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import datasets |
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import json |
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import os |
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from datasets import Value, Sequence |
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_CITATION = """\ |
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@inproceedings{chalkidis-etal-2019-neural, |
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title = "Neural Legal Judgment Prediction in {E}nglish", |
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author = "Chalkidis, Ilias and |
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Androutsopoulos, Ion and |
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Aletras, Nikolaos", |
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booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics", |
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month = jul, |
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year = "2019", |
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address = "Florence, Italy", |
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publisher = "Association for Computational Linguistics", |
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url = "https://aclanthology.org/P19-1424", |
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doi = "10.18653/v1/P19-1424", |
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pages = "4317--4323", |
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} |
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""" |
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_HOMEPAGE = "https://archive.org/details/ECHR-ACL2019" |
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_DESCRIPTION = """\ |
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The ECHR Cases dataset is designed for experimentation of neural judgment prediction, as in the original 2019 ACL paper "Neural Legal Judgment Prediction in English". |
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""" |
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ARTICLES = { |
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"2": "Right to life", |
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"3": "Prohibition of torture", |
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"4": "Prohibition of slavery and forced labour", |
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"5": "Right to liberty and security", |
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"6": "Right to a fair trial", |
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"7": "No punishment without law", |
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"8": "Right to respect for private and family life", |
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"9": "Freedom of thought, conscience and religion", |
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"10": "Freedom of expression", |
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"11": "Freedom of assembly and association", |
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"12": "Right to marry", |
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"13": "Right to an effective remedy", |
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"14": "Prohibition of discrimination", |
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"15": "Derogation in time of emergency", |
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"16": "Restrictions on political activity of aliens", |
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"17": "Prohibition of abuse of rights", |
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"18": "Limitation on use of restrictions on rights", |
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"34": "Individual applications", |
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"38": "Examination of the case", |
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"39": "Friendly settlements", |
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"46": "Binding force and execution of judgments", |
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"P1-1": "Protection of property", |
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"P1-2": "Right to education", |
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"P1-3": "Right to free elections", |
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"P3-1": "Right to free elections", |
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"P4-1": "Prohibition of imprisonment for debt", |
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"P4-2": "Freedom of movement", |
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"P4-3": "Prohibition of expulsion of nationals", |
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"P4-4": "Prohibition of collective expulsion of aliens", |
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"P6-1": "Abolition of the death penalty", |
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"P6-2": "Death penalty in time of war", |
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"P6-3": "Prohibition of derogations", |
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"P7-1": "Procedural safeguards relating to expulsion of aliens", |
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"P7-2": "Right of appeal in criminal matters", |
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"P7-3": "Compensation for wrongful conviction", |
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"P7-4": "Right not to be tried or punished twice", |
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"P7-5": "Equality between spouses", |
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"P12-1": "General prohibition of discrimination", |
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"P13-1": "Abolition of the death penalty", |
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"P13-2": "Prohibition of derogations", |
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"P13-3": "Prohibition of reservations", |
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} |
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class Echr(datasets.GeneratorBasedBuilder): |
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"""ECHR dataset.""" |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig(name="non-anon", data_dir="data"), |
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datasets.BuilderConfig(name="anon", data_dir="data_anon"), |
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] |
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def _info(self): |
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features = datasets.Features( |
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{ |
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"itemid": Value(dtype="string"), |
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"languageisocode": Value(dtype="string"), |
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"respondent": Value(dtype="string"), |
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"branch": Value(dtype="string"), |
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"date": Value(dtype="int64"), |
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"docname": Value(dtype="string"), |
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"importance": Value(dtype="int64"), |
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"conclusion": Value(dtype="string"), |
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"judges": Value(dtype="string"), |
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"text": Sequence(feature=Value(dtype="string")), |
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"violated_articles": Sequence(feature=Value(dtype="string")), |
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"violated_paragraphs": Sequence(feature=Value(dtype="string")), |
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"violated_bulletpoints": Sequence(feature=Value(dtype="string")), |
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"non_violated_articles": Sequence(feature=Value(dtype="string")), |
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"non_violated_paragraphs": Sequence(feature=Value(dtype="string")), |
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"non_violated_bulletpoints": Sequence(feature=Value(dtype="string")), |
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"violated": Value(dtype="bool"), |
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} |
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) |
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return datasets.DatasetInfo( |
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features=features, |
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homepage=_HOMEPAGE, |
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description=_DESCRIPTION, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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path_prefix = self.config.data_dir |
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data_dir = dl_manager.download([os.path.join(path_prefix, f"{f}.jsonl") for f in ["train", "test", "dev"]]) |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={ |
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"filepath": data_dir[0], |
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"split": "train", |
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}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={ |
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"filepath": data_dir[1], |
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"split": "test", |
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}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.VALIDATION, |
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gen_kwargs={ |
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"filepath": data_dir[2], |
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"split": "dev", |
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}, |
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), |
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] |
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def _generate_examples(self, filepath, split): |
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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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yield id_, data |
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