Datasets:
SuzanaB
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Browse files- .gitattributes +1 -0
- dev_ner.conllu +3 -0
- hr500k.py +180 -0
- test_ner.conllu +3 -0
- train_ner.conllu +3 -0
.gitattributes
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*.pb filter=lfs diff=lfs merge=lfs -text
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*.pt filter=lfs diff=lfs merge=lfs -text
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*.pth filter=lfs diff=lfs merge=lfs -text
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*.pb filter=lfs diff=lfs merge=lfs -text
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*.pt filter=lfs diff=lfs merge=lfs -text
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*.pth filter=lfs diff=lfs merge=lfs -text
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*.conllu filter=lfs diff=lfs merge=lfs -text
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dev_ner.conllu
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version https://git-lfs.github.com/spec/v1
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oid sha256:5d3ea0605657af9721b5e2eea04e0ea4510a764c503b09879826d5b254807345
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size 2770096
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hr500k.py
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# coding=utf-8
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# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
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#
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# Licensed under the Apache License, Version 2.0 (the 'License');
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an 'AS IS' BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import datasets
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_CITATION = ''
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_DESCRIPTION = """The hr500k training corpus contains about 500,000 tokens manually annotated on the levels of
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tokenisation, sentence segmentation, morphosyntactic tagging, lemmatisation and named entities.
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On the sentence level, the dataset contains 20159 training samples, 1963 validation samples and 2672 test samples
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across the respective data splits. Each sample represents a sentence and includes the following features:
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sentence ID ('sent_id'), sentence text ('text'), list of tokens ('tokens'), list of lemmas ('lemmas'),
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list of Multext-East tags ('xpos_tags), list of UPOS tags ('upos_tags'),
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list of morphological features ('feats'), and list of IOB tags ('iob_tags'). The 'upos_tags' and 'iob_tags' features
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are encoded as class labels.
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"""
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_HOMEPAGE = 'https://www.clarin.si/repository/xmlui/handle/11356/1183#'
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_LICENSE = ''
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_TRAINING_FILE = 'train_ner.conllu'
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_DEV_FILE = 'dev_ner.conllu'
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_TEST_FILE = 'test_ner.conllu'
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class Hr500K(datasets.GeneratorBasedBuilder):
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VERSION = datasets.Version('1.1.0')
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BUILDER_CONFIGS = [
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datasets.BuilderConfig(
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name='hr500k',
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version=VERSION,
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data_files=[_TRAINING_FILE, _DEV_FILE, _TEST_FILE],
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description=''
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)
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]
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def _info(self):
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features = datasets.Features(
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{
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'sent_id': datasets.Value('string'),
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'text': datasets.Value('string'),
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'tokens': datasets.Sequence(datasets.Value('string')),
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'lemmas': datasets.Sequence(datasets.Value('string')),
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'xpos_tags': datasets.Sequence(datasets.Value('string')),
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'upos_tags': datasets.Sequence(
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datasets.features.ClassLabel(
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names=[
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'X',
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'INTJ',
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'VERB',
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'PROPN',
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'ADV',
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'ADJ',
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'PUNCT',
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'PRON',
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'DET',
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'NUM',
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'SYM',
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'SCONJ',
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'NOUN',
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'AUX',
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'PART',
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'CCONJ',
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'ADP'
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]
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)
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),
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'feats': datasets.Sequence(datasets.Value('string')),
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'iob_tags': datasets.Sequence(
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datasets.features.ClassLabel(
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names=[
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'I-org',
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'B-misc',
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'B-per',
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'B-deriv-per',
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'B-org',
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'B-loc',
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'I-deriv-per',
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'I-misc',
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'I-loc',
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'I-per',
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'O'
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]
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)
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)
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}
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)
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=features,
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supervised_keys=None,
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homepage=_HOMEPAGE,
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license=_LICENSE,
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN, gen_kwargs={'filepath': _TRAINING_FILE, 'split': 'train'}
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),
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datasets.SplitGenerator(
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name=datasets.Split.VALIDATION, gen_kwargs={'filepath': _DEV_FILE, 'split': 'dev'}
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),
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datasets.SplitGenerator(
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name=datasets.Split.TEST, gen_kwargs={'filepath': _TEST_FILE, 'split': 'test'}
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),
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]
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def _generate_examples(self, filepath, split):
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with open(filepath, encoding='utf-8') as f:
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sent_id = ''
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text = ''
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tokens = []
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lemmas = []
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xpos_tags = []
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upos_tags = []
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feats = []
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iob_tags = []
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data_id = 0
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for line in f:
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if line and not line == '\n':
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if line.startswith('#'):
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if line.startswith('# sent_id'):
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if tokens:
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yield data_id, {
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'sent_id': sent_id,
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'text': text,
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'tokens': tokens,
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'lemmas': lemmas,
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'xpos_tags': xpos_tags,
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'upos_tags': upos_tags,
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'feats': feats,
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'iob_tags': iob_tags
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}
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tokens = []
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lemmas = []
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xpos_tags = []
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upos_tags = []
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feats = []
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iob_tags = []
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data_id += 1
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sent_id = line.split(' = ')[1].strip()
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elif line.startswith('# text'):
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text = line.split(' = ')[1].strip()
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elif not line.startswith('_'):
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splits = line.split('\t')
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tokens.append(splits[1].strip())
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lemmas.append(splits[2].strip())
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xpos_tags.append(splits[3].strip())
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upos_tags.append(splits[4].strip())
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feats.append(splits[5].strip())
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iob_tags.append(splits[9].strip())
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yield data_id, {
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'sent_id': sent_id,
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'text': text,
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'tokens': tokens,
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'lemmas': lemmas,
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'xpos_tags': xpos_tags,
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'upos_tags': upos_tags,
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'feats': feats,
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'iob_tags': iob_tags
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}
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test_ner.conllu
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version https://git-lfs.github.com/spec/v1
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oid sha256:dda18e6ed47510ab4de23642db8a744e99ecfac3c28d29545128bcd11b4bad2e
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size 3524103
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train_ner.conllu
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version https://git-lfs.github.com/spec/v1
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oid sha256:c248a1e78551300b3bcafcd98bdd72287adb584d8aad057ec5f719806ea75bf6
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size 28938043
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