Datasets:

qanastek
/

ANTILLES

	# coding=utf-8
	# Source: https://github.com/huggingface/datasets/blob/master/templates/new_dataset_script.py

	"""ANTILLES Corpus"""

	import os
	import datasets
	from tqdm import tqdm

	logger = datasets.logging.get_logger(__name__)

	_CITATION = """
	@misc{
	universaldependencies,
	title={UniversalDependencies/UD_French-GSD},
	url={https://github.com/UniversalDependencies/UD_French-GSD}, journal={GitHub},
	author={UniversalDependencies}
	}

	@inproceedings{mcdonald-etal-2013-universal,
	title = {{U}niversal {D}ependency Annotation for Multilingual Parsing},
	author = {
	McDonald, Ryan and
	Nivre, Joakim and
	Quirmbach-Brundage, Yvonne and
	Goldberg, Yoav and
	Das, Dipanjan and
	Ganchev, Kuzman and
	Hall, Keith and
	Petrov, Slav and
	Zhang, Hao and
	Tackstrom, Oscar and
	Bedini, Claudia and
	Bertomeu Castello, Nuria and
	Lee, Jungmee
	},
	booktitle = {Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)},
	month = aug,
	year = {2013},
	address = {Sofia, Bulgaria},
	publisher = {Association for Computational Linguistics},
	url = {https://aclanthology.org/P13-2017},
	pages = {92--97",
	}

	@techreport{
	LIA_TAGG,
	author = {Frédéric Béchet},
	title = {LIA_TAGG: a statistical POS tagger + syntactic bracketer},
	institution = {Aix-Marseille University & CNRS},
	year = {2001}
	}
	"""

	_LICENSE = """
	For the following languages

	German, Spanish, French, Indonesian, Italian, Japanese, Korean and Brazilian
	Portuguese

	we will distinguish between two portions of the data.

	1. The underlying text for sentences that were annotated. This data Google
	asserts no ownership over and no copyright over. Some or all of these
	sentences may be copyrighted in some jurisdictions. Where copyrighted,
	Google collected these sentences under exceptions to copyright or implied
	license rights. GOOGLE MAKES THEM AVAILABLE TO YOU 'AS IS', WITHOUT ANY
	WARRANTY OF ANY KIND, WHETHER EXPRESS OR IMPLIED.

	2. The annotations -- part-of-speech tags and dependency annotations. These are
	made available under a CC BY-SA 4.0. GOOGLE MAKES
	THEM AVAILABLE TO YOU 'AS IS', WITHOUT ANY WARRANTY OF ANY KIND, WHETHER
	EXPRESS OR IMPLIED. See attached LICENSE file for the text of CC BY-NC-SA.

	Portions of the German data were sampled from the CoNLL 2006 Tiger Treebank
	data. Hans Uszkoreit graciously gave permission to use the underlying
	sentences in this data as part of this release.

	Any use of the data should reference the above plus:

	Universal Dependency Annotation for Multilingual Parsing
	Ryan McDonald, Joakim Nivre, Yvonne Quirmbach-Brundage, Yoav Goldberg,
	Dipanjan Das, Kuzman Ganchev, Keith Hall, Slav Petrov, Hao Zhang,
	Oscar Tackstrom, Claudia Bedini, Nuria Bertomeu Castello and Jungmee Lee
	Proceedings of ACL 2013
	"""

	_DESCRIPTION = "No description"

	_URLS = {
	"ANTILLES": "https://huggingface.co/datasets/qanastek/ANTILLES/resolve/main/ANTILLES.zip"
	}

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

	VERSION = datasets.Version("1.1.0")

	BUILDER_CONFIGS = [
	datasets.BuilderConfig(name="ANTILLES", version=VERSION, description="The ANTILLES corpora"),
	]

	DEFAULT_CONFIG_NAME = "ANTILLES"

	def _info(self):
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{
	"id": datasets.Value("string"),
	"tokens": datasets.Sequence(datasets.Value("string")),
	"pos_tags": datasets.Sequence(
	datasets.features.ClassLabel(
	names = ['PART', 'PDEMMP', 'PREFS', 'PINDMP', 'DINTMS', 'NUM', 'PINTFS', 'NFP', 'PUNCT', 'PRELMS', 'NOUN', 'PPER3MS', 'AUX', 'COSUB', 'ADJ', 'VPPRE', 'COCO', 'ADJMP', 'X', 'NMS', 'PINDMS', 'DETFS', 'PPER2S', 'PREFP', 'PPER3MP', 'PRELMP', 'PINDFS', 'PRON', 'PREP', 'PPOBJMP', 'ADJFS', 'DET', 'ADJFP', 'PDEMFP', 'PREL', 'PPER3FS', 'VPPFS', 'PPER3FP', 'CHIF', 'NMP', 'SYM', 'NFS', 'VERB', 'PREF', 'VPPFP', 'PDEMMS', 'XFAMIL', 'PINDFP', 'VPPMP', 'YPFOR', 'ADV', 'PRELFS', 'DINTFS', 'DETMS', 'PPOBJFP', 'PPOBJMS', 'VPPMS', 'INTJ', 'PROPN', 'PDEMFS', 'PPER1S', 'PRELFP', 'MOTINC', 'ADJMS', 'PPOBJFS']
	)
	),
	}
	),
	supervised_keys=None,
	homepage="https://github.com/qanastek/ANTILLES",
	citation=_CITATION,
	license=_LICENSE,
	)

	def _split_generators(self, dl_manager):

	urls = _URLS[self.config.name]
	data_dir = dl_manager.download_and_extract(urls)

	TRAIN_PATH = 'train.conllu'
	DEV_PATH = 'dev.conllu'
	TEST_PATH = 'test.conllu'

	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={
	"filepath": os.path.join(data_dir, TRAIN_PATH),
	"split": "train",
	}
	),
	datasets.SplitGenerator(
	name=datasets.Split.VALIDATION,
	gen_kwargs={
	"filepath": os.path.join(data_dir, DEV_PATH),
	"split": "dev",
	}
	),
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	gen_kwargs={
	"filepath": os.path.join(data_dir, TEST_PATH),
	"split": "test",
	}
	),
	]


	def _generate_examples(self, filepath, split):

	logger.info("⏳ Generating examples from = %s", filepath)

	with open(filepath, encoding="utf-8") as f:

	guid = 0
	tokens = []
	pos_tags = []

	for line in tqdm(f):

	if "#" in line or line == "" or line == "\n":

	if tokens:

	yield guid, {
	"id": str(guid),
	"tokens": tokens,
	"pos_tags": pos_tags,
	}

	guid += 1
	tokens = []
	pos_tags = []

	else:

	splits = line.split('\t')
	tokens.append(splits[1])

	pos_tags.append(splits[3].rstrip() if "_" not in splits[3] else "X")

	yield guid, {
	"id": str(guid),
	"tokens": tokens,
	"pos_tags": pos_tags,
	}