Add data and code

janes_tag.py

@@ -0,0 +1,154 @@
+# 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 = """
+"""
+_HOMEPAGE = ''
+_LICENSE = ''
+
+_URL = 'https://huggingface.co/datasets/classla/janes_tag/raw/main/data.zip'
+_TRAINING_FILE = 'train_all.conllup'
+_DEV_FILE = 'dev_all.conllup'
+_TEST_FILE = 'test_all.conllup'
+_DATA_DIR = 'data'
+
+
+class JanesTag(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version('1.0.0')
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name='janes_tag',
+            version=VERSION,
+            description=''
+        )
+    ]
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                'sent_id': datasets.Value('string'),
+                'tokens': datasets.Sequence(datasets.Value('string')),
+                'norms': datasets.Sequence(datasets.Value('string')),
+                'lemmas': datasets.Sequence(datasets.Value('string')),
+                'xpos_tags': datasets.Sequence(datasets.Value('string')),
+                'feats': datasets.Sequence(datasets.Value('string')),
+                'upos_tags': datasets.Sequence(
+                    datasets.features.ClassLabel(
+                        names=[
+                            'SCONJ VERB', 'NOUN', 'NOUN NOUN', 'CCONJ SCONJ', 'ADV X', 'ADJ', 'NOUN NUM', 'ADP VERB',
+                            'CCONJ', 'SCONJ AUX', 'VERB', 'PRON PRON', 'CCONJ PART', 'ADV ADJ', 'PRON AUX', 'AUX AUX',
+                            'VERB ADP', 'DET ADJ', 'ADJ NOUN', 'PART PART', 'ADV AUX', 'NOUN ADV', 'PART CCONJ',
+                            'DET NOUN', 'CCONJ CCONJ', 'ADV', 'NUM', 'AUX NUM', 'ADV DET', 'ADV ADV', 'PRON VERB',
+                            'ADP PRON', 'DET AUX', 'VERB ADV', 'PROPN PROPN', 'NOUN PROPN', 'ADJ ADP', 'PART AUX',
+                            'PROPN NOUN', 'PROPN ADV', 'ADP NOUN', 'NUM ADV', 'NOUN ADJ', 'SCONJ', 'PART NOUN',
+                            'ADV NUM', 'VERB PRON', 'PART ADJ', 'AUX', 'ADP NUM', 'PRON', 'ADP ADJ', 'INTJ', 'ADV VERB',
+                            'NOUN SYM', 'PART', 'ADV PART', 'DET VERB', 'SCONJ PART', 'ADV SCONJ', 'NOUN CCONJ',
+                            'NUM DET', 'ADP X', 'INTJ X', 'NOUN VERB', 'PUNCT', 'ADP', 'ADV CCONJ', 'NOUN DET',
+                            'X NOUN', 'DET', 'PROPN X', 'SYM', 'PROPN NUM', 'PART VERB', 'SYM INTJ', 'ADP ADV',
+                            'X PROPN', 'X X', 'PROPN', 'ADP DET', 'X', 'AUX ADV', 'NUM NOUN'
+                        ]
+                    )
+                )
+            }
+        )
+
+        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 = os.path.join(dl_manager.download_and_extract(_URL), _DATA_DIR)
+
+        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 = []
+            norms = []
+            lemmas = []
+            xpos_tags = []
+            feats = []
+            upos_tags = []
+            data_id = 0
+            for line in f:
+                if line and line != '\n' and not line.startswith('# global.columns'):
+                    if line.startswith('# sent_id'):
+                        if tokens:
+                            yield data_id, {
+                                'sent_id': sent_id,
+                                'tokens': tokens,
+                                'norms': norms,
+                                'lemmas': lemmas,
+                                'xpos_tags': xpos_tags,
+                                'feats': feats,
+                                'upos_tags': upos_tags
+                            }
+                            tokens = []
+                            norms = []
+                            lemmas = []
+                            xpos_tags = []
+                            feats = []
+                            upos_tags = []
+                            data_id += 1
+                        sent_id = line.split(' = ')[1].strip()
+                    else:
+                        splits = line.split('\t')
+                        tokens.append(splits[1].strip())
+                        norms.append(splits[2].strip())
+                        lemmas.append(splits[3].strip())
+                        upos_tags.append(splits[4].strip())
+                        xpos_tags.append(splits[5].strip())
+                        feats.append(splits[6].strip())
+
+            yield data_id, {
+                'sent_id': sent_id,
+                'tokens': tokens,
+                'norms': norms,
+                'lemmas': lemmas,
+                'xpos_tags': xpos_tags,
+                'feats': feats,
+                'upos_tags': upos_tags
+            }