Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
topic-classification
Languages:
German
Size:
10K - 100K
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. | |
| """Ten Thousand German News Articles Dataset""" | |
| from __future__ import absolute_import, division, print_function | |
| import csv | |
| import datasets | |
| _DESCRIPTION = """\ | |
| This dataset is intended to advance topic classification for German texts. A classifier that is efffective in | |
| English may not be effective in German dataset because it has a higher inflection and longer compound words. | |
| The 10kGNAD dataset contains 10273 German news articles from an Austrian online newspaper categorized into | |
| 9 categories. Article titles and text are concatenated together and authors are removed to avoid a keyword-like | |
| classification on authors that write frequently about one category. This dataset can be used as a benchmark | |
| for German topic classification. | |
| """ | |
| _HOMEPAGE = "https://tblock.github.io/10kGNAD/" | |
| _LICENSE = "Creative Commons Attribution-NonCommercial-ShareAlike 4.0" | |
| _TRAIN_DOWNLOAD_URL = "https://raw.githubusercontent.com/tblock/10kGNAD/master/train.csv" | |
| _TEST_DOWNLOAD_URL = "https://raw.githubusercontent.com/tblock/10kGNAD/master/test.csv" | |
| class Gnad10(datasets.GeneratorBasedBuilder): | |
| """10k German news articles for topic classification""" | |
| VERSION = datasets.Version("1.1.0") | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=datasets.Features( | |
| { | |
| "text": datasets.Value("string"), | |
| "label": datasets.features.ClassLabel( | |
| names=[ | |
| "Web", | |
| "Panorama", | |
| "International", | |
| "Wirtschaft", | |
| "Sport", | |
| "Inland", | |
| "Etat", | |
| "Wissenschaft", | |
| "Kultur", | |
| ] | |
| ), | |
| } | |
| ), | |
| homepage="https://tblock.github.io/10kGNAD/", | |
| ) | |
| def _split_generators(self, dl_manager): | |
| """Returns SplitGenerators.""" | |
| train_path = dl_manager.download_and_extract(_TRAIN_DOWNLOAD_URL) | |
| test_path = dl_manager.download_and_extract(_TEST_DOWNLOAD_URL) | |
| return [ | |
| datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_path}), | |
| datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": test_path}), | |
| ] | |
| def _generate_examples(self, filepath): | |
| """Generate German news articles examples. """ | |
| with open(filepath, encoding="utf-8") as csv_file: | |
| csv_reader = csv.reader(csv_file, delimiter=";", quotechar="'", quoting=csv.QUOTE_ALL) | |
| for id_, row in enumerate(csv_reader): | |
| label, text = row | |
| yield id_, {"text": text, "label": label} | |