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README.md

@@ -1,3 +1,29 @@
----
-license: cc-by-4.0
----
+---
+dataset_info:
+  features:
+  - name: text
+    dtype: string
+  - name: coarse
+    dtype:
+      class_label:
+        names:
+          '0': OTHER
+          '1': OFFENSE
+  - name: fine
+    dtype:
+      class_label:
+        names:
+          '0': OTHER
+          '1': ABUSE
+          '2': INSULT
+          '3': PROFANITY
+  splits:
+  - name: train
+    num_bytes: 826320
+    num_examples: 5009
+  - name: test
+    num_bytes: 509105
+    num_examples: 3532
+  download_size: 1282870
+  dataset_size: 1335425
+---

germeval18.py

@@ -0,0 +1,103 @@
+# Copyright 2020 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.
+"""Loader script for the GermEval 18 dataset"""
+
+
+import csv
+import json
+import os
+
+import datasets
+
+
+_CITATION = """\
+@data{data/0B5VML_2019,
+author = {Wiegand, Michael},
+publisher = {heiDATA},
+title = {{GermEval-2018 Corpus (DE)}},
+year = {2019},
+version = {V1},
+doi = {10.11588/data/0B5VML},
+url = {https://doi.org/10.11588/data/0B5VML}
+}
+"""
+
+_DESCRIPTION = """\
+This dataset comprises the training and test data (German tweets) from the GermEval 2018 Shared on Offensive Language Detection.
+"""
+
+_HOMEPAGE = "https://doi.org/10.11588/data/0B5VML"
+
+_LICENSE = "CC-BY-4.0 Deed"
+
+# The files are pulled from the official GitHub repository.
+# https://github.com/uds-lsv/GermEval-2018-Data
+# We use the hashed URL from master branch / June 3th 2024.
+_URLS = {
+    "germeval18.test.txt":  "https://raw.githubusercontent.com/uds-lsv/GermEval-2018-Data/9877472d39523effd54cd079b4c61157ed141508/germeval2018.test.txt",
+    "germeval18.train.txt": "https://raw.githubusercontent.com/uds-lsv/GermEval-2018-Data/9877472d39523effd54cd079b4c61157ed141508/germeval2018.training.txt",
+}
+
+class GermEval18Dataset(datasets.GeneratorBasedBuilder):
+    """The GermEval18 dataset"""
+
+    VERSION = datasets.Version("1.1.0")
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "text": datasets.Value("string"),
+                'coarse': datasets.ClassLabel(num_classes=2, names=['OTHER', 'OFFENSE'], names_file=None, id=None),
+                'fine': datasets.ClassLabel(num_classes=4, names=['OTHER', 'ABUSE', 'INSULT', 'PROFANITY'], names_file=None, id=None),
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        downloaded_files = dl_manager.download(_URLS)
+        print(downloaded_files)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": downloaded_files["germeval18.train.txt"],
+                    "split": "train",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "filepath": downloaded_files["germeval18.test.txt"],
+                    "split": "test"
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath, split):
+        with open(filepath, encoding="utf-8") as f:
+            for key, row in enumerate(f):
+                # Every line only has two "\t" tabs.
+                data_text, lbl_coarse, lbl_fine = row.rstrip().split("\t")
+                yield key, {
+                    "text": data_text,
+                    "coarse": lbl_coarse,
+                    "fine": lbl_fine,
+                }