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bigbio
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bio_sim_verb

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bio_sim_verb / bio_sim_verb.py

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	# coding=utf-8
	# Copyright 2022 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.
	"""
	This repository contains the evaluation datasets for the paper Bio-SimVerb and
	Bio-SimLex: Wide-coverage Evaluation Sets of Word Similarity in Biomedicine by
	Billy Chiu, Sampo Pyysalo and Anna Korhonen.
	"""

	import csv
	from typing import Dict, List, Tuple

	import datasets

	from .bigbiohub import pairs_features
	from .bigbiohub import BigBioConfig
	from .bigbiohub import Tasks

	# TODO: Add BibTeX citation
	_LANGUAGES = ['English']
	_PUBMED = True
	_LOCAL = False
	_CITATION = """\
	@article{article,
	title = {
	Bio-SimVerb and Bio-SimLex: Wide-coverage evaluation sets of word
	similarity in biomedicine
	},
	author = {Chiu, Billy and Pyysalo, Sampo and Vulić, Ivan and Korhonen, Anna},
	year = 2018,
	month = {02},
	journal = {BMC Bioinformatics},
	volume = 19,
	pages = {},
	doi = {10.1186/s12859-018-2039-z}
	}
	"""

	_DATASETNAME = "bio_sim_verb"
	_DISPLAYNAME = "Bio-SimVerb"

	_DESCRIPTION = """
	This repository contains the evaluation datasets for the paper Bio-SimVerb and \
	Bio-SimLex: Wide-coverage Evaluation Sets of Word Similarity in Biomedicine by \
	Billy Chiu, Sampo Pyysalo and Anna Korhonen.
	"""

	_HOMEPAGE = "https://github.com/cambridgeltl/bio-simverb"

	_LICENSE = 'License information unavailable'

	_URLS = {
	_DATASETNAME: "https://raw.githubusercontent.com/cambridgeltl/bio-simverb/master/wvlib/word-similarities/bio-simverb/Bio-SimVerb.txt",
	}

	_SUPPORTED_TASKS = [Tasks.SEMANTIC_SIMILARITY]

	_SOURCE_VERSION = "1.0.0"
	_BIGBIO_VERSION = "1.0.0"


	# TODO: Name the dataset class to match the script name using CamelCase instead of snake_case
	# Append "Dataset" to the class name: BioASQ --> BioasqDataset
	class BioSimVerb(datasets.GeneratorBasedBuilder):
	"""Evaluation of word similarity in biomedical texts."""

	SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
	BIGBIO_VERSION = datasets.Version(_BIGBIO_VERSION)

	BUILDER_CONFIGS = [
	BigBioConfig(
	name="bio_sim_verb_source",
	version=SOURCE_VERSION,
	description="bio_sim_verb source schema",
	schema="source",
	subset_id="bio_sim_verb",
	),
	BigBioConfig(
	name="bio_sim_verb_bigbio_pairs",
	version=BIGBIO_VERSION,
	description="bio_sim_verb BigBio schema",
	schema="bigbio_pairs",
	subset_id="bio_sim_verb",
	),
	]

	DEFAULT_CONFIG_NAME = "bio_sim_verb_source"

	def _info(self) -> datasets.DatasetInfo:

	if self.config.schema == "source":
	features = datasets.Features(
	{
	"text_1": datasets.Value("string"),
	"text_2": datasets.Value("string"),
	"label": datasets.Value("float32"),
	}
	)

	# Using in pairs schema
	elif self.config.schema == "bigbio_pairs":
	features = pairs_features

	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=features,
	homepage=_HOMEPAGE,
	license=str(_LICENSE),
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager) -> List[datasets.SplitGenerator]:
	"""Returns SplitGenerators."""

	urls = _URLS[_DATASETNAME]
	data_dir = dl_manager.download_and_extract(urls)

	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	# Whatever you put in gen_kwargs will be passed to _generate_examples
	gen_kwargs={"filepath": data_dir, "split": "train"},
	)
	]

	def _generate_examples(self, filepath, split: str) -> Tuple[int, Dict]:
	"""Yields examples as (key, example) tuples."""

	with open(filepath, encoding="utf-8") as csv_file:
	csv_reader = csv.reader(
	csv_file,
	quotechar='"',
	delimiter="\t",
	quoting=csv.QUOTE_ALL,
	skipinitialspace=True,
	)

	if self.config.schema == "source":
	for id_, row in enumerate(csv_reader):
	text_1, text_2, label = row
	yield id_, {
	"text_1": text_1,
	"text_2": text_2,
	"label": float(label),
	}

	elif self.config.schema == "bigbio_pairs":
	uid = 0
	for id_, row in enumerate(csv_reader):
	uid += 1
	text_1, text_2, label = row
	yield id_, {
	"id": str(uid),
	"document_id": "NULL",
	"text_1": text_1,
	"text_2": text_2,
	"label": str(label),
	}