Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
json
Sub-tasks:
multi-class-classification
Languages:
Catalan
Size:
100K - 1M
License:
# Loading script for the TeCla dataset. | |
import json | |
import datasets | |
logger = datasets.logging.get_logger(__name__) | |
_CITATION = """ | |
Baucells, Irene, Carrino, Casimiro Pio, Rodriguez-Penagos, Carlos Gerardo, & Armentano-Oller, Carme. (2021). | |
TeCla: Text Classification Catalan dataset (Version 2.0) [Data set]. | |
Zenodo. http://doi.org/10.5281/zenodo.7334110 | |
""" | |
_DESCRIPTION = """ | |
TeCla: Text Classification Catalan dataset | |
Catalan News corpus for Text classification, crawled from ACN (Catalan News Agency) site: www.acn.cat | |
Corpus de notícies en català per a classificació textual, extret del web de l'Agència Catalana de Notícies - www.acn.cat | |
""" | |
_HOMEPAGE = """https://zenodo.org/record/4761505""" | |
# TODO: upload datasets to github | |
_URL = "./" | |
_TRAINING_FILE = "train.json" | |
_DEV_FILE = "dev.json" | |
_TEST_FILE = "test.json" | |
class teclaConfig(datasets.BuilderConfig): | |
""" Builder config for the TeCla dataset """ | |
def __init__(self, **kwargs): | |
"""BuilderConfig for TeCla. | |
Args: | |
**kwargs: keyword arguments forwarded to super. | |
""" | |
super(teclaConfig, self).__init__(**kwargs) | |
class tecla(datasets.GeneratorBasedBuilder): | |
""" TeCla Dataset """ | |
BUILDER_CONFIGS = [ | |
teclaConfig( | |
name="tecla", | |
version=datasets.Version("1.0.1"), | |
description="tecla 2.0 dataset", | |
), | |
] | |
def _info(self): | |
return datasets.DatasetInfo( | |
description=_DESCRIPTION, | |
features=datasets.Features( | |
{ | |
"text": datasets.Value("string"), | |
"label1": datasets.features.ClassLabel | |
(names= | |
[ | |
"Societat", | |
"Pol\u00edtica", | |
"Economia", | |
"Cultura", | |
] | |
), | |
"label2": datasets.features.ClassLabel | |
(names= | |
[ | |
"Llengua", | |
"Infraestructures", | |
"Arts", | |
"Parlament", | |
"Noves tecnologies", | |
"Castells", | |
"Successos", | |
"Empresa", | |
"Mobilitat", | |
"Teatre", | |
"Treball", | |
"Log\u00edstica", | |
"Urbanisme", | |
"Govern", | |
"Entitats", | |
"Finances", | |
"Govern espanyol", | |
"Tr\u00e0nsit", | |
"Ind\u00fastria", | |
"Esports", | |
"Exteriors", | |
"Medi ambient", | |
"Habitatge", | |
"Salut", | |
"Equipaments i patrimoni", | |
"Recerca", | |
"Cooperaci\u00f3", | |
"Innovaci\u00f3", | |
"Agroalimentaci\u00f3", | |
"Policial", | |
"Serveis Socials", | |
"Cinema", | |
"Mem\u00f2ria hist\u00f2rica", | |
"Turisme", | |
"Pol\u00edtica municipal", | |
"Comer\u00e7", | |
"Universitats", | |
"Hisenda", | |
"Judicial", | |
"Partits", | |
"M\u00fasica", | |
"Lletres", | |
"Religi\u00f3", | |
"Festa i cultura popular", | |
"Uni\u00f3 Europea", | |
"Moda", | |
"Moviments socials", | |
"Comptes p\u00fablics", | |
"Immigraci\u00f3", | |
"Educaci\u00f3", | |
"Gastronomia", | |
"Meteorologia", | |
"Energia" | |
] | |
), | |
} | |
), | |
homepage=_HOMEPAGE, | |
citation=_CITATION, | |
) | |
def _split_generators(self, dl_manager): | |
"""Returns SplitGenerators.""" | |
urls_to_download = { | |
"train": f"{_URL}{_TRAINING_FILE}", | |
"dev": f"{_URL}{_DEV_FILE}", | |
"test": f"{_URL}{_TEST_FILE}", | |
} | |
downloaded_files = dl_manager.download_and_extract(urls_to_download) | |
return [ | |
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}), | |
datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}), | |
datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}), | |
] | |
def _generate_examples(self, filepath): | |
"""This function returns the examples in the raw (text) form.""" | |
logger.info("generating examples from = %s", filepath) | |
with open(filepath, encoding="utf-8") as f: | |
acn_ca = json.load(f) | |
for id_, article in enumerate(acn_ca["data"]): | |
text = article["sentence"] | |
label1 = article["label1"] | |
label2 = article["label2"] | |
yield id_, { | |
"text": text, | |
"label1": label1, | |
"label2": label2, | |
} | |