Datasets:

clarin-pl
/

2021-punctuation-restoration

	import os

	import datasets
	import pandas as pd


	_CITATION = """"""

	_DESCRIPTION = """\
	This dataset is designed to be used in training models
	that restore punctuation marks from the output of
	Automatic Speech Recognition system for Polish language.
	"""

	_HOMEPAGE = "https://github.com/poleval/2021-punctuation-restoration"

	_URL = "https://raw.githubusercontent.com/poleval/2021-punctuation-restoration/main"

	_PATHS = {
	"train": [os.path.join(_URL, "train", "in.tsv"), os.path.join(_URL, "train", "expected.tsv")],
	"test-A": [os.path.join(_URL, "test-A", "in.tsv"), os.path.join(_URL, "test-A", "expected.tsv")],
	}

	_TO_DOWNLOAD = _PATHS["train"] + _PATHS["test-A"]


	class PunctuationDatasetConfig(datasets.BuilderConfig):
	"""BuilderConfig for AfrikaansNerCorpus"""

	def __init__(self, **kwargs):
	"""BuilderConfig for PunctuationDataset.
	Args:
	**kwargs: keyword arguments forwarded to super.
	"""
	super(PunctuationDatasetConfig, self).__init__(**kwargs)


	class PunctuationDataset(datasets.GeneratorBasedBuilder):
	"""TODO: Short description of my dataset."""

	VERSION = datasets.Version("1.0.0")

	BUILDER_CONFIGS = [
	PunctuationDatasetConfig(
	name="punctuation_dataset",
	version=datasets.Version("1.0.0"),
	description="PunctuationDataset dataset",
	),
	]

	def _info(self):
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{
	"text_in": datasets.Value("string"),
	"text_out": datasets.Value("string"),
	"tokens": datasets.Sequence(datasets.Value("string")),
	"tags": datasets.Sequence(
	datasets.features.ClassLabel(
	names=[
	'B-.',
	'B-,',
	'B--',
	'B-!',
	'B-?',
	'B-:',
	'B-;',
	'O',
	]
	)
	)
	}),
	supervised_keys=None,
	homepage=_HOMEPAGE,
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	data_paths = {key: dl_manager.download(urls) for key, urls in _PATHS.items()}
	print(data_paths)
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN, gen_kwargs={"filepaths": data_paths["train"]}
	),
	datasets.SplitGenerator(
	name=datasets.Split.TEST, gen_kwargs={"filepaths": data_paths["test-A"]}
	),
	]

	def _generate_examples(self, filepaths):
	in_df = pd.read_csv(os.path.join(filepaths[0]), sep='\t', header=None)
	out_df = pd.read_csv(os.path.join(filepaths[1]), sep='\t', header=None)
	for key, ((_, row_in), (_, row_out)) in enumerate(zip(in_df.iterrows(), out_df.iterrows()), 1):

	text_in = PunctuationDataset._clean_text(row_in[1])
	text_out = PunctuationDataset._clean_text(row_out[0])

	tokens = []
	tags = []
	for token_in, token_out in zip(text_in.split(), text_out.split()):
	assert token_in.lower() in token_out.lower()

	tokens.append(token_in)
	if token_in.lower() == token_out.lower():
	tags.append('O')
	else:
	tags.append(f'B-{token_out[-1]}')

	yield key, {
	"text_in": text_in,
	"text_out": text_out,
	"tokens": tokens,
	"tags": tags
	}

	@staticmethod
	def _clean_text(text: str, lower: bool = False) -> str:
	if lower:
	text = text.lower()
	text = text.replace(' -', '')
	text = text.replace(' .', '')
	text = text.replace(' ,', '')
	text = text.replace(' ', ' ')
	text = text.strip()
	return text