ouroboros-trace-help / evaluate.py
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#!/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())