hc4-corpus.py

# 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.

# Lint as: python3

import json

import datasets
from dataclasses import dataclass

_CITATION = '''
@article{Lawrie2022HC4,
  author = {Dawn Lawrie and James Mayfield and Douglas W. Oard and Eugene Yang},
  title = {HC4: A New Suite of Test Collections for Ad Hoc CLIR},
  booktitle = {{Advances in Information Retrieval. 44th European Conference on IR Research (ECIR 2022)},
  year = {2022},
  month = apr,
  publisher = {Springer},
  series = {Lecture Notes in Computer Science},
  site = {Stavanger, Norway},
  url = {https://arxiv.org/abs/2201.09992}
}
'''

# Note: this dataset requires to download HC4 collection based on the requirement of ir-datasets

import ir_datasets


langs = [
  'fa', 'ru', 'zh'
]

_DESCRIPTION = 'dataset load script for HC4 Corpus'


class HC4Corpus(datasets.GeneratorBasedBuilder):
    BUILDER_CONFIGS = [
        datasets.BuilderConfig(
            version=datasets.Version('1.0.0'),
            name=lang, 
            description=f'HC4 Corpus'
        ) for lang in langs
    ]

    def _info(self):
        features = datasets.Features({
            'docid': datasets.Value('string'), 
            'title': datasets.Value('string'),
            'text': datasets.Value('string'),
        })

        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=features,  # Here we define them above because they are different between the two configurations
            supervised_keys=None,
            # Homepage of the dataset for documentation
            homepage='https://github.com/hltcoe/HC4',
            # License for the dataset if available
            license='',
            # Citation for the dataset
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        lang = self.config.name

        splits = [
            datasets.SplitGenerator(
                name='train',
                gen_kwargs={
                    'lang': lang,
                },
            ),
        ]
        return splits

    def _generate_examples(self, lang):
        if lang not in {"fa", "ru", "zh"}:
            raise ValueError(f"Unexpected language: {lang}")

        dataset = ir_datasets.load(f'hc4/{lang}')
        for doc in dataset.docs_iter():
              yield doc.doc_id, {'docid': doc.doc_id, 'title': doc.title, 'text': doc.text}