csv_reader = csv.reader(
csv_file, quotechar='"', delimiter=";", quoting=csv.QUOTE_ALL, skipinitialspace=True
)
next(csv_reader)
for id_, row in enumerate(csv_reader):
yield id_, {
"sentence": str(row[0]),
"fol_translation": str(row[1]),
}
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