Datasets:
text2log

	# 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]),
	}