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README.md

@@ -1,50 +0,0 @@
----
-license: cc-by-nc-4.0
----
-# Dataset Card for `lbox_open`
-
-## Dataset Description
-
-- **Homepage:** `https://lbox.kr`
-- **Repository:** `https://github.com/lbox-kr/lbox_open`
-- **Point of Contact:** [Wonseok Hwang](mailto:[email protected])
-
-### Dataset Summary
-
-A Legal AI Benchmark Dataset from Korean Legal Cases.
-
-### Languages
-
-Korean
-
-### How to use
-```python
-from datasets import load_dataset
-
-# casename classficiation task
-data_cn = load_dataset("lbox/lbox_open", "casename_classification")
-data_cn_plus = load_dataset("lbox/lbox_open", "casename_classification_plus")
-
-# statutes classification task
-data_st = load_dataset("lbox/lbox_open", "statute_classification")
-data_st_plus = load_dataset("lbox/lbox_open", "statute_classification_plus")
-
-# Legal judgement prediction tasks
-data_ljp_criminal = load_dataset("lbox/lbox_open", "ljp_criminal")
-data_ljp_civil = load_dataset("lbox/lbox_open", "ljp_civil")
-
-# case summarization task
-data_summ = load_dataset("lbox/lbox_open", "summarization")
-data_summ_plus = load_dataset("lbox/lbox_open", "summarization_plus")
-
-# precedent corpus
-data_corpus = load_dataset("lbox/lbox_open", "precedent_corpus")
-
-```
-
-For more information about the dataset, please visit <https://github.com/lbox-kr/lbox_open>.
-
-## Licensing Information
-Copyright 2022-present [LBox Co. Ltd.](https://lbox.kr/)
-
-Licensed under the [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/)

casename_classification/lbox_open-test.parquet

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casename_classification/lbox_open-test2.parquet

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casename_classification/lbox_open-train.parquet

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casename_classification/lbox_open-validation.parquet

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casename_classification_plus/lbox_open-validation.parquet

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lbox_open.py

@@ -1,321 +0,0 @@
-# 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

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