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etos.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.
+
+from pathlib import Path
+from typing import Dict, List, Tuple
+
+import conllu
+import datasets
+
+from seacrowd.utils import schemas
+from seacrowd.utils.configs import SEACrowdConfig
+from seacrowd.utils.constants import Licenses, Tasks
+
+_CITATION = """\
+@INPROCEEDINGS{10053062,
+  author={Samsuri, Mukhlizar Nirwan and Yuliawati, Arlisa and Alfina, Ika},
+  booktitle={2022 5th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)},
+  title={A Comparison of Distributed, PAM, and Trie Data Structure Dictionaries in Automatic Spelling Correction for Indonesian Formal Text},
+  year={2022},
+  pages={525-530},
+  keywords={Seminars;Dictionaries;Data structures;Intelligent systems;Information technology;automatic spelling correction;distributed dictionary;non-word error;trie data structure;Partition Around Medoids},
+  doi={10.1109/ISRITI56927.2022.10053062},
+  url = {https://ieeexplore.ieee.org/document/10053062},
+}
+"""
+
+_DATASETNAME = "etos"
+
+_DESCRIPTION = """\
+ETOS (Ejaan oTOmatiS) is a dataset for parts-of-speech (POS) tagging for formal Indonesian
+text. It consists of 200 sentences, with 4,323 tokens in total, annotated following the
+CoNLL format.
+"""
+
+_HOMEPAGE = "https://github.com/ir-nlp-csui/etos"
+
+_LANGUAGES = ["ind"]
+
+_LICENSE = Licenses.AGPL_3_0.value
+
+_LOCAL = False
+
+_URLS = "https://raw.githubusercontent.com/ir-nlp-csui/etos/main/gold_standard.conllu"
+
+_SUPPORTED_TASKS = [Tasks.POS_TAGGING]
+
+_SOURCE_VERSION = "1.0.0"
+
+_SEACROWD_VERSION = "2024.06.20"
+
+
+class ETOSDataset(datasets.GeneratorBasedBuilder):
+    """
+    ETOS is an Indonesian parts-of-speech (POS) tagging dataset from https://github.com/ir-nlp-csui/etos.
+    """
+
+    SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
+    SEACROWD_VERSION = datasets.Version(_SEACROWD_VERSION)
+
+    UPOS_TAGS = [
+        "NOUN",
+        "PUNCT",
+        "ADP",
+        "NUM",
+        "SYM",
+        "SCONJ",
+        "ADJ",
+        "PART",
+        "DET",
+        "CCONJ",
+        "PROPN",
+        "PRON",
+        "X",
+        "_",
+        "ADV",
+        "INTJ",
+        "VERB",
+        "AUX",
+    ]
+
+    BUILDER_CONFIGS = [
+        SEACrowdConfig(
+            name=f"{_DATASETNAME}_source",
+            version=datasets.Version(_SOURCE_VERSION),
+            description=f"{_DATASETNAME} source schema",
+            schema="source",
+            subset_id=f"{_DATASETNAME}",
+        ),
+        SEACrowdConfig(
+            name=f"{_DATASETNAME}_seacrowd_seq_label",
+            version=datasets.Version(_SOURCE_VERSION),
+            description=f"{_DATASETNAME} sequence labeling schema",
+            schema="seacrowd_seq_label",
+            subset_id=f"{_DATASETNAME}",
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = f"{_DATASETNAME}_source"
+
+    def _info(self) -> datasets.DatasetInfo:
+        if self.config.schema == "source":
+            features = datasets.Features(
+                {
+                    "sent_id": datasets.Value("string"),
+                    "text": datasets.Value("string"),
+                    "tokens": datasets.Sequence(datasets.Value("string")),
+                    "lemmas": datasets.Sequence(datasets.Value("string")),
+                    "upos": datasets.Sequence(datasets.features.ClassLabel(names=self.UPOS_TAGS)),
+                    "xpos": datasets.Sequence(datasets.Value("string")),
+                    "feats": datasets.Sequence(datasets.Value("string")),
+                    "head": datasets.Sequence(datasets.Value("string")),
+                    "deprel": datasets.Sequence(datasets.Value("string")),
+                    "deps": datasets.Sequence(datasets.Value("string")),
+                    "misc": datasets.Sequence(datasets.Value("string")),
+                }
+            )
+
+        elif self.config.schema == "seacrowd_seq_label":
+            features = schemas.seq_label_features(self.UPOS_TAGS)
+
+        else:
+            raise ValueError(f"Invalid schema: '{self.config.schema}'")
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
+        """
+        Returns SplitGenerators.
+        """
+
+        train_path = dl_manager.download_and_extract(_URLS)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": train_path,
+                    "split": "train",
+                },
+            )
+        ]
+
+    def _generate_examples(self, filepath: Path, split: str) -> Tuple[int, Dict]:
+        """
+        Yields examples as (key, example) tuples.
+        """
+
+        with open(filepath, "r", encoding="utf-8") as data_file:
+            tokenlist = list(conllu.parse_incr(data_file))
+
+        for idx, sent in enumerate(tokenlist):
+            if "sent_id" in sent.metadata:
+                sent_id = sent.metadata["sent_id"]
+            else:
+                sent_id = idx
+
+            tokens = [token["form"] for token in sent]
+
+            if "text" in sent.metadata:
+                txt = sent.metadata["text"]
+            else:
+                txt = " ".join(tokens)
+
+            if self.config.schema == "source":
+                yield idx, {
+                    "sent_id": str(sent_id),
+                    "text": txt,
+                    "tokens": tokens,
+                    "lemmas": [token["lemma"] for token in sent],
+                    "upos": [token["upos"] for token in sent],
+                    "xpos": [token["xpos"] for token in sent],
+                    "feats": [str(token["feats"]) for token in sent],
+                    "head": [str(token["head"]) for token in sent],
+                    "deprel": [str(token["deprel"]) for token in sent],
+                    "deps": [str(token["deps"]) for token in sent],
+                    "misc": [str(token["misc"]) for token in sent],
+                }
+
+            elif self.config.schema == "seacrowd_seq_label":
+                yield idx, {
+                    "id": str(sent_id),
+                    "tokens": tokens,
+                    "labels": [token["upos"] for token in sent],
+                }
+
+            else:
+                raise ValueError(f"Invalid schema: '{self.config.schema}'")