Datasets:
Tasks:
Text Classification
Languages:
Swedish
Multilinguality:
monolingual
Size Categories:
1K<n<10K
Annotations Creators:
crowdsourced
Source Datasets:
extended|other-sts-b
ArXiv:
Tags:
License:
| # coding=utf-8 | |
| # Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors. | |
| # | |
| # 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. | |
| # Lint as: python3 | |
| import csv | |
| import os | |
| import datasets | |
| _DOWNLOAD_URL = "https://raw.githubusercontent.com/timpal0l/sts-benchmark-swedish/master/data/stsb-mt-sv.zip" | |
| _TRAIN_FILE = "train-sv.tsv" | |
| _VAL_FILE = "dev-sv.tsv" | |
| _TEST_FILE = "test-sv.tsv" | |
| _CITATION = """\ | |
| @article{isbister2020not, | |
| title={Why Not Simply Translate? A First Swedish Evaluation Benchmark for Semantic Similarity}, | |
| author={Isbister, Tim and Sahlgren, Magnus}, | |
| journal={arXiv preprint arXiv:2009.03116}, | |
| year={2020} | |
| } | |
| """ | |
| _DESCRIPTION = "Machine translated Swedish version of the original STS-B (http://ixa2.si.ehu.eus/stswiki)" | |
| class StsbMtSv(datasets.GeneratorBasedBuilder): | |
| BUILDER_CONFIGS = [ | |
| datasets.BuilderConfig( | |
| name="plain_text", | |
| version=datasets.Version("1.0.0", ""), | |
| description="Plain text import of the Swedish Machine Translated STS-B", | |
| ) | |
| ] | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=datasets.Features( | |
| { | |
| "sentence1": datasets.Value("string"), | |
| "sentence2": datasets.Value("string"), | |
| "score": datasets.Value("float"), | |
| } | |
| ), | |
| supervised_keys=None, | |
| homepage="https://github.com/timpal0l/sts-benchmark-swedish", | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| dl_dir = dl_manager.download_and_extract(_DOWNLOAD_URL) | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TEST, | |
| gen_kwargs={"filepath": os.path.join(dl_dir, _TEST_FILE)}, | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.VALIDATION, | |
| gen_kwargs={"filepath": os.path.join(dl_dir, _VAL_FILE)}, | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={"filepath": os.path.join(dl_dir, _TRAIN_FILE)}, | |
| ), | |
| ] | |
| def _generate_examples(self, filepath): | |
| """This function returns the examples in the raw (text) form.""" | |
| with open(filepath, encoding="utf-8") as f: | |
| reader = csv.DictReader(f, delimiter="\t", quoting=csv.QUOTE_NONE) | |
| for idx, row in enumerate(reader): | |
| yield idx, { | |
| "sentence1": row["sentence1"], | |
| "sentence2": row["sentence2"], | |
| "score": row["score"], | |
| } | |