def converter(config):
data_types = config['data']['split'].keys()
features = ['sents', 'arcs', 'rels', 'pos', 'cpos', 'stag']
for feature in features:
for data_type in data_types:
input_file = os.path.join(config['data']['base_dir'], config['data']['split'][data_type])
predicted_list = config['data']['split'][data_type].split('_')
if feature in predicted_list:
else:
output_file = os.path.join(config['data']['base_dir'], feature, data_type+'.txt')
if not os.path.isdir(os.path.dirname(output_file)):
os.makedirs(os.path.dirname(output_file))
if feature == 'sents':
index = 1
elif feature == 'predicted_pos':
index = 4
elif feature == 'predicted_cpos':
index = 3
elif feature == 'predicted_stag':
index = 10
elif feature == 'rels':
index = 7
elif feature == 'arcs':
index = 6
conllu2sents(index, input_file, output_file)
######### main ##########
if __name__ == '__main__':
print('The input file name tells you which is predicted')
converter(config_file)
def converter(config):
data_types = config['data']['split'].keys()
features = ['sents', 'gold_pos', 'gold_stag']
for feature in features:
for data_type in data_types:
input_file = os.path.join(config['data']['base_dir'],
config['data']['split'][data_type])
output_file = os.path.join(config['data']['base_dir'], feature,
data_type + '.txt')
if not os.path.isdir(os.path.dirname(output_file)):
os.makedirs(os.path.dirname(output_file))
if feature == 'sents':
index = 1
elif feature == 'gold_pos':
index = 4
elif feature == 'gold_stag':
index = 10
conllu2sents(index, input_file, output_file)