bio_sim_verb.py

# 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),
                    }