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"""COSUJU: The Court Summaries and Judgements Dataset.""" |
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from __future__ import absolute_import, division, print_function |
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import json |
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import datasets |
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logger = datasets.logging.get_logger(__name__) |
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_CITATION = """\ |
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@InProceedings{huggingface:dataset, |
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title = {CoSuJu 500+ Court Judegements and Summaries for Machine Text Summarization}, |
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authors = {Busani Ndlovu, Luke Jordan}, |
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year = {2021} |
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} |
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""" |
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_DESCRIPTION = """\ |
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Court Summaries and Judgements (CoSuJu) |
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""" |
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_URL = 'https://github.com/FRTNX/ml-data-scraper/blob/main/dataset/' |
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_URLS = { |
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'train': _URL + 'mini-train-v1.0.json' |
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} |
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class CosujuConfig(datasets.BuilderConfig): |
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"""BuilderConfig for COSUJU.""" |
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def __init__(self, **kwargs): |
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"""BuilderConfig for COSUJU. |
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Args: |
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**kwargs: keyword arguments forwarded to super. |
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""" |
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super(CosujuConfig, self).__init__(**kwargs) |
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class Cosuju(datasets.GeneratorBasedBuilder): |
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"""COSUJU: The Court Summaries and Judgements Dataset. Version 1.0.0""" |
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BUILDER_CONFIGS = [ |
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CosujuConfig( |
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name='plain_text', |
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version=datasets.Version('1.0.0', ''), |
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description='Plain text', |
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), |
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] |
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def _info(self): |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=datasets.Features( |
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{ |
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'id': datasets.Value('string'), |
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'title': datasets.Value('string'), |
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'url': datasets.Value('string'), |
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'year': datasets.Value('string'), |
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'update_date': datasets.Value('string'), |
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'summary_document': datasets.features.Sequence( |
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{ |
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'filename': datasets.Value('string'), |
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'file_url': datasets.Value('string'), |
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'file_content': datasets.Value('string') |
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} |
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), |
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'judgement_document': datasets.features.Sequence( |
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{ |
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'filename': datasets.Value('string'), |
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'file_url': datasets.Value('string'), |
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'file_content': datasets.Value('string') |
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} |
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), |
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} |
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), |
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supervised_keys=None, |
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homepage='https://github.com/FRTNX/ml-data-scraper', |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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downloaded_files = dl_manager.download_and_extract(_URLS) |
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return [ |
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={'filepath': downloaded_files['train']}), |
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] |
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def _generate_examples(self, filepath): |
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"""This function returns the examples in the raw (text) form.""" |
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logger.info('generating examples from = %s', filepath) |
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with open(filepath, encoding="utf-8") as f: |
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for id_, row in enumerate(f): |
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data = json.loads(row) |
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result = { |
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'id': data['id'], |
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'title': data['title'], |
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'url': data['url'], |
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'year': data['year'], |
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'update_date': data['update_date'] |
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} |
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for prop in ['summary_document', 'judgement_document']: |
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if data[prop]: |
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result[prop] = data[prop] |
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else: |
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result[prop] = { 'filename': '', 'file_url': '', 'file_content': '' } |
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yield id_, result |
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