Datasets:

strombergnlp
/

nordic_langid

	# 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
	"""NordicDSL: A language identification datasets for Nordic languages"""

	import csv
	import os

	import datasets


	logger = datasets.logging.get_logger(__name__)


	_CITATION = """\
	@inproceedings{haas-derczynski-2021-discriminating,
	title = "Discriminating Between Similar Nordic Languages",
	author = "Haas, Ren{\'e} and
	Derczynski, Leon",
	booktitle = "Proceedings of the Eighth Workshop on NLP for Similar Languages, Varieties and Dialects",
	month = apr,
	year = "2021",
	address = "Kiyv, Ukraine",
	publisher = "Association for Computational Linguistics",
	url = "https://aclanthology.org/2021.vardial-1.8",
	pages = "67--75",
	}

	"""

	_DESCRIPTION = """\
	Automatic language identification is a challenging problem. Discriminating
	between closely related languages is especially difficult. This paper presents
	a machine learning approach for automatic language identification for the
	Nordic languages, which often suffer miscategorisation by existing
	state-of-the-art tools. Concretely we will focus on discrimination between six
	Nordic languages: Danish, Swedish, Norwegian (Nynorsk), Norwegian (Bokmål),
	Faroese and Icelandic.

	This is the data for the tasks. Two variants are provided: 10K and 50K, with
	holding 10,000 and 50,000 examples for each language respectively.

	"""

	_URLS = {
	"10K": "nordic_dsl_10000",
	"50K": "nordic_dsl_50000",
	}


	class NordicLangIdConfig(datasets.BuilderConfig):
	"""BuilderConfig for NordicLangId"""

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

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


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

	VERSION = datasets.Version("1.0.0")

	BUILDER_CONFIGS = [
	NordicLangIdConfig(
	name="10k",
	description="Data for distinguishing between similar Nordic languages: 10k examples per class",
	version=VERSION,
	),
	NordicLangIdConfig(
	name="50k",
	description="Data for distinguishing between similar Nordic languages: 50k examples per class",
	version=VERSION,
	),
	]

	def _info(self):
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{
	"id": datasets.Value("string"),
	"sentence": datasets.Value("string"),
	"language": datasets.features.ClassLabel(
	names=[
	"dk",
	"sv",
	"nb",
	"nn",
	"fo",
	"is",
	]
	),
	}
	),
	supervised_keys=None,
	homepage="https://aclanthology.org/2021.vardial-1.8/",
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""
	if self.config.name == "10k":
	downloaded_train = dl_manager.download(_URLS["10K"] + 'train.csv')
	downloaded_test = dl_manager.download(_URLS["10K"] + 'test.csv')
	elif self.config.name == "50k":
	downloaded_train = dl_manager.download(_URLS["50K"] + 'train.csv')
	downloaded_test = dl_manager.download(_URLS["50K"] + 'test.csv')

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

	def _generate_examples(self, filepath):
	logger.info("⏳ Generating examples from = %s", filepath)
	with open(filepath, encoding="utf-8") as f:
	guid = 0
	for line in f:
	line = line.strip()
	if not line:
	continue
	if self.config.name == "10k":
	line = line.replace('dataset10000, ', '')
	if self.config.name == "50k":
	line = line.replace('dataset50000, ', '')

	instance = {
	"id": str(guid),
	"language": line[-2:],
	"sentence": line[:-3],
	}

	yield guid, instance
	guid += 1