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indotacos.py

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+from pathlib import Path
+from typing import List
+
+import datasets
+
+from nusacrowd.utils.configs import NusantaraConfig
+from nusacrowd.utils.constants import Tasks
+from nusacrowd.utils import schemas
+
+import pandas as pd
+
+_CITATION = """\
+    @misc{wibisono2022indotacos,
+        title = {IndoTacos},
+        howpublished = {\\url{https://www.kaggle.com/datasets/christianwbsn/indonesia-tax-court-verdict}},
+        note = {Accessed: 2022-09-22}
+    }
+"""
+
+_LOCAL = False
+_LANGUAGES = ["ind"]  # We follow ISO639-3 language code (https://iso639-3.sil.org/code_tables/639/data)
+_DATASETNAME = "indotacos"
+
+_DESCRIPTION = """\
+Predicting the outcome or the probability of winning a legal case has always been highly attractive in legal sciences and practice.
+Hardly any dataset has been developed to analyze and accelerate the research of court verdict analysis.
+Find out what factor affects the outcome of tax court verdict using Natural Language Processing.
+"""
+
+_HOMEPAGE = "https://www.kaggle.com/datasets/christianwbsn/indonesia-tax-court-verdict"
+
+_LICENSE = "Creative Common Attribution Share-Alike 4.0 International"
+
+# For publicly available datasets you will most likely end up passing these URLs to dl_manager in _split_generators.
+# In most cases the URLs will be the same for the source and nusantara config.
+# However, if you need to access different files for each config you can have multiple entries in this dict.
+# This can be an arbitrarily nested dict/list of URLs (see below in `_split_generators` method)
+_URLS = {_DATASETNAME: {"indotacos": "https://huggingface.co/datasets/christianwbsn/indotacos/resolve/main/indonesia_tax_court_verdict.csv"}}
+
+_SUPPORTED_TASKS = [Tasks.TAX_COURT_VERDICT]
+
+_SOURCE_VERSION = "1.0.0"
+
+_NUSANTARA_VERSION = "1.0.0"
+
+
+class IndoTacos(datasets.GeneratorBasedBuilder):
+    """IndoTacos, an Indonesian Tax Court verdict summary containing 12283 tax court cases provided by perpajakan.ddtc.co.id."""
+
+    SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
+    NUSANTARA_VERSION = datasets.Version(_NUSANTARA_VERSION)
+
+    BUILDER_CONFIGS = [
+        NusantaraConfig(
+            name="indotacos_source",
+            version=SOURCE_VERSION,
+            description="indotacos source schema",
+            schema="source",
+            subset_id="indotacos",
+        ),
+        NusantaraConfig(
+            name="indotacos_nusantara_text",
+            version=NUSANTARA_VERSION,
+            description="IndoTacos Nusantara schema",
+            schema="nusantara_text",
+            subset_id="indotacos",
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = "indotacos_source"
+    labels = ["mengabulkan sebagian", "mengabulkan seluruhnya", "menolak", "lain-lain", "menambah pajak", "mengabulkan", "membetulkan"]
+
+    def _info(self) -> datasets.DatasetInfo:
+
+        if self.config.schema == "source":
+            features = datasets.Features(
+                {
+                    "id": datasets.Value("int32"),
+                    "text": datasets.Value("string"),
+                    "nomor_putusan": datasets.Value("string"),
+                    "tahun_pajak": datasets.Value("int32"),
+                    "jenis_pajak": datasets.Value("string"),
+                    "tahun_putusan": datasets.Value("int32"),
+                    "pokok_sengketa": datasets.Value("string"),
+                    "jenis_putusan": datasets.Value("string"),
+                }
+            )
+        elif self.config.schema == "nusantara_text":
+            features = schemas.text_features(self.labels)
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
+        url = _URLS["indotacos"]
+        path = dl_manager.download(url)["indotacos"]
+        data_files = {"train": path}
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": data_files["train"],
+                },
+            )
+        ]
+
+    def _generate_examples(self, filepath: Path):
+        df = pd.read_csv(filepath)
+        if self.config.schema == "source":
+            row_id = 1
+            for row in df.itertuples():
+                ex = {
+                    "id": str(row_id),
+                    "text": row.text,
+                    "nomor_putusan": row.nomor_putusan,
+                    "tahun_pajak": row.tahun_pajak,
+                    "jenis_pajak": row.jenis_pajak,
+                    "tahun_putusan": row.tahun_putusan,
+                    "pokok_sengketa": row.pokok_sengketa,
+                    "jenis_putusan": row.jenis_putusan,
+                }
+                yield row_id, ex
+                row_id += 1
+        elif self.config.schema == "nusantara_text":
+            row_id = 1
+            for row in df.itertuples():
+                ex = {
+                    "id": str(row_id),
+                    "text": {"text": row.text, "nomor_putusan": row.nomor_putusan, "tahun_pajak": row.tahun_pajak, "jenis_pajak": row.jenis_pajak, "tahun_putusan": row.tahun_putusan, "pokok_sengketa": row.pokok_sengketa},
+                    "label": row.jenis_putusan,
+                }
+                yield row_id, ex
+                row_id += 1
+        else:
+            raise ValueError(f"Invalid config: {self.config.name}")