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