Upload lbox_open.py

lbox_open.py

@@ -0,0 +1,142 @@
+# LBox
+import json
+import datasets
+
+_CASENAME_CLASSIFICATION_FEATURES = {
+    "id": datasets.Value("int32"),
+    "casetype": datasets.Value("string"),
+    "casename": datasets.Value("string"),
+    "facts": datasets.Value("string"),
+}
+
+_STATUTE_CLASSIFICATION_FEATURES = {
+    "id": datasets.Value("int32"),
+    "casetype": datasets.Value("string"),
+    "casename": datasets.Value("string"),
+    "statutes": datasets.features.Sequence(datasets.Value("string")),
+    "facts": datasets.Value("string"),
+}
+
+_SUMMARIZATION_CLASSIFICATION_FEATURES = {
+    "id": datasets.Value("int32"),
+    "summary": datasets.Value("string"),
+    "precedent": datasets.Value("string"),
+}
+
+_CASE_CORPUS_FEATURES = {
+    "id": datasets.Value("int32"),
+    "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("0.1.0"), **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/v0.1.0/",
+            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/v0.1.0/",
+            citation="",
+            url="lbox.kr",
+        ),
+        LBoxOpenConfig(
+            name="summarization",
+            description="",
+            features=_SUMMARIZATION_CLASSIFICATION_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="case_corpus",
+            description="",
+            features=_CASE_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 == "case_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,
+                    },
+                )
+            ]
+
+        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