Create arman-ner.py

arman-ner.py

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+import csv
+from ast import literal_eval
+
+import datasets
+
+logger = datasets.logging.get_logger(__name__)
+
+_CITATION = """
+@inproceedings{poostchi-etal-2018-bilstm,
+    title = "{B}i{LSTM}-{CRF} for {P}ersian Named-Entity Recognition {A}rman{P}erso{NERC}orpus: the First Entity-Annotated {P}ersian Dataset",
+    author = "Poostchi, Hanieh  and
+      Zare Borzeshi, Ehsan  and
+      Piccardi, Massimo",
+    booktitle = "Proceedings of the Eleventh International Conference on Language Resources and Evaluation ({LREC} 2018)",
+    month = may,
+    year = "2018",
+    address = "Miyazaki, Japan",
+    publisher = "European Language Resources Association (ELRA)",
+    url = "https://aclanthology.org/L18-1701",
+}
+"""
+
+_DESCRIPTION = """"""
+
+_DOWNLOAD_URLS = {
+    "train": "https://huggingface.co/datasets/hezarai/arman-ner/resolve/main/arman-ner_train.csv",
+    "test": "https://huggingface.co/datasets/hezarai/arman-ner/resolve/main/arman-ner_test.csv",
+}
+
+
+class ArmanNERConfig(datasets.BuilderConfig):
+    def __init__(self, **kwargs):
+        super(ArmanNERConfig, self).__init__(**kwargs)
+
+
+class ArmanNER(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [
+        ArmanNERConfig(
+            name="Arman-NER",
+            version=datasets.Version("1.0.0"),
+            description=_DESCRIPTION,
+        ),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "tokens": datasets.Sequence(datasets.Value("string")),
+                    "ner_tags": datasets.Sequence(
+                        datasets.features.ClassLabel(
+                            names=[
+                                "O",
+                                "B-pro",
+                                "I-pro",
+                                "B-pers",
+                                "I-pers",
+                                "B-org",
+                                "I-org",
+                                "B-loc",
+                                "I-loc",
+                                "B-fac",
+                                "I-fac",
+                                "B-event",
+                                "I-event"
+                            ]
+                        )
+                    ),
+                }
+            ),
+            homepage="https://huggingface.co/datasets/hezarai/arman-ner",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """
+        Return SplitGenerators.
+        """
+
+        train_path = dl_manager.download_and_extract(_DOWNLOAD_URLS["train"])
+        test_path = dl_manager.download_and_extract(_DOWNLOAD_URLS["test"])
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_path}
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST, gen_kwargs={"filepath": test_path}
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        logger.info("⏳ Generating examples from = %s", filepath)
+        with open(filepath, encoding="utf-8") as csv_file:
+            csv_reader = csv.reader(
+                csv_file, quotechar='"', skipinitialspace=True
+            )
+
+            next(csv_reader, None)
+
+            for id_, row in enumerate(csv_reader):
+                tokens, ner_tags = row
+                # Optional preprocessing here
+                tokens = literal_eval(tokens)
+                ner_tags = literal_eval(ner_tags)
+                yield id_, {"tokens": tokens, "ner_tags": ner_tags}