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indqner.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.
+""" IndQNER 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{,
+author = {Ria Hari Gusmita, Asep Fajar Firmansyah, Khodijah Khuliyah},
+title = {{IndQNER: a NER Benchmark Dataset on Indonesian Translation of Quran}},
+url = {https://github.com/dice-group/IndQNER},
+year = {2022}
+}
+"""
+
+_LOCAL = False
+_LANGUAGES = ["ind"]
+_DATASETNAME = "IndQNER"
+_DESCRIPTION = """\
+IndQNER is a NER dataset created by manually annotating the Indonesian translation of Quran text.
+The dataset contains 18 named entity categories as follow:
+    "Allah": Allah (including synonim of Allah such as Yang maha mengetahui lagi mahabijaksana)
+    "Throne": Throne of Allah (such as 'Arasy)
+    "Artifact": Artifact (such as Ka'bah, Baitullah)
+    "AstronomicalBody": Astronomical body (such as bumi, matahari)
+    "Event": Event (such as hari akhir, kiamat)
+    "HolyBook": Holy book (such as AlQur'an)
+    "Language": Language (such as bahasa Arab
+    "Angel": Angel (such as Jibril, Mikail)
+    "Person": Person (such as Bani Israil, Fir'aun)
+    "Messenger": Messenger (such as Isa, Muhammad, Musa)
+    "Prophet": Prophet (such as Adam, Sulaiman)
+    "AfterlifeLocation": Afterlife location (such as Jahanam, Jahim, Padang Mahsyar)
+    "GeographicalLocation": Geographical location (such as Sinai, negeru Babilonia)
+    "Color": Color (such as kuning tua)
+    "Religion": Religion (such as Islam, Yahudi, Nasrani)
+    "Food": Food (such as manna, salwa)
+"""
+
+_HOMEPAGE = "https://github.com/dice-group/IndQNER"
+_LICENSE = "Unknown"
+_URLs = {
+    "train": "https://raw.githubusercontent.com/dice-group/IndQNER/master/datasets/train.txt",
+    "validation": "https://raw.githubusercontent.com/dice-group/IndQNER/master/datasets/dev.txt",
+    "test": "https://raw.githubusercontent.com/dice-group/IndQNER/master/datasets/test.txt",
+}
+_SUPPORTED_TASKS = [Tasks.NAMED_ENTITY_RECOGNITION]
+_SOURCE_VERSION = "1.0.0"
+_NUSANTARA_VERSION = "1.0.0"
+
+
+class IndqnerDataset(datasets.GeneratorBasedBuilder):
+    """IndQNER is an Named Entity Recognition benchmark dataset on a niche domain i.e. Indonesian Translation of Quran."""
+
+    label_classes = [
+        "B-Allah",
+        "B-Throne",
+        "B-Artifact",
+        "B-AstronomicalBody",
+        "B-Event",
+        "B-HolyBook",
+        "B-Language",
+        "B-Angel",
+        "B-Person",
+        "B-Messenger",
+        "B-Prophet",
+        "B-AfterlifeLocation",
+        "B-GeographicalLocation",
+        "B-Color",
+        "B-Religion",
+        "B-Food",
+        "I-Allah",
+        "I-Throne",
+        "I-Artifact",
+        "I-AstronomicalBody",
+        "I-Event",
+        "I-HolyBook",
+        "I-Language",
+        "I-Angel",
+        "I-Person",
+        "I-Messenger",
+        "I-Prophet",
+        "I-AfterlifeLocation",
+        "I-GeographicalLocation",
+        "I-Color",
+        "I-Religion",
+        "I-Food",
+        "O",
+    ]
+
+    BUILDER_CONFIGS = [
+        NusantaraConfig(
+            name="indqner_source",
+            version=datasets.Version(_SOURCE_VERSION),
+            description="NER dataset from Indonesian translation Quran source schema",
+            schema="source",
+            subset_id="indqner",
+        ),
+        NusantaraConfig(
+            name="indqner_nusantara_seq_label",
+            version=datasets.Version(_SOURCE_VERSION),
+            description="NER dataset from Indonesian translation Quran Nusantara schema",
+            schema="nusantara_seq_label",
+            subset_id="indqner",
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = "indqner_source"
+
+    def _info(self):
+        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)
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
+        train_tsv_path = Path(dl_manager.download_and_extract(_URLs["train"]))
+        validation_tsv_path = Path(dl_manager.download_and_extract(_URLs["validation"]))
+        test_tsv_path = Path(dl_manager.download_and_extract(_URLs["test"]))
+        data_files = {
+            "train": train_tsv_path,
+            "validation": validation_tsv_path,
+            "test": test_tsv_path,
+        }
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"filepath": data_files["train"]},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"filepath": data_files["validation"]},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"filepath": data_files["test"]},
+            ),
+        ]
+
+    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}")