| import csv |
| import json |
| import re |
| from pathlib import Path |
|
|
| ROOT = Path(__file__).resolve().parents[1] |
| RESULTS = ROOT / "results" |
| IN_PATH = RESULTS / "ollama_order_v3_raw.jsonl" |
| OUT_PATH = RESULTS / "ollama_order_v3_evidence.csv" |
|
|
|
|
| def clean_candidate(candidate: str) -> str: |
| candidate = candidate.strip() |
| candidate = candidate.replace("True", "true").replace("False", "false") |
| candidate = candidate.replace("None", "null") |
| candidate = re.sub(r'([{,]\s*)(order|confidence)\s*:', r'\1"\2":', candidate) |
| return candidate |
|
|
|
|
| def find_json_candidates(text: str): |
| text = (text or "").strip() |
| text = re.sub(r"^```(?:json)?\s*", "", text, flags=re.IGNORECASE) |
| text = re.sub(r"\s*```$", "", text) |
|
|
| fenced = re.findall(r"```(?:json)?\s*(\{.*?\})\s*```", text, flags=re.IGNORECASE | re.DOTALL) |
| for item in fenced: |
| yield item |
|
|
| objects = re.findall(r"\{[^{}]*(?:order|confidence)[^{}]*\}", text, flags=re.IGNORECASE | re.DOTALL) |
| for item in objects: |
| yield item |
|
|
| if text.startswith("{") and text.endswith("}"): |
| yield text |
|
|
|
|
| def extract_json_object(text: str): |
| for candidate in find_json_candidates(text): |
| fixed = clean_candidate(candidate) |
| try: |
| obj = json.loads(fixed) |
| except json.JSONDecodeError: |
| continue |
|
|
| if isinstance(obj, dict): |
| return obj |
|
|
| return None |
|
|
|
|
| def normalize_order(value): |
| if value is None: |
| return None |
|
|
| s = str(value).strip().upper() |
| s = s.replace("-", "_").replace(" ", "_") |
|
|
| if s in ("A_BEFORE_B", "EVENT_A_BEFORE_EVENT_B", "FORWARD", "TRUE"): |
| return "A_BEFORE_B" |
| if s in ("B_BEFORE_A", "EVENT_B_BEFORE_EVENT_A", "BACKWARD", "FALSE"): |
| return "B_BEFORE_A" |
| if s in ("UNCLEAR", "AMBIGUOUS", "UNKNOWN", "UNDETERMINED", "NEUTRAL"): |
| return "UNCLEAR" |
|
|
| return None |
|
|
|
|
| def normalize_confidence(value): |
| if isinstance(value, str): |
| lower = value.strip().lower() |
| if lower in ("very high", "high", "strong"): |
| return 0.85 |
| if lower in ("medium", "moderate"): |
| return 0.65 |
| if lower in ("low", "weak"): |
| return 0.4 |
|
|
| try: |
| x = float(value) |
| except (TypeError, ValueError): |
| return 0.5 |
|
|
| if 1.0 < x <= 100.0: |
| x = x / 100.0 |
|
|
| return max(0.0, min(1.0, x)) |
|
|
|
|
| def order_to_supports_forward(order: str): |
| if order == "A_BEFORE_B": |
| return True |
| if order == "B_BEFORE_A": |
| return False |
| return None |
|
|
|
|
| def main(): |
| if not IN_PATH.exists(): |
| raise FileNotFoundError(f"Missing input file: {IN_PATH}") |
|
|
| latest = {} |
|
|
| with IN_PATH.open("r", encoding="utf-8") as f: |
| for line_no, line in enumerate(f, start=1): |
| if not line.strip(): |
| continue |
|
|
| record = json.loads(line) |
| try: |
| key = (record.get("scenario_id", ""), int(record.get("step", 0))) |
| except Exception: |
| continue |
|
|
| latest[key] = {**record, "_line_no": line_no} |
|
|
| rows = [] |
|
|
| for key in sorted(latest.keys()): |
| record = latest[key] |
| response = record.get("response", "") |
| parsed = extract_json_object(response) |
|
|
| parse_ok = parsed is not None |
| parse_error = "" if parse_ok else "could_not_parse_json" |
|
|
| order = None |
| supports_forward = None |
| confidence = 0.5 |
|
|
| if parse_ok: |
| order = normalize_order(parsed.get("order")) |
| confidence = normalize_confidence(parsed.get("confidence", 0.5)) |
| supports_forward = order_to_supports_forward(order) |
|
|
| if order is None: |
| parse_ok = False |
| parse_error = "missing_or_invalid_order" |
|
|
| rows.append({ |
| "scenario_id": record.get("scenario_id", ""), |
| "step": record.get("step", ""), |
| "model": record.get("model", ""), |
| "evidence": record.get("evidence", ""), |
| "order": "" if order is None else order, |
| "supports_forward": "" if supports_forward is None else str(supports_forward), |
| "confidence": confidence, |
| "parse_ok": parse_ok, |
| "parse_error": parse_error, |
| "raw_response": "" if parse_ok else response, |
| "raw_line_no": record.get("_line_no", ""), |
| }) |
|
|
| fieldnames = [ |
| "scenario_id", |
| "step", |
| "model", |
| "evidence", |
| "order", |
| "supports_forward", |
| "confidence", |
| "parse_ok", |
| "parse_error", |
| "raw_response", |
| "raw_line_no", |
| ] |
|
|
| with OUT_PATH.open("w", encoding="utf-8", newline="") as f: |
| writer = csv.DictWriter(f, fieldnames=fieldnames) |
| writer.writeheader() |
| writer.writerows(rows) |
|
|
| ok = sum(1 for r in rows if str(r["parse_ok"]).lower() == "true") |
| print(f"Saved: {OUT_PATH}") |
| print(f"Rows: {len(rows)}") |
| print(f"Parse OK: {ok}/{len(rows)}") |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|