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sem_eval_2010_task_8 / sem_eval_2010_task_8.py

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	# coding=utf-8
	# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
	#
	# 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.
	"""The SemEval-2010 Task 8 on Multi-way classification of semantic relations between pairs of nominals"""


	import os

	import datasets
	from datasets.tasks import TextClassification


	_CITATION = """\
	@inproceedings{hendrickx-etal-2010-semeval,
	title = "{S}em{E}val-2010 Task 8: Multi-Way Classification of Semantic Relations between Pairs of Nominals",
	author = "Hendrickx, Iris and
	Kim, Su Nam and
	Kozareva, Zornitsa and
	Nakov, Preslav and
	{\'O} S{\'e}aghdha, Diarmuid and
	Pad{\'o}, Sebastian and
	Pennacchiotti, Marco and
	Romano, Lorenza and
	Szpakowicz, Stan",
	booktitle = "Proceedings of the 5th International Workshop on Semantic Evaluation",
	month = jul,
	year = "2010",
	address = "Uppsala, Sweden",
	publisher = "Association for Computational Linguistics",
	url = "https://www.aclweb.org/anthology/S10-1006",
	pages = "33--38",
	}
	"""

	_DESCRIPTION = """\
	The SemEval-2010 Task 8 focuses on Multi-way classification of semantic relations between pairs of nominals.
	The task was designed to compare different approaches to semantic relation classification
	and to provide a standard testbed for future research.
	"""

	_URL = "https://github.com/JoelNiklaus/SemEval2010Task8/raw/main/SemEval2010_task8_all_data.zip"


	class SemEval2010Task8(datasets.GeneratorBasedBuilder):
	"""The SemEval-2010 Task 8 focuses on Multi-way classification of semantic relations between pairs of nominals.
	The task was designed to compare different approaches to semantic relation classification
	and to provide a standard testbed for future research."""

	VERSION = datasets.Version("1.0.0")

	def _info(self):
	return datasets.DatasetInfo(
	# This is the description that will appear on the datasets page.
	description=_DESCRIPTION,
	# This defines the different columns of the dataset and their types
	features=datasets.Features(
	{
	"sentence": datasets.Value("string"),
	"relation": datasets.ClassLabel(
	names=[
	"Cause-Effect(e1,e2)",
	"Cause-Effect(e2,e1)",
	"Component-Whole(e1,e2)",
	"Component-Whole(e2,e1)",
	"Content-Container(e1,e2)",
	"Content-Container(e2,e1)",
	"Entity-Destination(e1,e2)",
	"Entity-Destination(e2,e1)",
	"Entity-Origin(e1,e2)",
	"Entity-Origin(e2,e1)",
	"Instrument-Agency(e1,e2)",
	"Instrument-Agency(e2,e1)",
	"Member-Collection(e1,e2)",
	"Member-Collection(e2,e1)",
	"Message-Topic(e1,e2)",
	"Message-Topic(e2,e1)",
	"Product-Producer(e1,e2)",
	"Product-Producer(e2,e1)",
	"Other",
	]
	),
	}
	),
	# If there's a common (input, target) tuple from the features,
	# specify them here. They'll be used if as_supervised=True in
	# builder.as_dataset.
	supervised_keys=datasets.info.SupervisedKeysData(input="sentence", output="relation"),
	# Homepage of the dataset for documentation
	homepage="https://semeval2.fbk.eu/semeval2.php?location=tasks&taskid=11",
	citation=_CITATION,
	task_templates=[TextClassification(text_column="sentence", label_column="relation")],
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""
	# dl_manager is a datasets.download.DownloadManager that can be used to
	# download and extract URLs
	dl_dir = dl_manager.download_and_extract(_URL)
	data_dir = os.path.join(dl_dir, "SemEval2010_task8_all_data")
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	# These kwargs will be passed to _generate_examples
	gen_kwargs={
	"filepath": os.path.join(data_dir, "SemEval2010_task8_training/TRAIN_FILE.TXT"),
	},
	),
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	gen_kwargs={
	"filepath": os.path.join(data_dir, "SemEval2010_task8_testing_keys/TEST_FILE_FULL.TXT"),
	},
	),
	]

	def _generate_examples(self, filepath):
	"""Yields examples."""
	with open(filepath, "r", encoding="us-ascii") as file:
	lines = file.readlines()
	num_lines_per_sample = 4

	for i in range(0, len(lines), num_lines_per_sample):
	idx = int(lines[i].split("\t")[0])
	sentence = lines[i].split("\t")[1][1:-2] # remove " at the start and "\n at the end
	relation = lines[i + 1][:-1] # remove \n at the end
	yield idx, {
	"sentence": sentence,
	"relation": relation,
	}