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import json
import os
import gzip
import requests
import pandas as pd
urls = {
'dev1': 'https://home.ttic.edu/~kgimpel/comsense_resources/dev1.txt.gz',
'dev2': 'https://home.ttic.edu/~kgimpel/comsense_resources/dev2.txt.gz',
'test': 'https://home.ttic.edu/~kgimpel/comsense_resources/test.txt.gz'
}
exclude = ['NotCapable', 'NotDesires']
def wget(url, cache_dir: str = './cache'):
""" wget and uncompress data_iterator """
os.makedirs(cache_dir, exist_ok=True)
filename = os.path.basename(url)
path = f'{cache_dir}/{filename}'
if os.path.exists(path):
return path.replace('.gz', '')
with open(path, "wb") as f:
r = requests.get(url)
f.write(r.content)
with gzip.open(path, 'rb') as f:
with open(path.replace('.gz', ''), 'wb') as f_write:
f_write.write(f.read())
os.remove(path)
return path.replace('.gz', '')
def read_file(file_name):
with open(file_name) as f_reader:
df = pd.DataFrame([i.split('\t') for i in f_reader.read().split('\n') if len(i) > 0],
columns=['relation', 'head', 'tail', 'flag'])
df_positive = df[df['flag'] == '1']
df_negative = df[df['flag'] == '0']
df_positive.pop('flag')
df_negative.pop('flag')
return df_positive, df_negative
if __name__ == '__main__':
test_p, test_n = read_file(wget(urls['test']))
dev1_p, dev1_n = read_file(wget(urls['dev1']))
train_p = pd.concat([test_p, dev1_p])
train_n = pd.concat([test_n, dev1_n])
with open(f'dataset/train.jsonl', 'w') as f:
for relation, df_p in train_p.groupby('relation'):
if len(df_p) < 2:
continue
if relation in exclude:
continue
df_n = train_n[train_n['relation'] == relation]
f.write(json.dumps({
'relation_type': relation,
'positives': df_p[['head', 'tail']].to_numpy().tolist(),
'negatives': df_n[['head', 'tail']].to_numpy().tolist()
}) + '\n')
dev2_p, dev2_n = read_file(wget(urls['dev2']))
with open(f'dataset/valid.jsonl', 'w') as f:
for relation, df_p in dev2_p.groupby('relation'):
if len(df_p) < 2:
continue
if relation in exclude:
continue
df_n = dev2_n[dev2_n['relation'] == relation]
f.write(json.dumps({
'relation_type': relation,
'positives': df_p[['head', 'tail']].to_numpy().tolist(),
'negatives': df_n[['head', 'tail']].to_numpy().tolist()
}) + '\n')
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