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import json |
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import datasets |
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from pathlib import Path |
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_DESCRIPTION = "OpenExempt is a diagnostic benchmark for legal reasoning in language models." |
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_HOMEPAGE = "https://github.com/servantez/OpenExempt" |
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_LICENSE = "CC BY 4.0" |
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_VERSION = datasets.Version("1.0.0") |
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_CITATION = """ |
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@misc{servantez2026openexemptdiagnosticbenchmarklegal, |
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title={OpenExempt: A Diagnostic Benchmark for Legal Reasoning and a Framework for Creating Custom Benchmarks on Demand}, |
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author={Sergio Servantez and Sarah B. Lawsky and Rajiv Jain and Daniel W. Linna Jr. and Kristian Hammond}, |
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year={2026}, |
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eprint={2601.13183}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL}, |
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url={https://arxiv.org/abs/2601.13183}, |
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} |
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""" |
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_SUITES = { |
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"advanced_competency": { |
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"archive": "data/advanced_competency.tar.gz", |
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"description": "Advanced Competency Suite." |
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}, |
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"basic_competency": { |
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"archive": "data/basic_competency.tar.gz", |
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"description": "Basic Competency Suite." |
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}, |
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"intermediate_competency": { |
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"archive": "data/intermediate_competency.tar.gz", |
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"description": "Intermediate Competency Suite." |
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}, |
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"asset_scaling": { |
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"archive": "data/asset_scaling.tar.gz", |
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"description": "Asset Scaling Suite." |
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}, |
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"temporal_reasoning": { |
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"archive": "data/temporal_reasoning.tar.gz", |
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"description": "Temporal Reasoning Suite." |
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}, |
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"reasoning_decomposition": { |
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"archive": "data/reasoning_decomposition.tar.gz", |
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"description": "Reasoning Decomposition Suite." |
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}, |
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"baseline_robustness": { |
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"archive": "data/baseline_robustness.tar.gz", |
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"description": "Baseline Robustness Suite." |
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}, |
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"distractor_robustness": { |
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"archive": "data/distractor_robustness.tar.gz", |
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"description": "Distractor Robustness Suite." |
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}, |
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"obfuscation_robustness": { |
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"archive": "data/obfuscation_robustness.tar.gz", |
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"description": "Obfuscation Robustness Suite." |
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}, |
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"sycophancy_robustness": { |
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"archive": "data/sycophancy_robustness.tar.gz", |
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"description": "Sycophancy Robustness Suite." |
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}, |
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} |
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def read_json(path: Path): |
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with path.open("r", encoding="utf-8") as file: |
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return json.load(file) |
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def read_jsonl_file(path: Path): |
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with path.open("r", encoding="utf-8") as file: |
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return [json.loads(line) for line in file if line.strip()] |
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class OpenExemptConfig(datasets.BuilderConfig): |
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def __init__(self, suite, **kwargs): |
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if suite == "all": |
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description = _DESCRIPTION |
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archives = [info["archive"] for info in _SUITES.values()] |
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else: |
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info = _SUITES[suite] |
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description = f"OpenExempt: {info['description']}" |
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archives = [info["archive"]] |
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super(OpenExemptConfig, self).__init__( |
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name=suite, |
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description=description, |
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version=_VERSION, |
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**kwargs) |
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self.suite = suite |
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self.archives = archives |
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class OpenExempt(datasets.GeneratorBasedBuilder): |
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BUILDER_CONFIG_CLASS = OpenExemptConfig |
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BUILDER_CONFIGS = [ |
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OpenExemptConfig(suite=suite) |
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for suite in ["all"] + list(_SUITES.keys()) |
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] |
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DEFAULT_CONFIG_NAME = "all" |
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def _info(self): |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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homepage=_HOMEPAGE, |
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license=_LICENSE, |
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citation=_CITATION, |
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features=datasets.Features( |
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{ |
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"id": datasets.Value("string"), |
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"prompt": datasets.Value("string"), |
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"solution": datasets.Value("string"), |
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"config": datasets.Value("string"), |
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"case": datasets.Value("string") |
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} |
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), |
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) |
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def _split_generators(self, dl_manager): |
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extracted_paths = dl_manager.download_and_extract(self.config.archives) |
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dataset_dirs = [] |
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for extracted_path in extracted_paths: |
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suite_dir = next(Path(extracted_path).iterdir()) |
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for dataset_dir in suite_dir.iterdir(): |
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if dataset_dir.is_dir(): |
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dataset_dirs.append(str(dataset_dir)) |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.VALIDATION, |
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gen_kwargs={ |
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"dataset_dirs": dataset_dirs, |
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"split": "dev", |
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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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"dataset_dirs": dataset_dirs, |
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"split": "test", |
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}, |
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), |
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] |
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def _generate_examples(self, dataset_dirs, split): |
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for dataset_dir in dataset_dirs: |
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dataset_dir = Path(dataset_dir) |
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config = read_json(dataset_dir / "config.json") |
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shared = read_json(dataset_dir / "shared.json") |
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examples = read_jsonl_file(dataset_dir / f"{split}.jsonl") |
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case_file_name = 'cases' if split == 'test' else f'{split}_cases' |
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cases = read_jsonl_file(dataset_dir / f'{case_file_name}.jsonl') |
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if len(examples) != len(cases): |
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raise ValueError(f"Number of examples and cases do not match for dataset: {dataset_dir}") |
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for example, case in zip(examples, cases): |
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uid = example["uid"] |
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prompt_inputs = [ |
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shared["instruction"], |
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shared["meta_instruction"], |
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shared["response_format"], |
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example["facts"], |
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example.get("solved_steps"), |
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shared["statutes"], |
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shared["format_reminder"] |
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] |
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prompt = '\n\n'.join(filter(None, prompt_inputs)) |
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solution = example["solution"] |
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if isinstance(solution, dict): |
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solution = json.dumps(solution, sort_keys=True) |
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yield uid, { |
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"id": uid, |
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"prompt": prompt, |
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"solution": solution, |
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"config": json.dumps(config, sort_keys=True), |
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"case": json.dumps(case, sort_keys=True) |
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} |
