setimes_sr.py

# 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 = """SETimes_sr is a Serbian dataset annotated for morphosyntactic information and named entities.

The dataset contains 3177 training samples, 395 validation samples and 319 test samples 
across the respective data splits. Each sample represents a sentence and includes the following features:
sentence ID ('sent_id'), sentence text ('text'), list of tokens ('tokens'), list of lemmas ('lemmas'), 
list of Multext-East tags ('xpos_tags), list of UPOS tags ('upos_tags'),
list of morphological features ('feats'), and list of IOB tags ('iob_tags'). The 'upos_tags' and 'iob_tags' features
are encoded as class labels.
"""
_HOMEPAGE = ''
_LICENSE = ''

_URLs = {
    'ner': 'https://huggingface.co/datasets/classla/setimes_sr/raw/main/data_ner.zip',
    'upos': 'https://huggingface.co/datasets/classla/setimes_sr/raw/main/data_ner.zip',
    'ud': 'https://huggingface.co/datasets/classla/setimes_sr/raw/main/data_ud.zip'
}

_DATA_DIRS = {
    'ner': 'data_ner',
    'upos': 'data_ner',
    'ud': 'data_ud'
}


class SeTimesSr(datasets.GeneratorBasedBuilder):
    VERSION = datasets.Version('1.0.1')

    BUILDER_CONFIGS = [
        datasets.BuilderConfig(
            name='upos',
            version=VERSION,
            description=''
        ),
        datasets.BuilderConfig(
            name='ner',
            version=VERSION,
            description=''
        ),
        datasets.BuilderConfig(
            name='ud',
            version=VERSION,
            description=''
        )
    ]

    DEFAULT_CONFIG_NAME = 'ner'

    def _info(self):
        if self.config.name == "upos":
            features = datasets.Features(
                {
                    'sent_id': datasets.Value('string'),
                    'text': datasets.Value('string'),
                    'tokens': datasets.Sequence(datasets.Value('string')),
                    'lemmas': datasets.Sequence(datasets.Value('string')),
                    'xpos_tags': datasets.Sequence(datasets.Value('string')),
                    'upos_tags': datasets.Sequence(
                        datasets.features.ClassLabel(
                            names=[
                                'X',
                                'INTJ',
                                'VERB',
                                'PROPN',
                                'ADV',
                                'ADJ',
                                'PUNCT',
                                'PRON',
                                'DET',
                                'NUM',
                                'SYM',
                                'SCONJ',
                                'NOUN',
                                'AUX',
                                'PART',
                                'CCONJ',
                                'ADP'
                            ]
                        )
                    ),
                    'feats': datasets.Sequence(datasets.Value('string')),
                    'iob_tags': datasets.Sequence(datasets.Value('string'))
                }
            )
        elif self.config.name == "ner":
            features = datasets.Features(
                {
                    'sent_id': datasets.Value('string'),
                    'text': datasets.Value('string'),
                    'tokens': datasets.Sequence(datasets.Value('string')),
                    'lemmas': datasets.Sequence(datasets.Value('string')),
                    'xpos_tags': datasets.Sequence(datasets.Value('string')),
                    'upos_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'
                            ]
                        )
                    )
                }
            )
        else:
            features = datasets.Features(
                {
                    'sent_id': datasets.Value('string'),
                    'text': datasets.Value('string'),
                    'tokens': datasets.Sequence(datasets.Value('string')),
                    'lemmas': datasets.Sequence(datasets.Value('string')),
                    'xpos_tags': datasets.Sequence(datasets.Value('string')),
                    'upos_tags': datasets.Sequence(datasets.Value('string')),
                    'feats': datasets.Sequence(datasets.Value('string')),
                    'iob_tags': datasets.Sequence(datasets.Value('string')),
                    'uds': datasets.Sequence(
                        datasets.features.ClassLabel(
                            names=[
                                'punct', 'advmod', 'conj', 'aux', 'iobj', 'acl', 'fixed', 'vocative', 'root', 'nsubj',
                                'goeswith', 'cop', 'det', 'discourse', 'det_numgov', 'dep', 'ccomp', 'flat', 'compound',
                                'orphan', 'list', 'advcl', 'csubj', 'nummod_gov', 'case', 'obl', 'parataxis', 'amod',
                                'obj', 'cc', 'nmod', 'xcomp', 'appos', 'nummod', 'mark'
                            ]
                        )
                    )
                }
            )

        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(_URLs[self.config.name]), _DATA_DIRS[self.config.name])

        if self.config.name == 'ud':
            training_file = 'train_ner_ud.conllup'
            dev_file = 'dev_ner_ud.conllup'
            test_file = 'test_ner_ud.conllup'
        else:
            training_file = 'train_ner.conllu'
            dev_file = 'dev_ner.conllu'
            test_file = 'test_ner.conllu'

        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):
        if self.config.name == 'ud':
            with open(filepath, encoding='utf-8') as f:
                sent_id = ''
                text = ''
                tokens = []
                lemmas = []
                xpos_tags = []
                upos_tags = []
                feats = []
                iob_tags = []
                uds = []
                data_id = 0
                for line in f:
                    if line and not line == '\n' and not line.startswith('# global.columns'):
                        if line.startswith('#'):
                            if line.startswith('# sent_id'):
                                if tokens:
                                    yield data_id, {
                                        'sent_id': sent_id,
                                        'text': text,
                                        'tokens': tokens,
                                        'lemmas': lemmas,
                                        'upos_tags': upos_tags,
                                        'xpos_tags': xpos_tags,
                                        'feats': feats,
                                        'iob_tags': iob_tags,
                                        'uds': uds
                                    }
                                    tokens = []
                                    lemmas = []
                                    upos_tags = []
                                    xpos_tags = []
                                    feats = []
                                    iob_tags = []
                                    uds = []
                                    data_id += 1
                                sent_id = line.split(' = ')[1].strip()
                            elif line.startswith('# text'):
                                text = line.split(' = ')[1].strip()
                        elif not line.startswith('_'):
                            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())
                            uds.append(splits[7].strip())

                yield data_id, {
                    'sent_id': sent_id,
                    'text': text,
                    'tokens': tokens,
                    'lemmas': lemmas,
                    'upos_tags': upos_tags,
                    'xpos_tags': xpos_tags,
                    'feats': feats,
                    'iob_tags': iob_tags,
                    'uds': uds
                }
        else:
            with open(filepath, encoding='utf-8') as f:
                sent_id = ''
                text = ''
                tokens = []
                lemmas = []
                xpos_tags = []
                upos_tags = []
                feats = []
                iob_tags = []
                data_id = 0
                for line in f:
                    if line and not line == '\n':
                        if line.startswith('#'):
                            if line.startswith('# sent_id'):
                                if tokens:
                                    yield data_id, {
                                        'sent_id': sent_id,
                                        'text': text,
                                        '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()
                            elif line.startswith('# text'):
                                text = line.split(' = ')[1].strip()
                        elif not line.startswith('_'):
                            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,
                    'text': text,
                    'tokens': tokens,
                    'lemmas': lemmas,
                    'upos_tags': upos_tags,
                    'xpos_tags': xpos_tags,
                    'feats': feats,
                    'iob_tags': iob_tags
                }