Datasets:
Tasks:
Translation
Languages:
English
Multilinguality:
monolingual
Size Categories:
100K<n<1M
Language Creators:
machine-generated
Annotations Creators:
machine-generated
Source Datasets:
original
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. | |
"""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]), | |
} | |