| import csv |
| import json |
| import re |
| import random |
| from pathlib import Path |
|
|
| def extract_pos(hmr_text): |
| """Extracts part of speech from strings like 'word (pos)'.""" |
| if not hmr_text: |
| return hmr_text, None |
| match = re.search(r'\s*\(([^)]+)\)$', hmr_text) |
| if match: |
| pos = match.group(1) |
| hmr_clean = hmr_text[:match.start()].strip() |
| return hmr_clean, pos |
| return hmr_text.strip(), None |
|
|
| def convert(): |
| data_dir = Path('data') |
| processed_dir = Path('processed') |
| processed_dir.mkdir(exist_ok=True) |
| |
| all_data = [] |
| |
| csv_files = sorted(list(data_dir.rglob('*.csv'))) |
| |
| for csv_file in csv_files: |
| try: |
| with open(csv_file, mode='r', encoding='utf-8') as f: |
| reader = csv.DictReader(f) |
| for row in reader: |
| en = (row.get('en') or '').strip() |
| hmr = (row.get('hmr') or '').strip() |
| if not en and not hmr: |
| continue |
| |
| hmr_clean, pos = extract_pos(hmr) |
| all_data.append({ |
| 'hmr': hmr_clean, |
| 'en': en, |
| 'pos': pos |
| }) |
| except Exception as e: |
| print(f"Error processing {csv_file}: {e}") |
|
|
| |
| random.seed(42) |
| random.shuffle(all_data) |
| |
| |
| split_idx = int(len(all_data) * 0.95) |
| train_data = all_data[:split_idx] |
| test_data = all_data[split_idx:] |
| |
| |
| with open('hmar_data.json', 'w', encoding='utf-8') as f: |
| json.dump(all_data, f, indent=2, ensure_ascii=False) |
| |
| |
| def save_jsonl(data, filename): |
| with open(processed_dir / filename, 'w', encoding='utf-8') as f: |
| for entry in data: |
| f.write(json.dumps(entry, ensure_ascii=False) + '\n') |
|
|
| save_jsonl(train_data, 'train.jsonl') |
| save_jsonl(test_data, 'test.jsonl') |
| |
| print(f"Total entries: {len(all_data)}") |
| print(f"Saved {len(train_data)} to processed/train.jsonl") |
| print(f"Saved {len(test_data)} to processed/test.jsonl") |
|
|
| if __name__ == '__main__': |
| convert() |
|
|