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import datasets
import pandas as pd
import os
class Vua20(datasets.GeneratorBasedBuilder):
BUILDER_CONFIG_CLASS=datasets.BuilderConfig
def _info(self):
if self.config.name == 'default':
feature = {
'id':datasets.Value('int32'),
'sent_id':datasets.Value('string'),
'word_index': datasets.Value('int32'),
'tokens':datasets.Sequence(datasets.Value('string')),
'label':datasets.ClassLabel(num_classes=2, names=['Not Metaphor', 'Is Metaphor']),
'pos':datasets.Value('string')
}
elif self.config.name == 'combined':
feature = {
'sent_id':datasets.Value('string'),
'is_target': datasets.Sequence(datasets.ClassLabel(num_classes=2)),
'tokens':datasets.Sequence(datasets.Value('string')),
'labels': datasets.Sequence(datasets.ClassLabel(num_classes=2)),
'pos_tags':datasets.Sequence(datasets.Value('string'))
}
return datasets.DatasetInfo(
description='Vua metaphor detection datasets.',
features=datasets.Features(feature),
config_name=self.config.name
)
def _split_generators(self, dl_manager):
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={'filepath': dl_manager.download('train.tsv')}),
datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={'filepath': dl_manager.download('test.tsv')}),
]
def _generate_examples(self, filepath):
df = pd.read_csv(filepath, sep='\t')
if self.config.name == 'default':
for index, row in df.iterrows():
yield index, {
'id': index,
'sent_id': row['index'],
'tokens': row['sentence'].split(),
'word_index': row['w_index'],
'label': row['label'],
'pos': row['POS']
}
elif self.config.name == 'combined':
for index, (sent_id, group) in enumerate(df.groupby('index')):
tokens = group.iloc[0]['sentence'].split()
is_target = [1 if i in group.w_index.values else 0 for i in range(len(tokens))]
labels = [1 if is_target[i] and group.label.iloc[sum(is_target[:i+1])-1] else 0 for i in range(len(tokens))]
pos_tags = [group.POS.iloc[sum(is_target[:i+1])-1] if is_target[i] else '_' for i in range(len(tokens))]
yield index, {
'sent_id': sent_id,
'tokens': tokens,
'is_target': is_target,
'labels': labels,
'pos_tags': pos_tags
} |