add base file

legaleval_rr.py

@@ -0,0 +1,133 @@
+import json
+
+import datasets
+
+logger = datasets.logging.get_logger(__name__)
+
+# TODO: Add BibTeX citation
+# Find for instance the citation on arxiv or on the dataset repo/website
+_CITATION = """\
+@InProceedings{huggingface:dataset,
+title = {A great new dataset},
+author={huggingface, Inc.
+},
+year={2020}
+}
+"""
+
+# TODO: Add description of the dataset here
+# You can copy an official description
+_DESCRIPTION = """\
+SemEval 2023 Task LegalEval
+"""
+
+# TODO: Add a link to an official homepage for the dataset here
+_HOMEPAGE = ""
+
+# TODO: Add the licence for the dataset here if you can find it
+_LICENSE = ""
+
+# TODO: Add link to the official dataset URLs here
+# The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
+# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
+_URLS = ""
+
+
+class LegalevalRrConfig(datasets.BuilderConfig):
+    """BuilderConfig for Multiconer2"""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig for Multiconer2.
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(LegalevalRrConfig, self).__init__(**kwargs)
+
+
+class LegalevalRr(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.0.0")
+
+    # This is an example of a dataset with multiple configurations.
+    # If you don't want/need to define several sub-sets in your dataset,
+    # just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes.
+
+    # If you need to make complex sub-parts in the datasets with configurable options
+    # You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig
+    # BUILDER_CONFIG_CLASS = MyBuilderConfig
+
+    # You will be able to load one or the other configurations in the following list with
+    # data = datasets.load_dataset('my_dataset', 'first_domain')
+    # data = datasets.load_dataset('my_dataset', 'second_domain')
+    BUILDER_CONFIGS = [
+        LegalevalRrConfig(name="it", version=VERSION),
+        LegalevalRrConfig(name="cl", version=VERSION),
+        LegalevalRrConfig(name="all", version=VERSION),
+    ]
+
+    DEFAULT_CONFIG_NAME = "all"
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("uint32"),
+                    "annotation_id": datasets.Value("string"),
+                    "text": datasets.Value("string"),
+                    "label":
+                        datasets.features.ClassLabel(
+                            names=[
+                                'NONE',
+                                "RPC",
+                                "RATIO",
+                                "PRE_NOT_RELIED",
+                                "PRE_RELIED",
+                                "STA",
+                                "ANALYSIS",
+                                "ARG_RESPONDENT",
+                                "ARG_PETITIONER",
+                                "ISSUE",
+                                "RLC",
+                                "FAC",
+                                "PREAMBLE"]
+                        )
+                }
+            ),
+            supervised_keys=None,
+            homepage="",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager: datasets.DownloadManager):
+        """Returns SplitGenerators."""
+
+        downloaded_files = dl_manager.download_and_extract({
+            "train": "train.json",
+            "dev": "dev.json",
+        })
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
+        ]
+
+    def _generate_examples(self, filepath):
+        logger.info("⏳ Generating examples from = %s", filepath)
+        config_name = self.config.name
+        with open(filepath, encoding="utf-8") as f:
+            data = json.load(f)
+        cnt = 0
+        for row in data:
+            meta_group = row["meta"]["group"]
+            if config_name == "it" and meta_group != "Tax":
+                continue
+            if config_name == "cl" and meta_group != "Criminal":
+                continue
+            for annotation in row["annotations"][0]['result']:
+                yield cnt, {
+                    "id": row["id"],
+                    "annotation_id": annotation["id"],
+                    "text": annotation["value"]["text"],
+                    "label": annotation["value"]["labels"][0],
+                }
+                cnt += 1