| 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', | |
| 'train': "https://home.ttic.edu/~kgimpel/comsense_resources/train600k.txt.gz" | |
| } | |
| os.makedirs("dataset", exist_ok=True) | |
| 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 = df[[not i.startswith("Not") for i in df.relation]] | |
| df_positive = df[df['flag'] != '0'] | |
| 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'])) | |
| dev2_p, dev2_n = read_file(wget(urls['dev2'])) | |
| train_p, _ = read_file(wget(urls['train'])) | |
| with open(f'dataset/test.jsonl', 'w') as f: | |
| for relation, df_p in test_p.groupby('relation'): | |
| if len(df_p) < 2: | |
| continue | |
| df_n = test_n[test_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') | |
| with open(f'dataset/train.jsonl', 'w') as f: | |
| for relation, df_p in train_p.groupby('relation'): | |
| if len(df_p) < 2: | |
| continue | |
| f.write(json.dumps({ | |
| 'relation_type': relation, | |
| 'positives': df_p[['head', 'tail']].to_numpy().tolist(), | |
| 'negatives': [] | |
| }) + '\n') | |
| with open(f'dataset/valid.jsonl', 'w') as f: | |
| for relation, df_p in dev1_p.groupby('relation'): | |
| if len(df_p) < 2: | |
| continue | |
| df_n = dev1_n[dev1_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') | |
| for relation, df_p in dev2_p.groupby('relation'): | |
| if len(df_p) < 2: | |
| 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') | |