Datasets:

stefan-it
/

HisGermaNER

@@ -1,113 +0,0 @@
-import datasets
-# Coming soon!
-_CITATION = ""
-_DESCRIPTION = """\
-HisGermaNER is another NER dataset from historical German newspapers.
-In the first release of our dataset, 11 newspapers from 1710 to 1840 from the Austrian National Library (ONB) are selected, resulting in 100 pages.
-"""
-class HisGermaNERConfig(datasets.BuilderConfig):
-    """BuilderConfig for HisGermaNER"""
-    def __init__(self, data_url, **kwargs):
-        super(HisGermaNERConfig, self).__init__(**kwargs)
-        self.data_url = data_url
-class HisGermaNER(datasets.GeneratorBasedBuilder):
-    BUILDER_CONFIGS = [
-        HisGermaNERConfig(
-            name="HisGermaNER",
-            version=datasets.Version("0.0.1"),
-            description="HisGermaNER Dataset",
-            data_url="https://huggingface.co/datasets/stefan-it/HisGermaNER/resolve/main/splits/HisGermaNER_v0_",
-        )
-    ]
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "id": datasets.Value("string"),
-                    "tokens": datasets.Sequence(datasets.Value("string")),
-                    "ner_tags": datasets.Sequence(
-                        datasets.features.ClassLabel(
-                            names=[
-                                "O",
-                                "B-PER",
-                                "I-PER",
-                                "B-ORG",
-                                "I-ORG",
-                                "B-LOC",
-                                "I-LOC",
-                            ]
-                        )
-                    )
-                }
-            ),
-            supervised_keys=None,
-            homepage="https://huggingface.co/datasets/stefan-it/HisGermaNER",
-            citation=_CITATION,
-        )
-    def _split_generators(self, dl_manager):
-        """Returns generator for dataset splits."""
-        download_urls = {
-            split: self.config.data_url + split + ".tsv" for split in ["train", "dev", "test"]
-        }
-        downloaded_files = dl_manager.download_and_extract(download_urls)
-        splits = [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
-            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
-            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]})
-        ]
-        return splits
-    def _generate_examples(self, filepath):
-        with open(filepath, "rt", encoding="utf-8") as f_p:
-            current_tokens = []
-            current_tags = []
-            sentence_counter = 0
-            for line in f_p:
-                line = line.strip()
-                if not line:
-                    if len(current_tokens) > 0:
-                        sentence = (
-                            sentence_counter, {
-                                "id": str(sentence_counter),
-                                "tokens": current_tokens,
-                                "ner_tags": current_tags,
-                            }
-                        )
-                        sentence_counter += 1
-                        current_tokens = []
-                        current_tags = []
-                        yield sentence
-                    continue
-                if line.startswith("TOKEN"):
-                    continue
-                if line.startswith("# "):
-                    continue
-                token, tag, misc = line.split("\t")
-                current_tokens.append(token)
-                current_tags.append(tag)
-            if len(current_tokens) > 0:
-                yield sentence_counter, {
-                    "id": str(sentence_counter),
-                    "tokens": current_tokens,
-                    "ner_tags": current_tags,
-                }