Datasets:

strombergnlp
/

shaj

	# coding=utf-8
	# Copyright 2020 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
	"""SHAJ: An abusive language dataset for Albanian"""

	import csv
	import os

	import datasets


	logger = datasets.logging.get_logger(__name__)


	_CITATION = """\
	@article{nurce2021detecting,
	title={Detecting Abusive Albanian},
	author={Nurce, Erida and Keci, Jorgel and Derczynski, Leon},
	journal={arXiv preprint arXiv:2107.13592},
	year={2021}
	}
	"""

	_DESCRIPTION = """\
	This is an abusive/offensive language detection dataset for Albanian. The data is formatted
	following the OffensEval convention, with three tasks:

	* Subtask A: Offensive (OFF) or not (NOT)
	* Subtask B: Untargeted (UNT) or targeted insult (TIN)
	* Subtask C: Type of target: individual (IND), group (GRP), or other (OTH)

	* The subtask A field should always be filled.
	* The subtask B field should only be filled if there's "offensive" (OFF) in A.
	* The subtask C field should only be filled if there's "targeted" (TIN) in B.

	The dataset name is a backronym, also standing for "Spoken Hate in the Albanian Jargon"

	See the paper [https://arxiv.org/abs/2107.13592](https://arxiv.org/abs/2107.13592) for full details.
	"""

	_URL = "full_albanian_dataset.csv"


	class ShajConfig(datasets.BuilderConfig):
	"""BuilderConfig for Shaj"""

	def __init__(self, **kwargs):
	"""BuilderConfig Shaj.

	Args:
	**kwargs: keyword arguments forwarded to super.
	"""
	super(ShajConfig, self).__init__(**kwargs)


	class Shaj(datasets.GeneratorBasedBuilder):
	"""Shaj dataset."""

	BUILDER_CONFIGS = [
	ShajConfig(name="Shaj", version=datasets.Version("1.0.0"), description="Abusive language dataset in Albanian"),
	]

	def _info(self):
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{
	"id": datasets.Value("string"),
	"text": datasets.Value("string"),
	"subtask_a": datasets.features.ClassLabel(
	names=[
	"OFF",
	"NOT",
	]
	),
	"subtask_b": datasets.features.ClassLabel(
	names=[
	"TIN",
	"UNT",
	"",
	]
	),
	"subtask_c": datasets.features.ClassLabel(
	names=[
	"IND",
	"GRP",
	"OTH",
	"",
	]
	),
	}
	),
	supervised_keys=None,
	homepage="https://arxiv.org/abs/2107.13592",
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""
	downloaded_file = dl_manager.download_and_extract(_URL)

	return [
	datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_file}),
	]

	def _generate_examples(self, filepath):
	logger.info("⏳ Generating examples from = %s", filepath)
	with open(filepath, encoding="utf-8") as f:
	shaj_reader = csv.DictReader(f, fieldnames=('text','subtask_a','subtask_b','subtask_c'), delimiter=";", quotechar='"')
	guid = 0
	for instance in shaj_reader:
	instance["id"] = str(guid)
	yield guid, instance
	guid += 1