| import json |
| import os |
| from typing import Dict, Any, List |
|
|
| OPTION_KEYS = ["A", "B", "C", "D", "E", "F"] |
|
|
|
|
| def normalize_option(option: Dict[str, Any]) -> Dict[str, str]: |
| new_option = {} |
| option = option or {} |
| for k in OPTION_KEYS: |
| new_option[k] = str(option.get(k, "")).strip() |
| return new_option |
|
|
|
|
| def normalize_item(item: Dict[str, Any], idx: int) -> Dict[str, Any]: |
| return { |
| "id": item.get("id", idx), |
| "exam_type": item.get("exam_type", ""), |
| "exam_class": item.get("exam_class", ""), |
| "exam_subject": item.get("exam_subject", ""), |
| "question": item.get("question", ""), |
| "answer": item.get("answer", ""), |
| "explanation": item.get("explanation", ""), |
| "question_type": item.get("question_type", ""), |
| "option": normalize_option(item.get("option")), |
| } |
|
|
|
|
| def clean_json(input_path: str) -> None: |
| with open(input_path, "r", encoding="utf-8") as f: |
| data: List[Dict[str, Any]] = json.load(f) |
|
|
| cleaned = [] |
| for idx, item in enumerate(data, start=1): |
| cleaned.append(normalize_item(item, idx)) |
|
|
| base, ext = os.path.splitext(input_path) |
| output_path = f"{base}-clean{ext}" |
|
|
| with open(output_path, "w", encoding="utf-8") as f: |
| json.dump(cleaned, f, ensure_ascii=False, indent=2) |
|
|
| print(f"[OK] {output_path} ({len(cleaned)} samples)") |
|
|
|
|
| if __name__ == "__main__": |
| input_files = [ |
| "CMB-Exam/CMB-train/CMB-train-merge.json", |
| "CMB-Exam/CMB-val/CMB-val-merge.json", |
| "CMB-Exam/CMB-test/CMB-test-choice-question-merge.json", |
| ] |
|
|
| for path in input_files: |
| clean_json(path) |
|
|
