|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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_all.conllup' |
|
_DEV_FILE = 'dev_all.conllup' |
|
_TEST_FILE = 'test_all.conllup' |
|
_DATA_DIR = 'data' |
|
|
|
|
|
class ReldiHr(datasets.GeneratorBasedBuilder): |
|
VERSION = datasets.Version('1.0.1') |
|
|
|
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')), |
|
'norms': 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 = 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 = [] |
|
upos_tags = [] |
|
xpos_tags = [] |
|
feats = [] |
|
iob_tags = [] |
|
data_id = 0 |
|
for line in f: |
|
if line and not 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, |
|
'upos_tags': upos_tags, |
|
'xpos_tags': xpos_tags, |
|
'feats': feats, |
|
'iob_tags': iob_tags |
|
} |
|
tokens = [] |
|
norms = [] |
|
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()) |
|
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()) |
|
iob_tags.append(splits[7].strip()) |
|
|
|
yield data_id, { |
|
'sent_id': sent_id, |
|
'tokens': tokens, |
|
'norms': norms, |
|
'lemmas': lemmas, |
|
'upos_tags': upos_tags, |
|
'xpos_tags': xpos_tags, |
|
'feats': feats, |
|
'iob_tags': iob_tags |
|
} |
|
|
