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malindo_morph.py

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+from pathlib import Path
+from typing import Dict, List, Tuple
+
+import datasets
+
+from seacrowd.utils.configs import SEACrowdConfig
+from seacrowd.utils.constants import Licenses
+
+_CITATION = """\
+@InProceedings{NOMOTO18.8,
+  author = {Hiroki Nomoto ,Hannah Choi ,David Moeljadi and Francis Bond},
+  title = {MALINDO Morph: Morphological dictionary and analyser for Malay/Indonesian},
+  booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)},
+  year = {2018},
+  month = {may},
+  date = {7-12},
+  location = {Miyazaki, Japan},
+  editor = {Kiyoaki Shirai},
+  publisher = {European Language Resources Association (ELRA)},
+  address = {Paris, France},
+  isbn = {979-10-95546-24-5},
+  language = {english}
+  }
+"""
+
+
+_DATASETNAME = "malindo_morph"
+
+_DESCRIPTION = """\
+MALINDO Morph is a morphological dictionary for Malay (bahasa Melayu) and Indonesian (bahasa Indonesia) language.
+It contains over 200,000 lines, with each containing an analysis for one (case-sensitive) token.
+Each line is made up of the following six items, separated by tabs: root, surface form, prefix, suffix, circumfix, reduplication.
+"""
+
+_HOMEPAGE = "https://github.com/matbahasa/MALINDO_Morph"
+
+_LANGUAGES = ["zlm", "ind"]  # We follow ISO639-3 language code (https://iso639-3.sil.org/code_tables/639/data)
+
+_LICENSE = Licenses.CC_BY_4_0.value  # example: Licenses.MIT.value, Licenses.CC_BY_NC_SA_4_0.value, Licenses.UNLICENSE.value, Licenses.UNKNOWN.value
+
+_LOCAL = False
+
+_URLS = {
+    _DATASETNAME: "https://raw.githubusercontent.com/matbahasa/MALINDO_Morph/master/malindo_dic_2023.tsv",
+}
+
+_SUPPORTED_TASKS = []
+
+_SOURCE_VERSION = "2023.0.0"
+
+_SEACROWD_VERSION = "2024.06.20"
+
+
+class MalindoMorph(datasets.GeneratorBasedBuilder):
+    """MALINDO Morph is a morphological dictionary for Malay (bahasa Melayu) and Indonesian (bahasa Indonesia) language. It provides morphological information (root, prefix, suffix, circumfix, reduplication) for over 200,000 surface forms."""
+
+    SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
+    SEACROWD_VERSION = datasets.Version(_SEACROWD_VERSION)
+
+    BUILDER_CONFIGS = [
+        SEACrowdConfig(
+            name=f"{_DATASETNAME}_source",
+            version=SOURCE_VERSION,
+            description=f"{_DATASETNAME} source schema",
+            schema="source",
+            subset_id=f"{_DATASETNAME}",
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = f"{_DATASETNAME}_source"
+
+    def _info(self) -> datasets.DatasetInfo:
+        if self.config.schema == "source":
+            features = datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "root": datasets.Value("string"),
+                    "bentuk_jadian": datasets.Value("string"),
+                    "prefix": datasets.Value("string"),
+                    "suffix": datasets.Value("string"),
+                    "circumfix": datasets.Value("string"),
+                    "reduplication": datasets.Value("string"),
+                    "source": datasets.Value("string"),
+                    "stem": datasets.Value("string"),
+                    "lemma": datasets.Value("string"),
+                }
+            )
+
+        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."""
+        urls = _URLS[_DATASETNAME]
+        file = dl_manager.download_and_extract(urls)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": file,
+                    "split": "train",
+                },
+            )
+        ]
+
+    def _generate_examples(self, filepath: Path, split: str) -> Tuple[int, Dict]:
+        """Yields examples as (key, example) tuples."""
+        rows = []
+        with open(filepath, encoding="utf8") as file:
+            for line in file:
+                row = line.split("\t")
+                row[-1] = row[-1].split("\n")[0] # remove newlines from lemma feature
+                rows.append(row)
+
+        if self.config.schema == "source":
+            for key, row in enumerate(rows):
+                example = {"id": row[0], "root": row[1], "bentuk_jadian": row[2], "prefix": row[3], "suffix": row[4], "circumfix": row[5], "reduplication": row[6], "source": row[7], "stem": row[8], "lemma": row[9]}
+                yield key, example