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reldi_hr.py

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+# coding=utf-8
+# 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.
+
+
+import os
+
+import datasets
+
+
+_CITATION = ''
+_DESCRIPTION = """The dataset contains 6339 training samples, 815 validation samples and 785 test samples. 
+Each sample represents a sentence and includes the following features: sentence ID ('sent_id'), 
+list of tokens ('tokens'), list of lemmas ('lemmas'), list of UPOS tags ('upos_tags'), 
+list of Multext-East tags ('xpos_tags), list of morphological features ('feats'), 
+and list of IOB tags ('iob_tags'), which are encoded as class labels.
+"""
+_HOMEPAGE = ''
+_LICENSE = ''
+
+_URL = 'https://huggingface.co/datasets/classla/reldi_hr/raw/main/data.zip'
+_TRAINING_FILE = 'train_ner.conllu'
+_DEV_FILE = 'dev_ner.conllu'
+_TEST_FILE = 'test_ner.conllu'
+
+
+class ReldiHr(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version('1.0.0')
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name='reldi_hr',
+            version=VERSION,
+            description=''
+        )
+    ]
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                'sent_id': datasets.Value('string'),
+                'tokens': datasets.Sequence(datasets.Value('string')),
+                'lemmas': datasets.Sequence(datasets.Value('string')),
+                'upos_tags': datasets.Sequence(datasets.Value('string')),
+                'xpos_tags': datasets.Sequence(datasets.Value('string')),
+                'feats': datasets.Sequence(datasets.Value('string')),
+                'iob_tags': datasets.Sequence(
+                    datasets.features.ClassLabel(
+                        names=[
+                            'I-org',
+                            'B-misc',
+                            'B-per',
+                            'B-deriv-per',
+                            'B-org',
+                            'B-loc',
+                            'I-deriv-per',
+                            'I-misc',
+                            'I-loc',
+                            'I-per',
+                            'O'
+                        ]
+                    )
+                )
+            }
+        )
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        data_dir = dl_manager.download_and_extract(_URL)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN, gen_kwargs={
+                    'filepath': os.path.join(data_dir, _TRAINING_FILE),
+                    'split': 'train'}
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION, gen_kwargs={
+                    'filepath': os.path.join(data_dir, _DEV_FILE),
+                    'split': 'dev'}
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST, gen_kwargs={
+                    'filepath': os.path.join(data_dir, _TEST_FILE),
+                    'split': 'test'}
+            ),
+        ]
+
+    def _generate_examples(self, filepath, split):
+        with open(filepath, encoding='utf-8') as f:
+            sent_id = ''
+            tokens = []
+            lemmas = []
+            upos_tags = []
+            xpos_tags = []
+            feats = []
+            iob_tags = []
+            data_id = 0
+            for line in f:
+                if line and not line == '\n':
+                    if line.startswith('# sent_id'):
+                        if tokens:
+                            yield data_id, {
+                                'sent_id': sent_id,
+                                'tokens': tokens,
+                                'lemmas': lemmas,
+                                'upos_tags': upos_tags,
+                                'xpos_tags': xpos_tags,
+                                'feats': feats,
+                                'iob_tags': iob_tags
+                            }
+                            tokens = []
+                            lemmas = []
+                            upos_tags = []
+                            xpos_tags = []
+                            feats = []
+                            iob_tags = []
+                            data_id += 1
+                        sent_id = line.split(' = ')[1].strip()
+                    else:
+                        splits = line.split('\t')
+                        tokens.append(splits[1].strip())
+                        lemmas.append(splits[2].strip())
+                        upos_tags.append(splits[3].strip())
+                        xpos_tags.append(splits[4].strip())
+                        feats.append(splits[5].strip())
+                        iob_tags.append(splits[9].strip())
+
+            yield data_id, {
+                'sent_id': sent_id,
+                'tokens': tokens,
+                'lemmas': lemmas,
+                'upos_tags': upos_tags,
+                'xpos_tags': xpos_tags,
+                'feats': feats,
+                'iob_tags': iob_tags
+            }