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nergrit.py

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+# coding=utf-8
+# Copyright 2022 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+""" NERGrit Dataset """
+
+from pathlib import Path
+from typing import List
+
+import datasets
+
+from nusacrowd.utils import schemas
+from nusacrowd.utils.common_parser import load_conll_data
+from nusacrowd.utils.configs import NusantaraConfig
+from nusacrowd.utils.constants import Tasks
+
+_CITATION = """\
+@misc{Fahmi_NERGRIT_CORPUS_2019,
+author = {Fahmi, Husni and Wibisono, Yudi and Kusumawati, Riyanti},
+title = {{NERGRIT CORPUS}},
+url = {https://github.com/grit-id/nergrit-corpus},
+year = {2019}
+}
+"""
+
+_LOCAL = False
+_LANGUAGES = ["ind"]  # We follow ISO639-3 language code (https://iso639-3.sil.org/code_tables/639/data)
+_DATASETNAME = "nergrit"
+_DESCRIPTION = """\
+Nergrit Corpus is a dataset collection of Indonesian Named Entity Recognition (NER), Statement Extraction,
+and Sentiment Analysis developed by PT Gria Inovasi Teknologi (GRIT).
+The Named Entity Recognition contains 18 entities as follow:
+    'CRD': Cardinal
+    'DAT': Date
+    'EVT': Event
+    'FAC': Facility
+    'GPE': Geopolitical Entity
+    'LAW': Law Entity (such as Undang-Undang)
+    'LOC': Location
+    'MON': Money
+    'NOR': Political Organization
+    'ORD': Ordinal
+    'ORG': Organization
+    'PER': Person
+    'PRC': Percent
+    'PRD': Product
+    'QTY': Quantity
+    'REG': Religion
+    'TIM': Time
+    'WOA': Work of Art
+    'LAN': Language
+"""
+
+_HOMEPAGE = "https://github.com/grit-id/nergrit-corpus"
+_LICENSE = "MIT"
+_URL = "https://github.com/cahya-wirawan/indonesian-language-models/raw/master/data/nergrit-corpus_20190726_corrected.tgz"
+_SUPPORTED_TASKS = [Tasks.NAMED_ENTITY_RECOGNITION]
+_SOURCE_VERSION = "1.0.0"
+_NUSANTARA_VERSION = "1.0.0"
+
+
+class NergritDataset(datasets.GeneratorBasedBuilder):
+    """Indonesian Named Entity Recognition from https://github.com/grit-id/nergrit-corpus."""
+
+    label_classes = {
+        "ner": [
+            "B-CRD",
+            "B-DAT",
+            "B-EVT",
+            "B-FAC",
+            "B-GPE",
+            "B-LAN",
+            "B-LAW",
+            "B-LOC",
+            "B-MON",
+            "B-NOR",
+            "B-ORD",
+            "B-ORG",
+            "B-PER",
+            "B-PRC",
+            "B-PRD",
+            "B-QTY",
+            "B-REG",
+            "B-TIM",
+            "B-WOA",
+            "I-CRD",
+            "I-DAT",
+            "I-EVT",
+            "I-FAC",
+            "I-GPE",
+            "I-LAN",
+            "I-LAW",
+            "I-LOC",
+            "I-MON",
+            "I-NOR",
+            "I-ORD",
+            "I-ORG",
+            "I-PER",
+            "I-PRC",
+            "I-PRD",
+            "I-QTY",
+            "I-REG",
+            "I-TIM",
+            "I-WOA",
+            "O",
+        ],
+        "sentiment": ["B-POS", "B-NEG", "B-NET", "I-POS", "I-NEG", "I-NET", "O"],
+        "statement": ["B-BREL", "B-FREL", "B-STAT", "B-WHO", "I-BREL", "I-FREL", "I-STAT", "I-WHO", "O"],
+    }
+    BUILDER_CONFIGS = [
+        NusantaraConfig(
+            name=f"nergrit_{task}_source",
+            version=datasets.Version(_SOURCE_VERSION),
+            description="NERGrit source schema",
+            schema="source",
+            subset_id=f"nergrit_{task}",
+        )
+        for task in label_classes
+    ]
+    BUILDER_CONFIGS += [
+        NusantaraConfig(
+            name=f"nergrit_{task}_nusantara_seq_label",
+            version=datasets.Version(_SOURCE_VERSION),
+            description="NERGrit Nusantara schema",
+            schema="nusantara_seq_label",
+            subset_id=f"nergrit_{task}",
+        )
+        for task in label_classes
+    ]
+
+    DEFAULT_CONFIG_NAME = "nergrit_ner_source"
+
+    def _info(self):
+        features = None
+        task = self.config.subset_id.split("_")[-1]
+        if self.config.schema == "source":
+            features = datasets.Features({"index": datasets.Value("string"), "tokens": [datasets.Value("string")], "ner_tag": [datasets.Value("string")]})
+        elif self.config.schema == "nusantara_seq_label":
+            features = schemas.seq_label_features(self.label_classes[task])
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
+        task = self.config.subset_id.split("_")[-1]
+        archive = Path(dl_manager.download_and_extract(_URL))
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"filepath": archive / f"nergrit-corpus/{task}/data/train_corrected.txt"},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"filepath": archive / f"nergrit-corpus/{task}/data/test_corrected.txt"},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"filepath": archive / f"nergrit-corpus/{task}/data/valid_corrected.txt"},
+            ),
+        ]
+
+    def _generate_examples(self, filepath: Path):
+        conll_dataset = load_conll_data(filepath)
+
+        if self.config.schema == "source":
+            for index, row in enumerate(conll_dataset):
+                ex = {"index": str(index), "tokens": row["sentence"], "ner_tag": row["label"]}
+                yield index, ex
+        elif self.config.schema == "nusantara_seq_label":
+            for index, row in enumerate(conll_dataset):
+                ex = {"id": str(index), "tokens": row["sentence"], "labels": row["label"]}
+                yield index, ex
+        else:
+            raise ValueError(f"Invalid config: {self.config.name}")