# 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""" 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}