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# LBox Open
# Copyright (c) 2022-present LBox Co. Ltd.
# CC BY-NC 4.0
# 2022.10.18, Wonseok: Add casename_classification_plus, statute_classification_plus, summarization_plus datasets
import json
import datasets
_CASENAME_CLASSIFICATION_FEATURES = {
"id": datasets.Value("int64"),
"casetype": datasets.Value("string"),
"casename": datasets.Value("string"),
"facts": datasets.Value("string"),
}
_STATUTE_CLASSIFICATION_FEATURES = {
"id": datasets.Value("int64"),
"casetype": datasets.Value("string"),
"casename": datasets.Value("string"),
"statutes": datasets.features.Sequence(datasets.Value("string")),
"facts": datasets.Value("string"),
}
_LJP_CRIMINAL = {
"id": datasets.Value("int64"),
"casetype": datasets.Value("string"),
"casename": datasets.Value("string"),
"facts": datasets.Value("string"),
"reason": datasets.Value("string"),
"label": {
"text": datasets.Value("string"),
"fine_lv": datasets.Value("int64"),
"imprisonment_with_labor_lv": datasets.Value("int64"),
"imprisonment_without_labor_lv": datasets.Value("int64"),
},
"ruling": {
"text": datasets.Value("string"),
"parse": {
"fine": {
"type": datasets.Value("string"),
"unit": datasets.Value("string"),
"value": datasets.Value("int64"),
},
"imprisonment": {
"type": datasets.Value("string"),
"unit": datasets.Value("string"),
"value": datasets.Value("int64"),
},
},
},
}
_LJP_CIVIL = {
"id": datasets.Value("int64"),
"casetype": datasets.Value("string"),
"casename": datasets.Value("string"),
"facts": datasets.Value("string"),
"claim_acceptance_lv": datasets.Value("int64"),
"gist_of_claim": {
"text": datasets.Value("string"),
"money": {
"provider": datasets.Value("string"),
"taker": datasets.Value("string"),
"unit": datasets.Value("string"),
"value": datasets.Value("int64"),
},
},
"ruling": {
"text": datasets.Value("string"),
"money": {
"provider": datasets.Value("string"),
"taker": datasets.Value("string"),
"unit": datasets.Value("string"),
"value": datasets.Value("int64"),
},
"litigation_cost": datasets.Value("float32"),
},
}
_SUMMARIZATION_FEATURES = {
"id": datasets.Value("int64"),
"summary": datasets.Value("string"),
"precedent": datasets.Value("string"),
}
_PRECEDENT_CORPUS_FEATURES = {
"id": datasets.Value("int64"),
"precedent": datasets.Value("string"),
}
class LBoxOpenConfig(datasets.BuilderConfig):
"""BuilderConfig for OpenLBox."""
def __init__(
self,
features,
data_url,
citation,
url,
label_classes=("False", "True"),
**kwargs,
):
# Version history:
# 0.1.0: Initial version.
super(LBoxOpenConfig, self).__init__(
version=datasets.Version("0.2.0"), **kwargs
)
self.features = features
self.label_classes = label_classes
self.data_url = data_url
self.citation = citation
self.url = url
class LBoxOpen(datasets.GeneratorBasedBuilder):
"""The Legal AI Benchmark dataset from Korean Legal Cases."""
BUILDER_CONFIGS = [
LBoxOpenConfig(
name="casename_classification",
description="",
features=_CASENAME_CLASSIFICATION_FEATURES,
data_url="https://lbox-open.s3.ap-northeast-2.amazonaws.com/precedent_benchmark_dataset/casename_classification/v0.1.2/",
citation="",
url="lbox.kr",
),
LBoxOpenConfig(
name="casename_classification_plus",
description="",
features=_CASENAME_CLASSIFICATION_FEATURES,
data_url="https://lbox-open.s3.ap-northeast-2.amazonaws.com/precedent_benchmark_dataset/casename_classification/v0.1.2_plus/",
citation="",
url="lbox.kr",
),
LBoxOpenConfig(
name="statute_classification",
description="",
features=_STATUTE_CLASSIFICATION_FEATURES,
data_url="https://lbox-open.s3.ap-northeast-2.amazonaws.com/precedent_benchmark_dataset/statute_classification/v0.1.2/",
citation="",
url="lbox.kr",
),
LBoxOpenConfig(
name="statute_classification_plus",
description="",
features=_STATUTE_CLASSIFICATION_FEATURES,
data_url="https://lbox-open.s3.ap-northeast-2.amazonaws.com/precedent_benchmark_dataset/statute_classification/v0.1.2_plus/",
citation="",
url="lbox.kr",
),
LBoxOpenConfig(
name="ljp_criminal",
description="",
features=_LJP_CRIMINAL,
data_url="https://lbox-open.s3.ap-northeast-2.amazonaws.com/precedent_benchmark_dataset/judgement_prediction/v0.1.2/criminal/",
citation="",
url="lbox.kr",
),
LBoxOpenConfig(
name="ljp_civil",
description="",
features=_LJP_CIVIL,
data_url="https://lbox-open.s3.ap-northeast-2.amazonaws.com/precedent_benchmark_dataset/judgement_prediction/v0.1.2/civil/",
citation="",
url="lbox.kr",
),
LBoxOpenConfig(
name="summarization",
description="",
features=_SUMMARIZATION_FEATURES,
data_url="https://lbox-open.s3.ap-northeast-2.amazonaws.com/precedent_benchmark_dataset/summarization/v0.1.0/",
citation="",
url="lbox.kr",
),
LBoxOpenConfig(
name="summarization_plus",
description="",
features=_SUMMARIZATION_FEATURES,
data_url="https://lbox-open.s3.ap-northeast-2.amazonaws.com/precedent_benchmark_dataset/summarization/v0.1.0_plus/",
citation="",
url="lbox.kr",
),
LBoxOpenConfig(
name="precedent_corpus",
description="",
features=_PRECEDENT_CORPUS_FEATURES,
data_url="https://lbox-open.s3.ap-northeast-2.amazonaws.com/precedent_benchmark_dataset/case_corpus/v0.1.0/",
citation="",
url="lbox.kr",
),
]
def _info(self):
return datasets.DatasetInfo(
description="",
features=datasets.Features(self.config.features),
homepage=self.config.url,
citation="",
)
def _split_generators(self, dl_manager):
if self.config.name == "precedent_corpus":
dl_dir = {
"train": dl_manager.download_and_extract(
f"{self.config.data_url}case_corpus-150k.jsonl"
)
or "",
}
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"data_file": dl_dir["train"],
"split": datasets.Split.TRAIN,
},
)
]
elif self.config.name in [
"casename_classification",
"statute_classification",
"ljp_criminal",
"ljp_civil",
]:
dl_dir = {
"train": dl_manager.download_and_extract(
f"{self.config.data_url}train.jsonl"
)
or "",
"valid": dl_manager.download_and_extract(
f"{self.config.data_url}valid.jsonl"
)
or "",
"test": dl_manager.download_and_extract(
f"{self.config.data_url}test.jsonl"
)
or "",
"test2": dl_manager.download_and_extract(
f"{self.config.data_url}test2.jsonl"
)
or "",
}
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"data_file": dl_dir["train"],
"split": datasets.Split.TRAIN,
},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={
"data_file": dl_dir["valid"],
"split": datasets.Split.VALIDATION,
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"data_file": dl_dir["test"],
"split": datasets.Split.TEST,
},
),
datasets.SplitGenerator(
name="test2",
gen_kwargs={
"data_file": dl_dir["test2"],
"split": "test2",
},
),
]
else:
dl_dir = {
"train": dl_manager.download_and_extract(
f"{self.config.data_url}train.jsonl"
)
or "",
"valid": dl_manager.download_and_extract(
f"{self.config.data_url}valid.jsonl"
)
or "",
"test": dl_manager.download_and_extract(
f"{self.config.data_url}test.jsonl"
)
or "",
}
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"data_file": dl_dir["train"],
"split": datasets.Split.TRAIN,
},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={
"data_file": dl_dir["valid"],
"split": datasets.Split.VALIDATION,
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"data_file": dl_dir["test"],
"split": datasets.Split.TEST,
},
),
]
def _generate_examples(self, data_file, split):
with open(data_file, encoding="utf-8") as f:
for line in f:
row = json.loads(line)
yield row["id"], row