#!/usr/bin/env python3 """Score model answers for the trace-help dataset. The parsing and matching rules below were fixed before any model was run and have not been changed since. Grading is blind: `judge` receives only the accepted answers and the answer text, never the setting the answer came from. Usage: evaluate.py data/test.jsonl answers.jsonl `answers.jsonl` — one JSON object per line: {"id": "orders-1", "setting": "with_trace", "repeat": 1, "output": "..."} `setting` is either "no_trace" or "with_trace". """ from __future__ import annotations import json import random import re import statistics import sys from pathlib import Path ABSTAIN = ("не знаю", "неизвестно", "нельзя определить", "недостаточно", "i don't know", "unknown", "cannot be determined") NUMBER = re.compile(r"-?\d+") SETTINGS = ("no_trace", "with_trace") def tidy(text: str) -> str: text = text.strip().strip("«»\"'`").strip().rstrip(".") return " ".join(text.lower().split()) def extract(raw: str) -> str | None: """The last line containing ОТВЕТ: — everything after the colon.""" found = None for line in raw.splitlines(): if "ОТВЕТ:" in line.upper() or "ответ:" in line: found = line.split(":", 1)[1] if ":" in line else line return found def judge(accepted: list[str], raw: str) -> str: """correct / abstain / wrong. Sees only accepted answers and the text.""" said = extract(raw) if said is None: return "wrong" said = tidy(said) if any(word in said for word in ABSTAIN): return "abstain" for want in accepted: want = tidy(want) if said == want: return "correct" if want in ("да", "нет") and said.startswith(want): return "correct" if NUMBER.fullmatch(want) and NUMBER.findall(said) == [want]: return "correct" return "wrong" def bootstrap(groups: list[list[tuple[str, str]]], rounds: int = 10000) -> dict: """95% interval, resampling whole programs with replacement.""" rnd = random.Random(20260830) n = len(groups) keep = {k: [] for k in ("no_trace", "with_trace", "difference", "wrong_no_trace", "wrong_with_trace", "wrong_difference")} for _ in range(rounds): flat = [item for _ in range(n) for item in groups[rnd.randrange(n)]] for setting in SETTINGS: mine = [v for s, v in flat if s == setting] keep[setting].append(sum(v == "correct" for v in mine) / len(mine)) keep["wrong_" + setting].append( sum(v == "wrong" for v in mine) / len(mine)) keep["difference"].append(keep["with_trace"][-1] - keep["no_trace"][-1]) keep["wrong_difference"].append( keep["wrong_with_trace"][-1] - keep["wrong_no_trace"][-1]) out = {} for key, values in keep.items(): values.sort() out[key] = (values[int(0.025 * rounds)], values[int(0.975 * rounds)]) return out def pct(x: float) -> str: return f"{100 * x:.1f} %" def main() -> int: rows = [json.loads(l) for l in Path(sys.argv[1]).read_text( encoding="utf-8").splitlines() if l.strip()] answers = [json.loads(l) for l in Path(sys.argv[2]).read_text( encoding="utf-8").splitlines() if l.strip()] accepted = {r["id"]: r["answers"] for r in rows} kind = {r["id"]: r["question_kind"] for r in rows} language = {r["id"]: r["language"] for r in rows} program = {r["id"]: r["program"] for r in rows} # --- blind part: only question id and answer text go in ----------------- blind = [(i, a["id"], a["output"]) for i, a in enumerate(answers)] random.Random(1).shuffle(blind) verdicts = {i: judge(accepted[qid], text) for i, qid, text in blind} # --- from here on the setting may be looked at -------------------------- for i, a in enumerate(answers): a["verdict"] = verdicts[i] def share(rows_, verdict): return sum(r["verdict"] == verdict for r in rows_) / len(rows_) if rows_ else 0.0 print(f"answers: {len(answers)}; questions: {len(accepted)}; " f"programs: {len(set(program.values()))}; " f"repeats: {len({a.get('repeat', 1) for a in answers})}") print() print("| setting | correct | confidently wrong | abstained | answers |") print("|---|---|---|---|---|") for setting in SETTINGS: mine = [a for a in answers if a["setting"] == setting] print(f"| {setting} | {pct(share(mine, 'correct'))} | " f"{pct(share(mine, 'wrong'))} | {pct(share(mine, 'abstain'))} | " f"{len(mine)} |") groups = [] for prog in sorted(set(program.values())): ids = {q for q, p in program.items() if p == prog} groups.append([(a["setting"], a["verdict"]) for a in answers if a["id"] in ids]) band = bootstrap(groups) print() print("95% intervals (10 000 resamples over programs):") print(f" correct, no trace {pct(band['no_trace'][0])} … {pct(band['no_trace'][1])}") print(f" correct, with trace {pct(band['with_trace'][0])} … {pct(band['with_trace'][1])}") print(f" difference {pct(band['difference'][0])} … {pct(band['difference'][1])}") print(f" confidently wrong, difference {pct(band['wrong_difference'][0])} … " f"{pct(band['wrong_difference'][1])}") repeats = sorted({a.get("repeat", 1) for a in answers}) if len(repeats) > 1: print() print("| repeat | no trace | with trace |") print("|---|---|---|") per = {} for rep in repeats: line = [share([a for a in answers if a.get("repeat", 1) == rep and a["setting"] == s], "correct") for s in SETTINGS] per[rep] = line print(f"| {rep} | {pct(line[0])} | {pct(line[1])} |") for idx, title in enumerate(SETTINGS): vals = [v[idx] for v in per.values()] print(f" {title}: range {pct(min(vals))} … {pct(max(vals))}, " f"standard deviation {pct(statistics.stdev(vals))}") for title, table in (("language", language), ("question kind", kind)): print() print(f"| {title} | correct, no trace | correct, with trace | answers each |") print("|---|---|---|---|") for value in sorted(set(table.values())): ids = {q for q, v in table.items() if v == value} line = [[a for a in answers if a["id"] in ids and a["setting"] == s] for s in SETTINGS] print(f"| {value} | {pct(share(line[0], 'correct'))} | " f"{pct(share(line[1], 'correct'))} | {len(line[0])} |") return 0 if __name__ == "__main__": raise SystemExit(main())