Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
topic-classification
Languages:
English
Size:
100K - 1M
ArXiv:
License:
Commit
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Browse files- dbpedia_14.py +0 -150
dbpedia_14.py
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# coding=utf-8
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# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""The DBpedia dataset for text classification."""
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import csv
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import datasets
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# TODO: Add BibTeX citation
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# Find for instance the citation on arxiv or on the dataset repo/website
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_CITATION = """\
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@article{lehmann2015dbpedia,
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title={DBpedia--a large-scale, multilingual knowledge base extracted from Wikipedia},
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author={Lehmann, Jens and Isele, Robert and Jakob, Max and Jentzsch, Anja and Kontokostas,
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Dimitris and Mendes, Pablo N and Hellmann, Sebastian and Morsey, Mohamed and Van Kleef,
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Patrick and Auer, S{\"o}ren and others},
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journal={Semantic web},
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volume={6},
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number={2},
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pages={167--195},
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year={2015},
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publisher={IOS Press}
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}
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"""
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_DESCRIPTION = """\
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The DBpedia ontology classification dataset is constructed by picking 14 non-overlapping classes
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from DBpedia 2014. They are listed in classes.txt. From each of thse 14 ontology classes, we
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randomly choose 40,000 training samples and 5,000 testing samples. Therefore, the total size
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of the training dataset is 560,000 and testing dataset 70,000.
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There are 3 columns in the dataset (same for train and test splits), corresponding to class index
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(1 to 14), title and content. The title and content are escaped using double quotes ("), and any
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internal double quote is escaped by 2 double quotes (""). There are no new lines in title or content.
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"""
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_HOMEPAGE = "https://wiki.dbpedia.org/develop/datasets"
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_LICENSE = "Creative Commons Attribution-ShareAlike 3.0 and the GNU Free Documentation License"
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_URLs = {
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"dbpedia_14": "https://s3.amazonaws.com/fast-ai-nlp/dbpedia_csv.tgz",
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}
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class DBpedia14Config(datasets.BuilderConfig):
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"""BuilderConfig for DBpedia."""
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def __init__(self, **kwargs):
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"""BuilderConfig for DBpedia.
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Args:
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**kwargs: keyword arguments forwarded to super.
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"""
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super(DBpedia14Config, self).__init__(**kwargs)
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class DBpedia14(datasets.GeneratorBasedBuilder):
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"""DBpedia 2014 Ontology Classification Dataset."""
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VERSION = datasets.Version("2.0.0")
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BUILDER_CONFIGS = [
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DBpedia14Config(
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name="dbpedia_14", version=VERSION, description="DBpedia 2014 Ontology Classification Dataset."
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),
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]
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def _info(self):
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features = datasets.Features(
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{
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"label": datasets.features.ClassLabel(
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names=[
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"Company",
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"EducationalInstitution",
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"Artist",
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"Athlete",
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"OfficeHolder",
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"MeanOfTransportation",
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"Building",
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"NaturalPlace",
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"Village",
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"Animal",
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"Plant",
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"Album",
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"Film",
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"WrittenWork",
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]
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),
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"title": datasets.Value("string"),
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"content": datasets.Value("string"),
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}
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)
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=features,
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supervised_keys=None,
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homepage=_HOMEPAGE,
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license=_LICENSE,
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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"""Returns SplitGenerators."""
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my_urls = _URLs[self.config.name]
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archive = dl_manager.download(my_urls)
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs={
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"filepath": "dbpedia_csv/train.csv",
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"files": dl_manager.iter_archive(archive),
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},
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),
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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gen_kwargs={
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"filepath": "dbpedia_csv/test.csv",
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"files": dl_manager.iter_archive(archive),
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},
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),
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]
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def _generate_examples(self, filepath, files):
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"""Yields examples."""
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for path, f in files:
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if path == filepath:
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lines = (line.decode("utf-8") for line in f)
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data = csv.reader(lines, delimiter=",", quoting=csv.QUOTE_NONNUMERIC)
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for id_, row in enumerate(data):
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yield id_, {
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"title": row[1],
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"content": row[2],
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"label": int(row[0]) - 1,
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}
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break
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