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HIPE2020_sent-split / HIPE2020_sent-split.py

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	# coding=utf-8
	# Copyright 2022 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
	"""TODO"""

	from datetime import datetime
	from typing import Optional
	import datasets
	import re


	_CITATION = """\
	TODO
	"""

	_DESCRIPTION = """\
	TODO
	"""

	_BASE_URL_TRAIN_DEV_TEST = "https://raw.githubusercontent.com/impresso/CLEF-HIPE-2020/master/data/v1.4/"


	_URLs = {
	"EN": {
	"dev": _BASE_URL_TRAIN_DEV_TEST + "en/HIPE-data-v1.4-dev-en.tsv",
	"test": _BASE_URL_TRAIN_DEV_TEST + "en/HIPE-data-v1.4-test-en.tsv"
	}, # English only no train
	"DE": {
	"dev": _BASE_URL_TRAIN_DEV_TEST + "de/HIPE-data-v1.4-dev-de.tsv",
	"train": _BASE_URL_TRAIN_DEV_TEST + "de/HIPE-data-v1.4-train-de.tsv",
	"test": _BASE_URL_TRAIN_DEV_TEST + "de/HIPE-data-v1.4-test-de.tsv"
	},
	"FR": {
	"dev": _BASE_URL_TRAIN_DEV_TEST + "fr/HIPE-data-v1.4-dev-fr.tsv",
	"train": _BASE_URL_TRAIN_DEV_TEST + "fr/HIPE-data-v1.4-train-fr.tsv",
	"test": _BASE_URL_TRAIN_DEV_TEST + "fr/HIPE-data-v1.4-test-fr.tsv"
	},
	}


	class HIPE2020Config(datasets.BuilderConfig):
	"""BuilderConfig for HIPE2020"""

	def __init__(self, data_urls,**kwargs):
	"""BuilderConfig for HIPE2020.
	Args:
	**kwargs: keyword arguments forwarded to super.
	"""
	super(HIPE2020Config, self).__init__(**kwargs)
	self.data_urls = data_urls


	class HIPE2020(datasets.GeneratorBasedBuilder):
	"""HIPE2020 dataset."""

	BUILDER_CONFIGS = [
	HIPE2020Config(
	name="en",
	data_urls=_URLs["EN"],
	version=datasets.Version("1.0.0"),
	description="HIPE dataset covering English",
	),
	HIPE2020Config(
	name="de",
	data_urls=_URLs["DE"],
	version=datasets.Version("1.0.0"),
	description="HIPE dataset covering German",
	),
	HIPE2020Config(
	name="fr",
	data_urls=_URLs["FR"],
	version=datasets.Version("1.0.0"),
	description="HIPE dataset covering French",
	),
	]

	def _info(self):
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{
	"id": datasets.Value("string"),
	"tokens": datasets.Sequence(datasets.Value("string")),
	"NE_COARSE_LIT": datasets.Sequence(
	datasets.features.ClassLabel(
	names=[
	"O",
	"B-comp",
	"B-loc",
	"B-org",
	"B-pers",
	"B-prod",
	"B-time",
	"I-loc",
	"I-org",
	"I-pers",
	"I-prod",
	"I-time",
	"_",
	]
	)
	),
	"NE_COARSE_METO_tags": datasets.Sequence(
	datasets.features.ClassLabel(
	names=[
	"O",
	"B-loc",
	"B-org",
	"B-pers",
	"B-prod",
	"B-time",
	"I-loc",
	"I-org",
	"I-pers",
	"_",
	]
	)
	),
	"NE_FINE_LIT_tags": datasets.Sequence(
	datasets.features.ClassLabel(
	names=[
	"O",
	"B-comp.name",
	"B-loc",
	"B-loc.add.elec",
	"B-loc.add.phys",
	"B-loc.adm.nat",
	"B-loc.adm.reg",
	"B-loc.adm.sup",
	"B-loc.adm.town",
	"B-loc.fac",
	"B-loc.oro",
	"B-loc.phys.astro",
	"B-loc.phys.geo",
	"B-loc.phys.hydro",
	"B-loc.unk",
	"B-org",
	"B-org.adm",
	"B-org.ent",
	"B-org.ent.pressagency",
	"B-pers",
	"B-pers.coll",
	"B-pers.ind",
	"B-pers.ind.articleauthor",
	"B-prod",
	"B-prod.doctr",
	"B-prod.media",
	"B-time",
	"B-time.date.abs",
	"I-loc",
	"I-loc.add.elec",
	"I-loc.add.phys",
	"I-loc.adm.nat",
	"I-loc.adm.reg",
	"I-loc.adm.sup",
	"I-loc.adm.town",
	"I-loc.fac",
	"I-loc.oro",
	"I-loc.phys.astro",
	"I-loc.phys.geo",
	"I-loc.phys.hydro",
	"I-loc.unk",
	"I-org",
	"I-org.adm",
	"I-org.ent",
	"I-org.ent.pressagency",
	"I-pers",
	"I-pers.coll",
	"I-pers.ind",
	"I-pers.ind.articleauthor",
	"I-prod",
	"I-prod.doctr",
	"I-prod.media",
	"I-time",
	"I-time.date.abs",
	"_",
	]
	)
	),
	"NE_FINE_METO_tags": datasets.Sequence(
	datasets.features.ClassLabel(
	names=[
	"O",
	"B-loc",
	"B-loc.adm.nat",
	"B-loc.adm.reg",
	"B-loc.adm.town",
	"B-loc.fac",
	"B-loc.oro",
	"B-org",
	"B-org.adm",
	"B-org.ent",
	"B-pers.coll",
	"B-pers.ind",
	"B-prod.media",
	"B-time.date.abs",
	"I-loc",
	"I-loc.adm.nat",
	"I-loc.adm.reg",
	"I-loc.fac",
	"I-loc.oro",
	"I-org",
	"I-org.adm",
	"I-org.ent",
	"I-pers",
	"I-pers.ind",
	"_",
	]
	)
	),
	"NE_FINE_COMP_tags": datasets.Sequence(
	datasets.features.ClassLabel(
	names=[
	"O",
	"B-comp.demonym",
	"B-comp.function",
	"B-comp.name",
	"B-comp.qualifier",
	"B-comp.title",
	"I-comp.demonym",
	"I-comp.function",
	"I-comp.name",
	"I-comp.qualifier",
	"I-comp.title",
	"_",
	]
	)
	),
	"NE_NESTED_tags": datasets.Sequence(
	datasets.features.ClassLabel(
	names=[
	"O",
	"B-loc",
	"B-loc.adm.nat",
	"B-loc.adm.reg",
	"B-loc.adm.sup",
	"B-loc.adm.town",
	"B-loc.fac",
	"B-loc.oro",
	"B-loc.phys.geo",
	"B-loc.phys.hydro",
	"B-org",
	"B-org.adm",
	"B-org.ent",
	"B-pers.coll",
	"B-pers.ind",
	"B-prod.media",
	"B-time.date.abs",
	"I-loc",
	"I-loc.adm.nat",
	"I-loc.adm.reg",
	"I-loc.adm.town",
	"I-loc.adm.sup",
	"I-loc.fac",
	"I-loc.oro",
	"I-loc.phys.astro",
	"I-loc.phys.geo",
	"I-loc.phys.hydro",
	"I-org",
	"I-org.adm",
	"I-org.ent",
	"I-pers.ind",
	"I-prod.media",
	"_",
	]
	)
	),
	"NEL_LIT_ID": datasets.Sequence(datasets.Value("string")),
	"NEL_METO_ID": datasets.Sequence(datasets.Value("string")),
	"no_space_after": datasets.Sequence(datasets.Value("bool")),
	"end_of_line": datasets.Sequence(datasets.Value("bool")),
	"PySBDSegment":datasets.Sequence(datasets.Value("bool")),
	"date": datasets.Value("timestamp[s]"),
	"title": datasets.Value("string"),
	"document_id": datasets.Value("string"),
	}
	),
	supervised_keys=None,
	homepage="TODO",
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""
	downloaded_files = dl_manager.download_and_extract(self.config.data_urls)
	data_files = {
	"dev": downloaded_files["dev"],
	"test": downloaded_files["test"],
	}
	splits = [
	datasets.SplitGenerator(
	name=datasets.Split.VALIDATION,
	gen_kwargs={"filepath": data_files["dev"]},
	),
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	gen_kwargs={"filepath": data_files["test"]},
	),
	]
	if self.config.name != "en":
	data_files.update({
	"train": downloaded_files["train"],
	})
	splits += [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={"filepath": data_files["train"]},
	),
	]
	return splits

	def _generate_examples(self, filepath):
	date_re = re.compile(r"# date = (\d{4}-\d{2}-\d{02})")
	title_re = re.compile(r"newspaper = (\w{3})")
	document_id_re = re.compile(r"document_id = (.*)")
	with open(filepath, encoding="utf-8") as f:
	guid = 0
	tokens = []
	NE_COARSE_LIT_tags = []
	NE_COARSE_METO_tags = []
	NE_FINE_LIT_tags = []
	NE_FINE_METO_tags = []
	NE_FINE_COMP_tags = []
	NE_NESTED_tags = []
	NEL_LIT_ID = []
	NEL_METO_ID = []
	no_space_after = []
	end_of_line = []
	pysdbsegment = []

	new_sentence = False

	for line in f:
	if line.startswith(
	"TOKEN NE-COARSE-LIT NE-COARSE-METO NE-FINE-LIT NE-FINE-METO NE-FINE-COMP NE-NESTED NEL-LIT NEL-METO MISC"
	):
	continue
	if line.startswith("#") or line == "\n":
	date_match = re.search(date_re, line)
	if date_match:
	date = date_match.group(1)
	date = datetime.strptime(date, "%Y-%m-%d")
	title_match = re.search(title_re, line)
	if title_match:
	title = title_match.group(1)
	document_id_match = re.search(document_id_re, line)
	if document_id_match:
	document_id = document_id_match.group(1)
	if tokens:
	yield guid, {
	"id": str(guid),
	"tokens": tokens,
	"NE_COARSE_LIT": NE_COARSE_LIT_tags,
	"NE_COARSE_METO_tags": NE_COARSE_METO_tags,
	"NE_FINE_LIT_tags": NE_FINE_LIT_tags,
	"NE_FINE_METO_tags": NE_FINE_METO_tags,
	"NE_FINE_COMP_tags": NE_FINE_COMP_tags,
	"NE_NESTED_tags": NE_NESTED_tags,
	"NEL_LIT_ID": NEL_LIT_ID,
	"NEL_METO_ID": NEL_METO_ID,
	"no_space_after": no_space_after,
	"end_of_line": end_of_line,
	"PySBDSegment":pysdbsegment,
	"date": date,
	"title": title,
	"document_id": document_id,
	}
	guid += 1
	tokens = []
	NE_COARSE_LIT_tags = []
	NE_COARSE_METO_tags = []
	NE_FINE_LIT_tags = []
	NE_FINE_METO_tags = []
	NE_FINE_COMP_tags = []
	NE_NESTED_tags = []
	NEL_LIT_ID = []
	NEL_METO_ID = []
	no_space_after = []
	end_of_line = []
	pysdbsegment = []
	else:
	# New row if there is a new sentence
	if new_sentence == True:
	yield guid, {
	"id": str(guid),
	"tokens": tokens,
	"NE_COARSE_LIT": NE_COARSE_LIT_tags,
	"NE_COARSE_METO_tags": NE_COARSE_METO_tags,
	"NE_FINE_LIT_tags": NE_FINE_LIT_tags,
	"NE_FINE_METO_tags": NE_FINE_METO_tags,
	"NE_FINE_COMP_tags": NE_FINE_COMP_tags,
	"NE_NESTED_tags": NE_NESTED_tags,
	"NEL_LIT_ID": NEL_LIT_ID,
	"NEL_METO_ID": NEL_METO_ID,
	"no_space_after": no_space_after,
	"end_of_line": end_of_line,
	"PySBDSegment":pysdbsegment,
	"date": date,
	"title": title,
	"document_id": document_id,
	}
	guid += 1
	tokens = []
	NE_COARSE_LIT_tags = []
	NE_COARSE_METO_tags = []
	NE_FINE_LIT_tags = []
	NE_FINE_METO_tags = []
	NE_FINE_COMP_tags = []
	NE_NESTED_tags = []
	NEL_LIT_ID = []
	NEL_METO_ID = []
	no_space_after = []
	end_of_line = []
	pysdbsegment = []

	# HIPE 2020 tokens are tab separated
	splits = line.split(
	"\t"
	) # TOKEN NE-COARSE-LIT NE-COARSE-METO NE-FINE-LIT NE-FINE-METO NE-FINE-COMP NE-NESTED NEL-LIT NEL-METO MISC
	tokens.append(splits[0])
	NE_COARSE_LIT_tags.append(splits[1])
	NE_COARSE_METO_tags.append(splits[2])
	NE_FINE_LIT_tags.append(splits[3])
	NE_FINE_METO_tags.append(splits[4])
	NE_FINE_COMP_tags.append(splits[5])
	NE_NESTED_tags.append(splits[6])
	NEL_LIT_ID.append(splits[7])
	NEL_METO_ID.append(splits[8])
	misc = splits[-1]
	is_space = "NoSpaceAfter" in misc
	is_end_of_line = "EndOfLine" in misc
	PySBDSegment = "PySBDSegment" in misc
	no_space_after.append(is_space)
	end_of_line.append(is_end_of_line)
	pysdbsegment.append(PySBDSegment)

	new_sentence = PySBDSegment

	# last example
	yield guid, {
	"id": str(guid),
	"tokens": tokens,
	"NE_COARSE_LIT": NE_COARSE_LIT_tags,
	"NE_COARSE_METO_tags": NE_COARSE_METO_tags,
	"NE_FINE_LIT_tags": NE_FINE_LIT_tags,
	"NE_FINE_METO_tags": NE_FINE_METO_tags,
	"NE_FINE_COMP_tags": NE_FINE_COMP_tags,
	"NE_NESTED_tags": NE_NESTED_tags,
	"NEL_LIT_ID": NEL_LIT_ID,
	"NEL_METO_ID": NEL_METO_ID,
	"no_space_after": no_space_after,
	"end_of_line": end_of_line,
	"PySBDSegment":pysdbsegment,
	"date": date,
	"title": title,
	"document_id": document_id,
	}