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Oleg Maslov
2026-09-02 10:10:29 +02:00
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76
benchmarks/calibration/v6-kappa-recal/_summary-v6-kappa.json Normal file
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{
"verdict": "PASS",
"k_opus_gpt": 0.847958297132928,
"k_opus_minimax": 0.8548922056384745,
"k_gpt_minimax": 0.7877758913412564,
"k_conservative_trio": 0.7877758913412564,
"minimax_parse_success": 100,
"minimax_n_total": 100,
"minimax_lat_p50_ms": 11927,
"minimax_lat_p95_ms": 31426,
"minimax_routing_errors": 0,
"minimax_retries_total": 0,
"minimax_prompt_tokens_total": 53855,
"minimax_completion_tokens_total": 48920,
"cost_actual_usd": 0.0749,
"per_cell": [
{
"cell": "no-context",
"n": 20,
"mm_parsed": 20,
"k_og": 1.0,
"k_om": 1.0,
"k_gm": 1.0
},
{
"cell": "oracle-context",
"n": 20,
"mm_parsed": 20,
"k_og": 0.7058823529411763,
"k_om": 0.7916666666666667,
"k_gm": 0.7058823529411763
},
{
"cell": "full-context",
"n": 20,
"mm_parsed": 20,
"k_og": 0.8,
"k_om": 0.7,
"k_gm": 0.7058823529411763
},
{
"cell": "retrieval",
"n": 20,
"mm_parsed": 20,
"k_og": 1.0,
"k_om": 0.8936170212765956,
"k_gm": 0.8936170212765956
},
{
"cell": "agentic",
"n": 20,
"mm_parsed": 20,
"k_og": 0.782608695652174,
"k_om": 0.8979591836734693,
"k_gm": 0.6874999999999999
}
],
"confusion_opus_gpt": {
"correct_correct": 32,
"correct_incorrect": 7,
"incorrect_correct": 0,
"incorrect_incorrect": 61
},
"confusion_opus_minimax": {
"correct_correct": 37,
"correct_incorrect": 2,
"incorrect_correct": 5,
"incorrect_incorrect": 56
},
"confusion_gpt_minimax": {
"correct_correct": 32,
"correct_incorrect": 0,
"incorrect_correct": 10,
"incorrect_incorrect": 58
}
}

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benchmarks/calibration/v6-kappa-recal/cold-probes-phase2.py Normal file
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"""
Manifest v6 Phase 2 pre-flight — cold alias probes
====================================================
Validates both v6 judge aliases are production-ready with a minimal
probe sample before any N=400 commit. 6 calls total (3 MiniMax + 3
Kimi) on the first 3 split instances from §1.3h sample.
Probes use direct HTTP to upstream endpoints (same methodology as
§1.3g / §1.3h / §1.3h-C / v6 κ re-cal). LiteLLM proxy is NOT in the
loop — isolates upstream routing/parse behavior from middleware.
Kimi backup has never been exercised in production under v6 authority;
this is the first production-class test.
Scope: §11-compliant (read-only access to frozen files; new artefact
under benchmarks/calibration/v6-kappa-recal/).
"""
from __future__ import annotations
import json
import re
import sys
import time
import urllib.error
import urllib.request
from datetime import datetime, timezone
from pathlib import Path
try:
sys.stdout.reconfigure(encoding="utf-8", errors="replace")
sys.stderr.reconfigure(encoding="utf-8", errors="replace")
except Exception:
pass
OUT_PATH = Path("D:/Projects/waggle-os/benchmarks/calibration/v6-kappa-recal/phase2-cold-probes.jsonl")
# Reuse first 3 split instances from §1.3h — they exercised both providers before
SAMPLE_PATH = Path("D:/Projects/waggle-os/benchmarks/probes/judge-swap-validation/split-cases-sample.jsonl")
JUDGE_PROMPT_TEMPLATE = "\n".join([
"You are evaluating whether an LLM's answer is correct against ground truth.",
"",
"## Question",
"{question}",
"",
"## Ground-truth answer",
"{ground_truth}",
"",
"## Ground-truth supporting context (excerpt shown to the model)",
"{context}",
"",
"## Model's answer",
"{model_answer}",
"",
"## Your task",
"",
"Step 1: Determine if the model's answer is correct.",
"- \"correct\" means the model's answer contains all required facts from ground truth, with no additional incorrect claims.",
"- Minor phrasing differences, synonyms, or alternative but equivalent formulations are acceptable.",
"- Extra detail is acceptable ONLY if it is factually correct.",
"",
"Step 2: If incorrect, assign exactly one failure mode using this decision tree:",
"",
"1. Does the model explicitly refuse or say it does not know? -> F1 (ABSTAIN)",
"2. Does the model answer a DIFFERENT question than was asked (coherent but off-topic)? -> F5 (OFF-TOPIC)",
"3. Does the model rely on entities, names, dates, or claims that do NOT appear in the ground-truth context (fabrication)? -> F4 (HALLUCINATED)",
"4. Does the model correctly state SOME required facts but miss others, without stating any incorrect facts? -> F2 (PARTIAL)",
"5. Otherwise (model states facts derived from the context but gets them wrong): -> F3 (INCORRECT)",
"",
"Step 3: Return JSON only, no prose, in this exact schema:",
"",
"{{",
" \"verdict\": \"correct\" | \"incorrect\",",
" \"failure_mode\": null | \"F1\" | \"F2\" | \"F3\" | \"F4\" | \"F5\",",
" \"rationale\": \"one sentence explaining the verdict\"",
"}}",
"",
"If verdict is \"correct\", failure_mode MUST be null.",
"If verdict is \"incorrect\", failure_mode MUST be one of F1-F5.",
])
def ts() -> str:
return datetime.now(timezone.utc).isoformat()
def logmsg(msg: str) -> None:
print(f"{ts()} {msg}", flush=True)
def load_env() -> dict[str, str]:
env_path = Path("D:/Projects/waggle-os/.env")
out: dict[str, str] = {}
for line in env_path.read_text(encoding="utf-8").splitlines():
line = line.strip()
if not line or line.startswith("#") or "=" not in line:
continue
k, _, v = line.partition("=")
out[k.strip()] = v.strip().strip('"').strip("'")
return out
def extract_json_body(raw: str) -> dict | None:
if not raw:
return None
trimmed = raw.strip()
if trimmed.startswith("```"):
m = re.match(r"^```(?:json)?\s*\n?(.*?)```\s*$", trimmed, re.DOTALL)
if m:
trimmed = m.group(1).strip()
try:
return json.loads(trimmed)
except Exception:
pass
first = trimmed.find("{")
last = trimmed.rfind("}")
if first != -1 and last != -1 and last > first:
try:
return json.loads(trimmed[first:last + 1])
except Exception:
return None
return None
def parse_verdict(raw: str) -> tuple[str | None, str | None, str | None]:
body = extract_json_body(raw)
if not isinstance(body, dict):
return (None, None, None)
v = body.get("verdict")
fm = body.get("failure_mode")
rat = body.get("rationale")
if v not in ("correct", "incorrect"):
return (None, None, None)
if fm is not None and fm not in ("F1", "F2", "F3", "F4", "F5"):
fm = None
return (v, fm, rat if isinstance(rat, str) else None)
def http_post_json(url: str, headers: dict, body: dict, timeout_s: int = 60) -> tuple[int, dict | str]:
req = urllib.request.Request(
url, data=json.dumps(body).encode("utf-8"), method="POST",
headers={"Content-Type": "application/json", **headers},
)
try:
with urllib.request.urlopen(req, timeout=timeout_s) as resp:
raw = resp.read().decode("utf-8", errors="replace")
try:
return resp.status, json.loads(raw)
except Exception:
return resp.status, raw
except urllib.error.HTTPError as e:
try:
return e.code, e.read().decode("utf-8", errors="replace")[:2000]
except Exception:
return e.code, ""
except Exception as e:
return 0, f"{type(e).__name__}: {e}"
def call_minimax(prompt: str, or_key: str) -> dict:
url = "https://openrouter.ai/api/v1/chat/completions"
headers = {"Authorization": f"Bearer {or_key}"}
body = {
"model": "minimax/minimax-m2.7",
"messages": [{"role": "user", "content": prompt}],
"temperature": 0.0,
"max_tokens": 4096,
}
started = time.time()
status, resp = http_post_json(url, headers, body)
latency = int((time.time() - started) * 1000)
if status == 200 and isinstance(resp, dict):
choices = resp.get("choices") or []
if choices:
msg = choices[0].get("message") or {}
content = msg.get("content") or msg.get("reasoning_content") or ""
usage = resp.get("usage", {})
return {
"raw_text": content,
"status": 200,
"latency_ms": latency,
"prompt_tokens": usage.get("prompt_tokens"),
"completion_tokens": usage.get("completion_tokens"),
"provider": "minimax",
"alias": "minimax-m27-via-openrouter",
"routing": "openrouter_direct_http",
"error": None,
}
return {
"raw_text": "",
"status": status,
"latency_ms": latency,
"error": str(resp)[:300],
"provider": "minimax",
"alias": "minimax-m27-via-openrouter",
"routing": "openrouter_direct_http",
"prompt_tokens": None,
"completion_tokens": None,
}
def call_kimi(prompt: str, moonshot_key: str) -> dict:
"""Kimi K2.6 via Moonshot direct intl endpoint. First production-class
run of the v6 kimi-k26-direct alias equivalent (LiteLLM proxy not in
loop; routes directly to upstream)."""
url = "https://api.moonshot.ai/v1/chat/completions"
headers = {"Authorization": f"Bearer {moonshot_key}"}
body = {
"model": "kimi-k2.6",
"messages": [{"role": "user", "content": prompt}],
"max_tokens": 4096,
}
started = time.time()
status, resp = http_post_json(url, headers, body)
latency = int((time.time() - started) * 1000)
if status == 200 and isinstance(resp, dict):
choices = resp.get("choices") or []
if choices:
msg = choices[0].get("message") or {}
content = msg.get("content") or msg.get("reasoning_content") or ""
usage = resp.get("usage", {})
return {
"raw_text": content,
"status": 200,
"latency_ms": latency,
"prompt_tokens": usage.get("prompt_tokens"),
"completion_tokens": usage.get("completion_tokens"),
"provider": "kimi",
"alias": "kimi-k26-direct",
"routing": "moonshot_direct_http",
"error": None,
}
return {
"raw_text": "",
"status": status,
"latency_ms": latency,
"error": str(resp)[:300],
"provider": "kimi",
"alias": "kimi-k26-direct",
"routing": "moonshot_direct_http",
"prompt_tokens": None,
"completion_tokens": None,
}
def main() -> int:
logmsg("[cold-probes] Phase 2 pre-flight START")
env = load_env()
or_key = env.get("OPENROUTER_API_KEY", "").strip()
moonshot_key = env.get("MOONSHOT_API_KEY", "").strip()
if not or_key or not moonshot_key:
logmsg("[cold-probes] FATAL missing keys (OR or MOONSHOT)")
return 2
sample = []
with SAMPLE_PATH.open("r", encoding="utf-8") as f:
for line in f:
line = line.strip()
if line:
sample.append(json.loads(line))
sample = sample[:3] # first 3 instances
logmsg(f"[cold-probes] loaded {len(sample)} probe instances from §1.3h split sample")
rows = []
for i, s in enumerate(sample):
prompt = JUDGE_PROMPT_TEMPLATE.format(
question=s["question"], ground_truth=s["ground_truth"],
context=s["context"], model_answer=s["model_answer"],
)
for fn, label in ((call_minimax, "minimax"), (call_kimi, "kimi")):
resp = fn(prompt, or_key if label == "minimax" else moonshot_key)
verdict, fm, rat = parse_verdict(resp["raw_text"])
rows.append({
"instance_id": s["instance_id"],
"cell": s["cell"],
"provider": resp["provider"],
"alias": resp["alias"],
"routing": resp["routing"],
"http_status": resp["status"],
"error": resp.get("error"),
"latency_ms": resp["latency_ms"],
"prompt_tokens": resp.get("prompt_tokens"),
"completion_tokens": resp.get("completion_tokens"),
"parsed_verdict": verdict,
"parsed_failure_mode": fm,
"parsed_rationale": rat,
"raw_text": resp["raw_text"],
"opus_verdict_ref": s.get("opus_verdict"),
"gpt_verdict_ref": s.get("gpt_verdict"),
})
logmsg(
f"[cold-probes] {label:7} {i+1}/3 {s['instance_id']} status={resp['status']} "
f"verdict={verdict} lat={resp['latency_ms']}ms"
)
OUT_PATH.parent.mkdir(parents=True, exist_ok=True)
with OUT_PATH.open("w", encoding="utf-8") as f:
for r in rows:
f.write(json.dumps(r, ensure_ascii=False) + "\n")
# Summary
mm_rows = [r for r in rows if r["provider"] == "minimax"]
km_rows = [r for r in rows if r["provider"] == "kimi"]
mm_parsed = sum(1 for r in mm_rows if r["parsed_verdict"] is not None)
km_parsed = sum(1 for r in km_rows if r["parsed_verdict"] is not None)
logmsg(f"[cold-probes] SUMMARY MiniMax: {mm_parsed}/3 parsed Kimi: {km_parsed}/3 parsed")
logmsg("[cold-probes] END")
return 0 if (mm_parsed == 3 and km_parsed == 3) else 3
if __name__ == "__main__":
sys.exit(main())

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benchmarks/calibration/v6-kappa-recal/kappa-sample-instances.jsonl Normal file
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{"instance_id": "locomo_conv-50_q086", "cell": "no-context", "question": "What sports activity is Calvin planning to try after the tour with Frank Ocean?", "ground_truth": "Skiing", "context": "Session 9 (3:15 pm on 21 June, 2023):\nCalvin: Nope, not yet! I haven't been there before, but it's on my to-do list for after my tour with Frank Ocean ends. Can't wait to see them in person! Look at that snowy peak. [image: a photo of a person on skis on a snowy mountain]", "model_answer": "Surfing", "opus_verdict": "incorrect", "opus_failure_mode": "F3", "gpt_verdict": "incorrect", "gpt_failure_mode": "F3", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F4"}
{"instance_id": "locomo_conv-26_q059", "cell": "no-context", "question": "Would Caroline be considered religious?", "ground_truth": "Somewhat, but not extremely religious", "context": "Session 12 (1:50 pm on 17 August, 2023):\nCaroline: Hey Mel! How're ya doin'? Recently, I had a not-so-great experience on a hike. I ran into a group of religious conservatives who said something that really upset me. It made me think how much work we still have to do for LGBTQ rights. It's been so helpful to have people around me who accept and support me, so I know I'll be ok!\n\nSession 14 (1:33 pm on 25 August, 2023):\nCaroline: Thanks! It was made for a local church and shows time changing our lives. I made it to show my own journey as a transgender woman and how we should accept growth and change. [image: a photo of a large stained glass window in a church]", "model_answer": "Cannot be determined without context.", "opus_verdict": "incorrect", "opus_failure_mode": "F1", "gpt_verdict": "incorrect", "gpt_failure_mode": "F1", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F1"}
{"instance_id": "locomo_conv-44_q000", "cell": "no-context", "question": "Which year did Audrey adopt the first three of her dogs?", "ground_truth": "2020", "context": "Session 1 (1:10 pm on 27 March, 2023):\nAudrey: I've had them for 3 years! Their names are Pepper, Precious and Panda. I can't live without my little ones!", "model_answer": "1954", "opus_verdict": "incorrect", "opus_failure_mode": "F4", "gpt_verdict": "incorrect", "gpt_failure_mode": "F4", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F4"}
{"instance_id": "locomo_conv-41_q080", "cell": "no-context", "question": "What did Maria make for her home to remind her of a trip to England?", "ground_truth": "painting of a castle on a hill", "context": "Session 8 (6:03 pm on 6 March, 2023):\nMaria: Thanks, John! I got the idea from that trip to England a few years ago - I was mesmerized by the castles. I wanted to bring that same magic to my home, like a reminder of the world's beauty. I made a painting too! [image: a photography of a painting of a castle on a hill]", "model_answer": "A wind chime", "opus_verdict": "incorrect", "opus_failure_mode": "F4", "gpt_verdict": "incorrect", "gpt_failure_mode": "F3", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F4"}
{"instance_id": "locomo_conv-42_q001", "cell": "no-context", "question": "What kind of interests do Joanna and Nate share?", "ground_truth": "Watching movies, making desserts", "context": "Session 1 (7:31 pm on 21 January, 2022):\nJoanna: Yeah! Besides writing, I also enjoy reading, watching movies, and exploring nature. Anything else you enjoy doing, Nate?\nNate: Playing video games and watching movies are my main hobbies.\nJoanna: Cool, Nate! So we both have similar interests. What type of movies do you like best?\n\nSession 3 (9:27 am on 7 February, 2022):\nNate: Thanks, Joanna. Not much has changed for me, but I just discovered that I can make coconut milk icecream and gave it a try. It was actually pretty good, so I'm proud of myself. [image: a photo of a bowl of ice cream with a spoon in it]\n\nSession 4 (1:07 pm on 25 February, 2022):\nNate: Thanks, Joanna! It means a lot that you enjoy the desserts I bake.\n\nSession 10 (11:54 am on 2 May, 2022):\nJoanna: Not much is new other than the screenplay. Been working on some projects and testing out dairy-free dessert recipes for friends and fam. Here's a pic of a cake I made recently! [image: a photo of a cake with white frosting on a wooden table]\n\nSession 20 (6:03 pm on 5 September, 2022):\nJoanna: Hey Nate! Cute turtles! Bummer about the setback. Any positive vibes comin' your way? I just revised on of my old recipes and made this! [image: a photo of a piece of cake with strawberries and chocolate]", "model_answer": "Reading", "opus_verdict": "incorrect", "opus_failure_mode": "F3", "gpt_verdict": "incorrect", "gpt_failure_mode": "F3", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F3"}
{"instance_id": "locomo_conv-43_q155", "cell": "no-context", "question": "How did John feel after being able to jog without pain?", "ground_truth": "It was a huge success.", "context": "Session 24 (3:37 pm on 16 December, 2023):\nJohn: It was great! After being out for so long, jogging without any pain was a huge success. My wife and I hosted a small get-together with friends and family to celebrate.", "model_answer": "Relieved.", "opus_verdict": "incorrect", "opus_failure_mode": "F3", "gpt_verdict": "incorrect", "gpt_failure_mode": "F3", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F4"}
{"instance_id": "locomo_conv-50_q015", "cell": "no-context", "question": "Why does Dave regularly visit parks?", "ground_truth": "because it relaxes and calms him", "context": "Session 1 (11:53 am on 23 March, 2023):\nDave: That's great, can't wait for you to return from your trip. I've been spending lots of time at this beautiful park lately - so calming. Have you been there before? [image: a photography of a park with a lake and a few boats]\n\nSession 8 (2:31 pm on 9 June, 2023):\nDave: Hey, nice photo of the studio! Working in a team yields incredible results, well done! Keep pushing it! I've been doing good - thanks for asking. I've been exploring some parks on the weekends to relax - it's so peaceful being surrounded by nature. Are there any chill spots you enjoy in Boston?", "model_answer": "Unknown.", "opus_verdict": "incorrect", "opus_failure_mode": "F1", "gpt_verdict": "incorrect", "gpt_failure_mode": "F1", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F1"}
{"instance_id": "locomo_conv-48_q020", "cell": "no-context", "question": "Which games have Jolene and her partner played together?", "ground_truth": "Detroit, Walking Dead, Battlefield 1, It Takes Two, Overcooked 2", "context": "Session 2 (9:49 am on 27 January, 2023):\nJolene: They are very unusual pets! Here's me and my partner gaming last week - it's so fun. We played the game \"Detroit\" on the console. We are both crazy about this activity! [image: a photo of a person laying in bed with a dog watching tv]\nJolene: We are planning to play \"Walking Dead\" next Saturday.\n\nSession 15 (7:37 pm on 9 July, 2023):\nJolene: Yeah, we love playing \"It takes two\" together! It's a fun team-strategy game and it's competitive. Plus, it's a great way for us to bond. Do you have any activities you like doing with people?\n\nSession 19 (12:52 am on 19 August, 2023):\nJolene: Oh, I forgot to mention Overcooked 2 - this is a good co-op game if you're into hilarious and chaotic cooking. My partner and I often play for bets! I once won three large pizzas!\n\nSession 20 (9:11 am on 21 August, 2023):\nJolene: Long time no talk! We were given a new game for the console last week, it is Battlefield 1. What's been up with you?", "model_answer": "Animal Crossing and Minecraft", "opus_verdict": "incorrect", "opus_failure_mode": "F4", "gpt_verdict": "incorrect", "gpt_failure_mode": "F4", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F4"}
{"instance_id": "locomo_conv-48_q055", "cell": "no-context", "question": "Which pet did Jolene adopt more recently - Susie or Seraphim?", "ground_truth": "Seraphim", "context": "Session 2 (9:49 am on 27 January, 2023):\nJolene: I bought it a year ago in Paris.\nJolene: Even as a child I learned to play on my own.\n\nSession 16 (9:26 am on 1 August, 2023):\nJolene: I adopted her two years ago when I was feeling lonely and wanted some company.", "model_answer": "Seraphim", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-26_q128", "cell": "no-context", "question": "What did Caroline find in her neighborhood during her walk?", "ground_truth": "a rainbow sidewalk", "context": "Session 14 (1:33 pm on 25 August, 2023):\nCaroline: I was out walking in my neighborhood when I came across this cool rainbow sidewalk for Pride Month. It was so vibrant and welcoming, I had to take a picture! It reminds us that love and acceptance are everywhere—even where we least expect it.", "model_answer": "A butterfly.", "opus_verdict": "incorrect", "opus_failure_mode": "F4", "gpt_verdict": "incorrect", "gpt_failure_mode": "F4", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F4"}
{"instance_id": "locomo_conv-50_q010", "cell": "no-context", "question": "When did Calvin's place get flooded in Tokyo?", "ground_truth": "On a week before 16 May, 2023", "context": "Session 6 (11:50 am on 16 May, 2023):\nCalvin: Hey Dave, not everything has been going smoothly. I had an incident last week where my place got flooded, but thankfully, I managed to save my music gear and favorite microphone. It's been tough, but I'm staying positive and looking forward to getting everything fixed up.", "model_answer": "October 2019", "opus_verdict": "incorrect", "opus_failure_mode": "F4", "gpt_verdict": "incorrect", "gpt_failure_mode": "F4", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F4"}
{"instance_id": "locomo_conv-50_q078", "cell": "no-context", "question": "What was the necklace Calvin received meant to remind him of?", "ground_truth": "why he keeps hustling as a musician", "context": "Session 4 (6:24 pm on 1 May, 2023):\nCalvin: Thanks, Dave! I got it from another artist as a gift - it's a great reminder of why I keep hustling as a musician!", "model_answer": "Home.", "opus_verdict": "incorrect", "opus_failure_mode": "F3", "gpt_verdict": "incorrect", "gpt_failure_mode": "F3", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F4"}
{"instance_id": "locomo_conv-47_q092", "cell": "no-context", "question": "What did John create for the charitable foundation that helped generate reports for analysis?", "ground_truth": "computer application on smartphones", "context": "Session 11 (5:00 pm on 11 May, 2022):\nJohn: Previously, this foundation used paper records and all inventory was recorded manually. I made an application that structured their work, and now everything they need for inventory is in one application on their smartphone.", "model_answer": "A database", "opus_verdict": "incorrect", "opus_failure_mode": "F3", "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F4"}
{"instance_id": "locomo_conv-30_q057", "cell": "no-context", "question": "What advice does Gina give to Jon about running a successful business?", "ground_truth": "build relationships with customers, create a strong brand image, stay positive", "context": "Session 7 (7:28 pm on 23 March, 2023):\nJon: Yeah, brand identity is key. Make sure yours stands out. Also be sure to build relationships with your customers – let them know you care. And don't forget to stay positive and motivate others. Your energy will be contagious!", "model_answer": "Focus on the customer.", "opus_verdict": "incorrect", "opus_failure_mode": "F2", "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F2"}
{"instance_id": "locomo_conv-30_q029", "cell": "no-context", "question": "Which cities has Jon visited?", "ground_truth": "Paris, Rome", "context": "Session 2 (2:32 pm on 29 January, 2023):\nJon: Hey Gina! Thanks for asking. I'm on the hunt for the ideal spot for my dance studio and it's been quite a journey! I've been looking at different places and picturing how the space would look. I even found a place with great natural light! Oh, I've been to Paris yesterday! It was sooo cool. [image: a photo of a bathroom with a blue floor and a pink wall]\n\nSession 15 (10:04 am on 19 June, 2023):\nJon: Hey Gina, hope you're doing great! Still working on my biz. Took a short trip last week to Rome to clear my mind a little.", "model_answer": "Unknown.", "opus_verdict": "incorrect", "opus_failure_mode": "F1", "gpt_verdict": "incorrect", "gpt_failure_mode": "F1", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F1"}
{"instance_id": "locomo_conv-44_q066", "cell": "no-context", "question": "What type of dog was Andrew looking to adopt based on his living space?", "ground_truth": "smaller dog", "context": "Session 5 (10:47 am on 6 May, 2023):\nAndrew: Meeting all these adorable pups has been awesome! For those considering getting a pup, the size of living space and the exercise needs of the breed are important. For me, a person living in an apartment, a smaller dog would be best, but if one is active, consider getting one that loves to play and run.", "model_answer": "A small dog", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-44_q002", "cell": "no-context", "question": "What kind of indoor activities has Andrew pursued with his girlfriend?", "ground_truth": "boardgames, volunteering at pet shelter, wine tasting, growing flowers", "context": "Session 13 (3:52 pm on 27 July, 2023):\nAndrew: Hey Audrey! How are you? My GF and I just had a great experience volunteering at a pet shelter on Monday - it was so rewarding! We loved spending time with those cute animals and it gave us so much joy. It was so rewarding, it reminded me just how much I love them!\n\nSession 19 (5:53 pm on 24 September, 2023):\nAndrew: Yeah! They really do bring so much into our lives - it's amazing to watch them interact. Here's something I've been taking care of lately. Look at those flowers! [image: a photo of a balcony with a bunch of flowers on it]\n\nSession 23 (4:22 pm on 13 October, 2023):\nAndrew: Hey Audrey, it's been a busy week for me. Last Tuesday, my gf, Toby, and I had a really awesome night playing board games. It was really nice. What's been up with you lately? [image: a photography of a dog sitting at a chess board with a chess set in front of him]\n\nSession 25 (10:14 am on 24 October, 2023):\nAndrew: Hi Audrey! How have you been lately? My girlfriend and I went to this awesome wine tasting last weekend. It was great! We tried so many unique wines and learned a lot. I was surprised at how much I enjoyed it. A reminder to step out of the comfort zone!", "model_answer": "Board games", "opus_verdict": "incorrect", "opus_failure_mode": "F2", "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F2"}
{"instance_id": "locomo_conv-47_q046", "cell": "no-context", "question": "When did John and James meet at McGee's bar?", "ground_truth": "August 27, 2022", "context": "Session 21 (9:18 pm on 26 August, 2022):\nJohn: Great, then I agree! See you tomorrow at McGee's Pub!", "model_answer": "Never", "opus_verdict": "incorrect", "opus_failure_mode": "F3", "gpt_verdict": "incorrect", "gpt_failure_mode": "F3", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F3"}
{"instance_id": "locomo_conv-43_q076", "cell": "no-context", "question": "What kind of picture did Tim share as part of their Harry Potter book collection?", "ground_truth": "MinaLima's creation from the Harry Potter films", "context": "Session 2 (5:08 pm on 15 June, 2023):\nTim: Thanks! That picture is from MinaLima. They created all the props for the Harry Potter films, and I love their work. It's like having a piece of the wizarding world at home!", "model_answer": "A selfie", "opus_verdict": "incorrect", "opus_failure_mode": "F3", "gpt_verdict": "incorrect", "gpt_failure_mode": "F4", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F4"}
{"instance_id": "locomo_conv-41_q065", "cell": "no-context", "question": "What is John's main focus in local politics?", "ground_truth": "Improving education and infrastructure", "context": "Session 1 (11:01 am on 17 December, 2022):\nJohn: I'm passionate about improving education and infrastructure in our community. Those are my main focuses.", "model_answer": "Unknown which John.", "opus_verdict": "incorrect", "opus_failure_mode": "F1", "gpt_verdict": "incorrect", "gpt_failure_mode": "F1", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F1"}
{"instance_id": "locomo_conv-50_q086", "cell": "oracle-context", "question": "What sports activity is Calvin planning to try after the tour with Frank Ocean?", "ground_truth": "Skiing", "context": "Session 9 (3:15 pm on 21 June, 2023):\nCalvin: Nope, not yet! I haven't been there before, but it's on my to-do list for after my tour with Frank Ocean ends. Can't wait to see them in person! Look at that snowy peak. [image: a photo of a person on skis on a snowy mountain]", "model_answer": "Skiing", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-26_q059", "cell": "oracle-context", "question": "Would Caroline be considered religious?", "ground_truth": "Somewhat, but not extremely religious", "context": "Session 12 (1:50 pm on 17 August, 2023):\nCaroline: Hey Mel! How're ya doin'? Recently, I had a not-so-great experience on a hike. I ran into a group of religious conservatives who said something that really upset me. It made me think how much work we still have to do for LGBTQ rights. It's been so helpful to have people around me who accept and support me, so I know I'll be ok!\n\nSession 14 (1:33 pm on 25 August, 2023):\nCaroline: Thanks! It was made for a local church and shows time changing our lives. I made it to show my own journey as a transgender woman and how we should accept growth and change. [image: a photo of a large stained glass window in a church]", "model_answer": "Yes", "opus_verdict": "incorrect", "opus_failure_mode": "F3", "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F2"}
{"instance_id": "locomo_conv-44_q000", "cell": "oracle-context", "question": "Which year did Audrey adopt the first three of her dogs?", "ground_truth": "2020", "context": "Session 1 (1:10 pm on 27 March, 2023):\nAudrey: I've had them for 3 years! Their names are Pepper, Precious and Panda. I can't live without my little ones!", "model_answer": "2020", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-41_q080", "cell": "oracle-context", "question": "What did Maria make for her home to remind her of a trip to England?", "ground_truth": "painting of a castle on a hill", "context": "Session 8 (6:03 pm on 6 March, 2023):\nMaria: Thanks, John! I got the idea from that trip to England a few years ago - I was mesmerized by the castles. I wanted to bring that same magic to my home, like a reminder of the world's beauty. I made a painting too! [image: a photography of a painting of a castle on a hill]", "model_answer": "A painting", "opus_verdict": "incorrect", "opus_failure_mode": "F2", "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F2"}
{"instance_id": "locomo_conv-42_q001", "cell": "oracle-context", "question": "What kind of interests do Joanna and Nate share?", "ground_truth": "Watching movies, making desserts", "context": "Session 1 (7:31 pm on 21 January, 2022):\nJoanna: Yeah! Besides writing, I also enjoy reading, watching movies, and exploring nature. Anything else you enjoy doing, Nate?\nNate: Playing video games and watching movies are my main hobbies.\nJoanna: Cool, Nate! So we both have similar interests. What type of movies do you like best?\n\nSession 3 (9:27 am on 7 February, 2022):\nNate: Thanks, Joanna. Not much has changed for me, but I just discovered that I can make coconut milk icecream and gave it a try. It was actually pretty good, so I'm proud of myself. [image: a photo of a bowl of ice cream with a spoon in it]\n\nSession 4 (1:07 pm on 25 February, 2022):\nNate: Thanks, Joanna! It means a lot that you enjoy the desserts I bake.\n\nSession 10 (11:54 am on 2 May, 2022):\nJoanna: Not much is new other than the screenplay. Been working on some projects and testing out dairy-free dessert recipes for friends and fam. Here's a pic of a cake I made recently! [image: a photo of a cake with white frosting on a wooden table]\n\nSession 20 (6:03 pm on 5 September, 2022):\nJoanna: Hey Nate! Cute turtles! Bummer about the setback. Any positive vibes comin' your way? I just revised on of my old recipes and made this! [image: a photo of a piece of cake with strawberries and chocolate]", "model_answer": "Movies", "opus_verdict": "incorrect", "opus_failure_mode": "F2", "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F2"}
{"instance_id": "locomo_conv-43_q155", "cell": "oracle-context", "question": "How did John feel after being able to jog without pain?", "ground_truth": "It was a huge success.", "context": "Session 24 (3:37 pm on 16 December, 2023):\nJohn: It was great! After being out for so long, jogging without any pain was a huge success. My wife and I hosted a small get-together with friends and family to celebrate.", "model_answer": "Great", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-50_q015", "cell": "oracle-context", "question": "Why does Dave regularly visit parks?", "ground_truth": "because it relaxes and calms him", "context": "Session 1 (11:53 am on 23 March, 2023):\nDave: That's great, can't wait for you to return from your trip. I've been spending lots of time at this beautiful park lately - so calming. Have you been there before? [image: a photography of a park with a lake and a few boats]\n\nSession 8 (2:31 pm on 9 June, 2023):\nDave: Hey, nice photo of the studio! Working in a team yields incredible results, well done! Keep pushing it! I've been doing good - thanks for asking. I've been exploring some parks on the weekends to relax - it's so peaceful being surrounded by nature. Are there any chill spots you enjoy in Boston?", "model_answer": "To relax", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-48_q020", "cell": "oracle-context", "question": "Which games have Jolene and her partner played together?", "ground_truth": "Detroit, Walking Dead, Battlefield 1, It Takes Two, Overcooked 2", "context": "Session 2 (9:49 am on 27 January, 2023):\nJolene: They are very unusual pets! Here's me and my partner gaming last week - it's so fun. We played the game \"Detroit\" on the console. We are both crazy about this activity! [image: a photo of a person laying in bed with a dog watching tv]\nJolene: We are planning to play \"Walking Dead\" next Saturday.\n\nSession 15 (7:37 pm on 9 July, 2023):\nJolene: Yeah, we love playing \"It takes two\" together! It's a fun team-strategy game and it's competitive. Plus, it's a great way for us to bond. Do you have any activities you like doing with people?\n\nSession 19 (12:52 am on 19 August, 2023):\nJolene: Oh, I forgot to mention Overcooked 2 - this is a good co-op game if you're into hilarious and chaotic cooking. My partner and I often play for bets! I once won three large pizzas!\n\nSession 20 (9:11 am on 21 August, 2023):\nJolene: Long time no talk! We were given a new game for the console last week, it is Battlefield 1. What's been up with you?", "model_answer": "Detroit, It Takes Two, Overcooked 2", "opus_verdict": "incorrect", "opus_failure_mode": "F2", "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F2"}
{"instance_id": "locomo_conv-48_q055", "cell": "oracle-context", "question": "Which pet did Jolene adopt more recently - Susie or Seraphim?", "ground_truth": "Seraphim", "context": "Session 2 (9:49 am on 27 January, 2023):\nJolene: I bought it a year ago in Paris.\nJolene: Even as a child I learned to play on my own.\n\nSession 16 (9:26 am on 1 August, 2023):\nJolene: I adopted her two years ago when I was feeling lonely and wanted some company.", "model_answer": "Susie", "opus_verdict": "incorrect", "opus_failure_mode": "F3", "gpt_verdict": "incorrect", "gpt_failure_mode": "F3", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F3"}
{"instance_id": "locomo_conv-26_q128", "cell": "oracle-context", "question": "What did Caroline find in her neighborhood during her walk?", "ground_truth": "a rainbow sidewalk", "context": "Session 14 (1:33 pm on 25 August, 2023):\nCaroline: I was out walking in my neighborhood when I came across this cool rainbow sidewalk for Pride Month. It was so vibrant and welcoming, I had to take a picture! It reminds us that love and acceptance are everywhere—even where we least expect it.", "model_answer": "A rainbow sidewalk", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-50_q010", "cell": "oracle-context", "question": "When did Calvin's place get flooded in Tokyo?", "ground_truth": "On a week before 16 May, 2023", "context": "Session 6 (11:50 am on 16 May, 2023):\nCalvin: Hey Dave, not everything has been going smoothly. I had an incident last week where my place got flooded, but thankfully, I managed to save my music gear and favorite microphone. It's been tough, but I'm staying positive and looking forward to getting everything fixed up.", "model_answer": "Last week", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F2"}
{"instance_id": "locomo_conv-50_q078", "cell": "oracle-context", "question": "What was the necklace Calvin received meant to remind him of?", "ground_truth": "why he keeps hustling as a musician", "context": "Session 4 (6:24 pm on 1 May, 2023):\nCalvin: Thanks, Dave! I got it from another artist as a gift - it's a great reminder of why I keep hustling as a musician!", "model_answer": "Why he keeps hustling as a musician", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-47_q092", "cell": "oracle-context", "question": "What did John create for the charitable foundation that helped generate reports for analysis?", "ground_truth": "computer application on smartphones", "context": "Session 11 (5:00 pm on 11 May, 2022):\nJohn: Previously, this foundation used paper records and all inventory was recorded manually. I made an application that structured their work, and now everything they need for inventory is in one application on their smartphone.", "model_answer": "An application", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F2"}
{"instance_id": "locomo_conv-30_q057", "cell": "oracle-context", "question": "What advice does Gina give to Jon about running a successful business?", "ground_truth": "build relationships with customers, create a strong brand image, stay positive", "context": "Session 7 (7:28 pm on 23 March, 2023):\nJon: Yeah, brand identity is key. Make sure yours stands out. Also be sure to build relationships with your customers – let them know you care. And don't forget to stay positive and motivate others. Your energy will be contagious!", "model_answer": "Not mentioned.", "opus_verdict": "incorrect", "opus_failure_mode": "F1", "gpt_verdict": "incorrect", "gpt_failure_mode": "F1", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F1"}
{"instance_id": "locomo_conv-30_q029", "cell": "oracle-context", "question": "Which cities has Jon visited?", "ground_truth": "Paris, Rome", "context": "Session 2 (2:32 pm on 29 January, 2023):\nJon: Hey Gina! Thanks for asking. I'm on the hunt for the ideal spot for my dance studio and it's been quite a journey! I've been looking at different places and picturing how the space would look. I even found a place with great natural light! Oh, I've been to Paris yesterday! It was sooo cool. [image: a photo of a bathroom with a blue floor and a pink wall]\n\nSession 15 (10:04 am on 19 June, 2023):\nJon: Hey Gina, hope you're doing great! Still working on my biz. Took a short trip last week to Rome to clear my mind a little.", "model_answer": "Paris and Rome", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-44_q066", "cell": "oracle-context", "question": "What type of dog was Andrew looking to adopt based on his living space?", "ground_truth": "smaller dog", "context": "Session 5 (10:47 am on 6 May, 2023):\nAndrew: Meeting all these adorable pups has been awesome! For those considering getting a pup, the size of living space and the exercise needs of the breed are important. For me, a person living in an apartment, a smaller dog would be best, but if one is active, consider getting one that loves to play and run.", "model_answer": "A smaller dog", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-44_q002", "cell": "oracle-context", "question": "What kind of indoor activities has Andrew pursued with his girlfriend?", "ground_truth": "boardgames, volunteering at pet shelter, wine tasting, growing flowers", "context": "Session 13 (3:52 pm on 27 July, 2023):\nAndrew: Hey Audrey! How are you? My GF and I just had a great experience volunteering at a pet shelter on Monday - it was so rewarding! We loved spending time with those cute animals and it gave us so much joy. It was so rewarding, it reminded me just how much I love them!\n\nSession 19 (5:53 pm on 24 September, 2023):\nAndrew: Yeah! They really do bring so much into our lives - it's amazing to watch them interact. Here's something I've been taking care of lately. Look at those flowers! [image: a photo of a balcony with a bunch of flowers on it]\n\nSession 23 (4:22 pm on 13 October, 2023):\nAndrew: Hey Audrey, it's been a busy week for me. Last Tuesday, my gf, Toby, and I had a really awesome night playing board games. It was really nice. What's been up with you lately? [image: a photography of a dog sitting at a chess board with a chess set in front of him]\n\nSession 25 (10:14 am on 24 October, 2023):\nAndrew: Hi Audrey! How have you been lately? My girlfriend and I went to this awesome wine tasting last weekend. It was great! We tried so many unique wines and learned a lot. I was surprised at how much I enjoyed it. A reminder to step out of the comfort zone!", "model_answer": "Board games.", "opus_verdict": "incorrect", "opus_failure_mode": "F2", "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F2"}
{"instance_id": "locomo_conv-47_q046", "cell": "oracle-context", "question": "When did John and James meet at McGee's bar?", "ground_truth": "August 27, 2022", "context": "Session 21 (9:18 pm on 26 August, 2022):\nJohn: Great, then I agree! See you tomorrow at McGee's Pub!", "model_answer": "27 August, 2022", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-43_q076", "cell": "oracle-context", "question": "What kind of picture did Tim share as part of their Harry Potter book collection?", "ground_truth": "MinaLima's creation from the Harry Potter films", "context": "Session 2 (5:08 pm on 15 June, 2023):\nTim: Thanks! That picture is from MinaLima. They created all the props for the Harry Potter films, and I love their work. It's like having a piece of the wizarding world at home!", "model_answer": "MinaLima", "opus_verdict": "incorrect", "opus_failure_mode": "F2", "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F2"}
{"instance_id": "locomo_conv-41_q065", "cell": "oracle-context", "question": "What is John's main focus in local politics?", "ground_truth": "Improving education and infrastructure", "context": "Session 1 (11:01 am on 17 December, 2022):\nJohn: I'm passionate about improving education and infrastructure in our community. Those are my main focuses.", "model_answer": "Education and infrastructure", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-50_q086", "cell": "full-context", "question": "What sports activity is Calvin planning to try after the tour with Frank Ocean?", "ground_truth": "Skiing", "context": "Session 9 (3:15 pm on 21 June, 2023):\nCalvin: Nope, not yet! I haven't been there before, but it's on my to-do list for after my tour with Frank Ocean ends. Can't wait to see them in person! Look at that snowy peak. [image: a photo of a person on skis on a snowy mountain]", "model_answer": "skiing", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-26_q059", "cell": "full-context", "question": "Would Caroline be considered religious?", "ground_truth": "Somewhat, but not extremely religious", "context": "Session 12 (1:50 pm on 17 August, 2023):\nCaroline: Hey Mel! How're ya doin'? Recently, I had a not-so-great experience on a hike. I ran into a group of religious conservatives who said something that really upset me. It made me think how much work we still have to do for LGBTQ rights. It's been so helpful to have people around me who accept and support me, so I know I'll be ok!\n\nSession 14 (1:33 pm on 25 August, 2023):\nCaroline: Thanks! It was made for a local church and shows time changing our lives. I made it to show my own journey as a transgender woman and how we should accept growth and change. [image: a photo of a large stained glass window in a church]", "model_answer": "unknown", "opus_verdict": "incorrect", "opus_failure_mode": "F1", "gpt_verdict": "incorrect", "gpt_failure_mode": "F1", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F1"}
{"instance_id": "locomo_conv-44_q000", "cell": "full-context", "question": "Which year did Audrey adopt the first three of her dogs?", "ground_truth": "2020", "context": "Session 1 (1:10 pm on 27 March, 2023):\nAudrey: I've had them for 3 years! Their names are Pepper, Precious and Panda. I can't live without my little ones!", "model_answer": "2020", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-41_q080", "cell": "full-context", "question": "What did Maria make for her home to remind her of a trip to England?", "ground_truth": "painting of a castle on a hill", "context": "Session 8 (6:03 pm on 6 March, 2023):\nMaria: Thanks, John! I got the idea from that trip to England a few years ago - I was mesmerized by the castles. I wanted to bring that same magic to my home, like a reminder of the world's beauty. I made a painting too! [image: a photography of a painting of a castle on a hill]", "model_answer": "a painting", "opus_verdict": "incorrect", "opus_failure_mode": "F2", "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F2"}
{"instance_id": "locomo_conv-42_q001", "cell": "full-context", "question": "What kind of interests do Joanna and Nate share?", "ground_truth": "Watching movies, making desserts", "context": "Session 1 (7:31 pm on 21 January, 2022):\nJoanna: Yeah! Besides writing, I also enjoy reading, watching movies, and exploring nature. Anything else you enjoy doing, Nate?\nNate: Playing video games and watching movies are my main hobbies.\nJoanna: Cool, Nate! So we both have similar interests. What type of movies do you like best?\n\nSession 3 (9:27 am on 7 February, 2022):\nNate: Thanks, Joanna. Not much has changed for me, but I just discovered that I can make coconut milk icecream and gave it a try. It was actually pretty good, so I'm proud of myself. [image: a photo of a bowl of ice cream with a spoon in it]\n\nSession 4 (1:07 pm on 25 February, 2022):\nNate: Thanks, Joanna! It means a lot that you enjoy the desserts I bake.\n\nSession 10 (11:54 am on 2 May, 2022):\nJoanna: Not much is new other than the screenplay. Been working on some projects and testing out dairy-free dessert recipes for friends and fam. Here's a pic of a cake I made recently! [image: a photo of a cake with white frosting on a wooden table]\n\nSession 20 (6:03 pm on 5 September, 2022):\nJoanna: Hey Nate! Cute turtles! Bummer about the setback. Any positive vibes comin' your way? I just revised on of my old recipes and made this! [image: a photo of a piece of cake with strawberries and chocolate]", "model_answer": "watching movies", "opus_verdict": "incorrect", "opus_failure_mode": "F2", "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F2"}
{"instance_id": "locomo_conv-43_q155", "cell": "full-context", "question": "How did John feel after being able to jog without pain?", "ground_truth": "It was a huge success.", "context": "Session 24 (3:37 pm on 16 December, 2023):\nJohn: It was great! After being out for so long, jogging without any pain was a huge success. My wife and I hosted a small get-together with friends and family to celebrate.", "model_answer": "great", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-50_q015", "cell": "full-context", "question": "Why does Dave regularly visit parks?", "ground_truth": "because it relaxes and calms him", "context": "Session 1 (11:53 am on 23 March, 2023):\nDave: That's great, can't wait for you to return from your trip. I've been spending lots of time at this beautiful park lately - so calming. Have you been there before? [image: a photography of a park with a lake and a few boats]\n\nSession 8 (2:31 pm on 9 June, 2023):\nDave: Hey, nice photo of the studio! Working in a team yields incredible results, well done! Keep pushing it! I've been doing good - thanks for asking. I've been exploring some parks on the weekends to relax - it's so peaceful being surrounded by nature. Are there any chill spots you enjoy in Boston?", "model_answer": "to relax", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-48_q020", "cell": "full-context", "question": "Which games have Jolene and her partner played together?", "ground_truth": "Detroit, Walking Dead, Battlefield 1, It Takes Two, Overcooked 2", "context": "Session 2 (9:49 am on 27 January, 2023):\nJolene: They are very unusual pets! Here's me and my partner gaming last week - it's so fun. We played the game \"Detroit\" on the console. We are both crazy about this activity! [image: a photo of a person laying in bed with a dog watching tv]\nJolene: We are planning to play \"Walking Dead\" next Saturday.\n\nSession 15 (7:37 pm on 9 July, 2023):\nJolene: Yeah, we love playing \"It takes two\" together! It's a fun team-strategy game and it's competitive. Plus, it's a great way for us to bond. Do you have any activities you like doing with people?\n\nSession 19 (12:52 am on 19 August, 2023):\nJolene: Oh, I forgot to mention Overcooked 2 - this is a good co-op game if you're into hilarious and chaotic cooking. My partner and I often play for bets! I once won three large pizzas!\n\nSession 20 (9:11 am on 21 August, 2023):\nJolene: Long time no talk! We were given a new game for the console last week, it is Battlefield 1. What's been up with you?", "model_answer": "Detroit, It takes two, Overcooked 2", "opus_verdict": "incorrect", "opus_failure_mode": "F2", "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F2"}
{"instance_id": "locomo_conv-48_q055", "cell": "full-context", "question": "Which pet did Jolene adopt more recently - Susie or Seraphim?", "ground_truth": "Seraphim", "context": "Session 2 (9:49 am on 27 January, 2023):\nJolene: I bought it a year ago in Paris.\nJolene: Even as a child I learned to play on my own.\n\nSession 16 (9:26 am on 1 August, 2023):\nJolene: I adopted her two years ago when I was feeling lonely and wanted some company.", "model_answer": "unknown", "opus_verdict": "incorrect", "opus_failure_mode": "F1", "gpt_verdict": "incorrect", "gpt_failure_mode": "F1", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F1"}
{"instance_id": "locomo_conv-26_q128", "cell": "full-context", "question": "What did Caroline find in her neighborhood during her walk?", "ground_truth": "a rainbow sidewalk", "context": "Session 14 (1:33 pm on 25 August, 2023):\nCaroline: I was out walking in my neighborhood when I came across this cool rainbow sidewalk for Pride Month. It was so vibrant and welcoming, I had to take a picture! It reminds us that love and acceptance are everywhere—even where we least expect it.", "model_answer": "rainbow sidewalk", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-50_q010", "cell": "full-context", "question": "When did Calvin's place get flooded in Tokyo?", "ground_truth": "On a week before 16 May, 2023", "context": "Session 6 (11:50 am on 16 May, 2023):\nCalvin: Hey Dave, not everything has been going smoothly. I had an incident last week where my place got flooded, but thankfully, I managed to save my music gear and favorite microphone. It's been tough, but I'm staying positive and looking forward to getting everything fixed up.", "model_answer": "last week", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F2"}
{"instance_id": "locomo_conv-50_q078", "cell": "full-context", "question": "What was the necklace Calvin received meant to remind him of?", "ground_truth": "why he keeps hustling as a musician", "context": "Session 4 (6:24 pm on 1 May, 2023):\nCalvin: Thanks, Dave! I got it from another artist as a gift - it's a great reminder of why I keep hustling as a musician!", "model_answer": "why I keep hustling as a musician", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-47_q092", "cell": "full-context", "question": "What did John create for the charitable foundation that helped generate reports for analysis?", "ground_truth": "computer application on smartphones", "context": "Session 11 (5:00 pm on 11 May, 2022):\nJohn: Previously, this foundation used paper records and all inventory was recorded manually. I made an application that structured their work, and now everything they need for inventory is in one application on their smartphone.", "model_answer": "an application", "opus_verdict": "incorrect", "opus_failure_mode": "F2", "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F2"}
{"instance_id": "locomo_conv-30_q057", "cell": "full-context", "question": "What advice does Gina give to Jon about running a successful business?", "ground_truth": "build relationships with customers, create a strong brand image, stay positive", "context": "Session 7 (7:28 pm on 23 March, 2023):\nJon: Yeah, brand identity is key. Make sure yours stands out. Also be sure to build relationships with your customers – let them know you care. And don't forget to stay positive and motivate others. Your energy will be contagious!", "model_answer": "unknown", "opus_verdict": "incorrect", "opus_failure_mode": "F1", "gpt_verdict": "incorrect", "gpt_failure_mode": "F1", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F1"}
{"instance_id": "locomo_conv-30_q029", "cell": "full-context", "question": "Which cities has Jon visited?", "ground_truth": "Paris, Rome", "context": "Session 2 (2:32 pm on 29 January, 2023):\nJon: Hey Gina! Thanks for asking. I'm on the hunt for the ideal spot for my dance studio and it's been quite a journey! I've been looking at different places and picturing how the space would look. I even found a place with great natural light! Oh, I've been to Paris yesterday! It was sooo cool. [image: a photo of a bathroom with a blue floor and a pink wall]\n\nSession 15 (10:04 am on 19 June, 2023):\nJon: Hey Gina, hope you're doing great! Still working on my biz. Took a short trip last week to Rome to clear my mind a little.", "model_answer": "Paris Rome", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-44_q066", "cell": "full-context", "question": "What type of dog was Andrew looking to adopt based on his living space?", "ground_truth": "smaller dog", "context": "Session 5 (10:47 am on 6 May, 2023):\nAndrew: Meeting all these adorable pups has been awesome! For those considering getting a pup, the size of living space and the exercise needs of the breed are important. For me, a person living in an apartment, a smaller dog would be best, but if one is active, consider getting one that loves to play and run.", "model_answer": "smaller dog", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-44_q002", "cell": "full-context", "question": "What kind of indoor activities has Andrew pursued with his girlfriend?", "ground_truth": "boardgames, volunteering at pet shelter, wine tasting, growing flowers", "context": "Session 13 (3:52 pm on 27 July, 2023):\nAndrew: Hey Audrey! How are you? My GF and I just had a great experience volunteering at a pet shelter on Monday - it was so rewarding! We loved spending time with those cute animals and it gave us so much joy. It was so rewarding, it reminded me just how much I love them!\n\nSession 19 (5:53 pm on 24 September, 2023):\nAndrew: Yeah! They really do bring so much into our lives - it's amazing to watch them interact. Here's something I've been taking care of lately. Look at those flowers! [image: a photo of a balcony with a bunch of flowers on it]\n\nSession 23 (4:22 pm on 13 October, 2023):\nAndrew: Hey Audrey, it's been a busy week for me. Last Tuesday, my gf, Toby, and I had a really awesome night playing board games. It was really nice. What's been up with you lately? [image: a photography of a dog sitting at a chess board with a chess set in front of him]\n\nSession 25 (10:14 am on 24 October, 2023):\nAndrew: Hi Audrey! How have you been lately? My girlfriend and I went to this awesome wine tasting last weekend. It was great! We tried so many unique wines and learned a lot. I was surprised at how much I enjoyed it. A reminder to step out of the comfort zone!", "model_answer": "playing board games", "opus_verdict": "incorrect", "opus_failure_mode": "F2", "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F2"}
{"instance_id": "locomo_conv-47_q046", "cell": "full-context", "question": "When did John and James meet at McGee's bar?", "ground_truth": "August 27, 2022", "context": "Session 21 (9:18 pm on 26 August, 2022):\nJohn: Great, then I agree! See you tomorrow at McGee's Pub!", "model_answer": "tomorrow", "opus_verdict": "incorrect", "opus_failure_mode": "F2", "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F3"}
{"instance_id": "locomo_conv-43_q076", "cell": "full-context", "question": "What kind of picture did Tim share as part of their Harry Potter book collection?", "ground_truth": "MinaLima's creation from the Harry Potter films", "context": "Session 2 (5:08 pm on 15 June, 2023):\nTim: Thanks! That picture is from MinaLima. They created all the props for the Harry Potter films, and I love their work. It's like having a piece of the wizarding world at home!", "model_answer": "from MinaLima", "opus_verdict": "incorrect", "opus_failure_mode": "F2", "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-41_q065", "cell": "full-context", "question": "What is John's main focus in local politics?", "ground_truth": "Improving education and infrastructure", "context": "Session 1 (11:01 am on 17 December, 2022):\nJohn: I'm passionate about improving education and infrastructure in our community. Those are my main focuses.", "model_answer": "improving education and infrastructure", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-50_q086", "cell": "retrieval", "question": "What sports activity is Calvin planning to try after the tour with Frank Ocean?", "ground_truth": "Skiing", "context": "Session 9 (3:15 pm on 21 June, 2023):\nCalvin: Nope, not yet! I haven't been there before, but it's on my to-do list for after my tour with Frank Ocean ends. Can't wait to see them in person! Look at that snowy peak. [image: a photo of a person on skis on a snowy mountain]", "model_answer": "Not mentioned", "opus_verdict": "incorrect", "opus_failure_mode": "F1", "gpt_verdict": "incorrect", "gpt_failure_mode": "F1", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F1"}
{"instance_id": "locomo_conv-26_q059", "cell": "retrieval", "question": "Would Caroline be considered religious?", "ground_truth": "Somewhat, but not extremely religious", "context": "Session 12 (1:50 pm on 17 August, 2023):\nCaroline: Hey Mel! How're ya doin'? Recently, I had a not-so-great experience on a hike. I ran into a group of religious conservatives who said something that really upset me. It made me think how much work we still have to do for LGBTQ rights. It's been so helpful to have people around me who accept and support me, so I know I'll be ok!\n\nSession 14 (1:33 pm on 25 August, 2023):\nCaroline: Thanks! It was made for a local church and shows time changing our lives. I made it to show my own journey as a transgender woman and how we should accept growth and change. [image: a photo of a large stained glass window in a church]", "model_answer": "No.", "opus_verdict": "incorrect", "opus_failure_mode": "F3", "gpt_verdict": "incorrect", "gpt_failure_mode": "F3", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F3"}
{"instance_id": "locomo_conv-44_q000", "cell": "retrieval", "question": "Which year did Audrey adopt the first three of her dogs?", "ground_truth": "2020", "context": "Session 1 (1:10 pm on 27 March, 2023):\nAudrey: I've had them for 3 years! Their names are Pepper, Precious and Panda. I can't live without my little ones!", "model_answer": "Not mentioned.", "opus_verdict": "incorrect", "opus_failure_mode": "F1", "gpt_verdict": "incorrect", "gpt_failure_mode": "F1", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F1"}
{"instance_id": "locomo_conv-41_q080", "cell": "retrieval", "question": "What did Maria make for her home to remind her of a trip to England?", "ground_truth": "painting of a castle on a hill", "context": "Session 8 (6:03 pm on 6 March, 2023):\nMaria: Thanks, John! I got the idea from that trip to England a few years ago - I was mesmerized by the castles. I wanted to bring that same magic to my home, like a reminder of the world's beauty. I made a painting too! [image: a photography of a painting of a castle on a hill]", "model_answer": "A painting.", "opus_verdict": "incorrect", "opus_failure_mode": "F2", "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F2"}
{"instance_id": "locomo_conv-42_q001", "cell": "retrieval", "question": "What kind of interests do Joanna and Nate share?", "ground_truth": "Watching movies, making desserts", "context": "Session 1 (7:31 pm on 21 January, 2022):\nJoanna: Yeah! Besides writing, I also enjoy reading, watching movies, and exploring nature. Anything else you enjoy doing, Nate?\nNate: Playing video games and watching movies are my main hobbies.\nJoanna: Cool, Nate! So we both have similar interests. What type of movies do you like best?\n\nSession 3 (9:27 am on 7 February, 2022):\nNate: Thanks, Joanna. Not much has changed for me, but I just discovered that I can make coconut milk icecream and gave it a try. It was actually pretty good, so I'm proud of myself. [image: a photo of a bowl of ice cream with a spoon in it]\n\nSession 4 (1:07 pm on 25 February, 2022):\nNate: Thanks, Joanna! It means a lot that you enjoy the desserts I bake.\n\nSession 10 (11:54 am on 2 May, 2022):\nJoanna: Not much is new other than the screenplay. Been working on some projects and testing out dairy-free dessert recipes for friends and fam. Here's a pic of a cake I made recently! [image: a photo of a cake with white frosting on a wooden table]\n\nSession 20 (6:03 pm on 5 September, 2022):\nJoanna: Hey Nate! Cute turtles! Bummer about the setback. Any positive vibes comin' your way? I just revised on of my old recipes and made this! [image: a photo of a piece of cake with strawberries and chocolate]", "model_answer": "Movies and nature.", "opus_verdict": "incorrect", "opus_failure_mode": "F3", "gpt_verdict": "incorrect", "gpt_failure_mode": "F3", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F3"}
{"instance_id": "locomo_conv-43_q155", "cell": "retrieval", "question": "How did John feel after being able to jog without pain?", "ground_truth": "It was a huge success.", "context": "Session 24 (3:37 pm on 16 December, 2023):\nJohn: It was great! After being out for so long, jogging without any pain was a huge success. My wife and I hosted a small get-together with friends and family to celebrate.", "model_answer": "Relieved", "opus_verdict": "incorrect", "opus_failure_mode": "F3", "gpt_verdict": "incorrect", "gpt_failure_mode": "F3", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F4"}
{"instance_id": "locomo_conv-50_q015", "cell": "retrieval", "question": "Why does Dave regularly visit parks?", "ground_truth": "because it relaxes and calms him", "context": "Session 1 (11:53 am on 23 March, 2023):\nDave: That's great, can't wait for you to return from your trip. I've been spending lots of time at this beautiful park lately - so calming. Have you been there before? [image: a photography of a park with a lake and a few boats]\n\nSession 8 (2:31 pm on 9 June, 2023):\nDave: Hey, nice photo of the studio! Working in a team yields incredible results, well done! Keep pushing it! I've been doing good - thanks for asking. I've been exploring some parks on the weekends to relax - it's so peaceful being surrounded by nature. Are there any chill spots you enjoy in Boston?", "model_answer": "To relax, recharge, and hang out with friends.", "opus_verdict": "incorrect", "opus_failure_mode": "F4", "gpt_verdict": "incorrect", "gpt_failure_mode": "F4", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F4"}
{"instance_id": "locomo_conv-48_q020", "cell": "retrieval", "question": "Which games have Jolene and her partner played together?", "ground_truth": "Detroit, Walking Dead, Battlefield 1, It Takes Two, Overcooked 2", "context": "Session 2 (9:49 am on 27 January, 2023):\nJolene: They are very unusual pets! Here's me and my partner gaming last week - it's so fun. We played the game \"Detroit\" on the console. We are both crazy about this activity! [image: a photo of a person laying in bed with a dog watching tv]\nJolene: We are planning to play \"Walking Dead\" next Saturday.\n\nSession 15 (7:37 pm on 9 July, 2023):\nJolene: Yeah, we love playing \"It takes two\" together! It's a fun team-strategy game and it's competitive. Plus, it's a great way for us to bond. Do you have any activities you like doing with people?\n\nSession 19 (12:52 am on 19 August, 2023):\nJolene: Oh, I forgot to mention Overcooked 2 - this is a good co-op game if you're into hilarious and chaotic cooking. My partner and I often play for bets! I once won three large pizzas!\n\nSession 20 (9:11 am on 21 August, 2023):\nJolene: Long time no talk! We were given a new game for the console last week, it is Battlefield 1. What's been up with you?", "model_answer": "Detroit, Overcooked 2, It Takes Two", "opus_verdict": "incorrect", "opus_failure_mode": "F2", "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F2"}
{"instance_id": "locomo_conv-48_q055", "cell": "retrieval", "question": "Which pet did Jolene adopt more recently - Susie or Seraphim?", "ground_truth": "Seraphim", "context": "Session 2 (9:49 am on 27 January, 2023):\nJolene: I bought it a year ago in Paris.\nJolene: Even as a child I learned to play on my own.\n\nSession 16 (9:26 am on 1 August, 2023):\nJolene: I adopted her two years ago when I was feeling lonely and wanted some company.", "model_answer": "Seraphim", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-26_q128", "cell": "retrieval", "question": "What did Caroline find in her neighborhood during her walk?", "ground_truth": "a rainbow sidewalk", "context": "Session 14 (1:33 pm on 25 August, 2023):\nCaroline: I was out walking in my neighborhood when I came across this cool rainbow sidewalk for Pride Month. It was so vibrant and welcoming, I had to take a picture! It reminds us that love and acceptance are everywhere—even where we least expect it.", "model_answer": "A rainbow sidewalk.", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-50_q010", "cell": "retrieval", "question": "When did Calvin's place get flooded in Tokyo?", "ground_truth": "On a week before 16 May, 2023", "context": "Session 6 (11:50 am on 16 May, 2023):\nCalvin: Hey Dave, not everything has been going smoothly. I had an incident last week where my place got flooded, but thankfully, I managed to save my music gear and favorite microphone. It's been tough, but I'm staying positive and looking forward to getting everything fixed up.", "model_answer": "Last week.", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F2"}
{"instance_id": "locomo_conv-50_q078", "cell": "retrieval", "question": "What was the necklace Calvin received meant to remind him of?", "ground_truth": "why he keeps hustling as a musician", "context": "Session 4 (6:24 pm on 1 May, 2023):\nCalvin: Thanks, Dave! I got it from another artist as a gift - it's a great reminder of why I keep hustling as a musician!", "model_answer": "Why he keeps hustling as a musician.", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-47_q092", "cell": "retrieval", "question": "What did John create for the charitable foundation that helped generate reports for analysis?", "ground_truth": "computer application on smartphones", "context": "Session 11 (5:00 pm on 11 May, 2022):\nJohn: Previously, this foundation used paper records and all inventory was recorded manually. I made an application that structured their work, and now everything they need for inventory is in one application on their smartphone.", "model_answer": "A software tool", "opus_verdict": "incorrect", "opus_failure_mode": "F2", "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F2"}
{"instance_id": "locomo_conv-30_q057", "cell": "retrieval", "question": "What advice does Gina give to Jon about running a successful business?", "ground_truth": "build relationships with customers, create a strong brand image, stay positive", "context": "Session 7 (7:28 pm on 23 March, 2023):\nJon: Yeah, brand identity is key. Make sure yours stands out. Also be sure to build relationships with your customers – let them know you care. And don't forget to stay positive and motivate others. Your energy will be contagious!", "model_answer": "Stay passionate, focused, and resilient; believe in yourself, keep going, and stay open to learning.", "opus_verdict": "incorrect", "opus_failure_mode": "F4", "gpt_verdict": "incorrect", "gpt_failure_mode": "F4", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F4"}
{"instance_id": "locomo_conv-30_q029", "cell": "retrieval", "question": "Which cities has Jon visited?", "ground_truth": "Paris, Rome", "context": "Session 2 (2:32 pm on 29 January, 2023):\nJon: Hey Gina! Thanks for asking. I'm on the hunt for the ideal spot for my dance studio and it's been quite a journey! I've been looking at different places and picturing how the space would look. I even found a place with great natural light! Oh, I've been to Paris yesterday! It was sooo cool. [image: a photo of a bathroom with a blue floor and a pink wall]\n\nSession 15 (10:04 am on 19 June, 2023):\nJon: Hey Gina, hope you're doing great! Still working on my biz. Took a short trip last week to Rome to clear my mind a little.", "model_answer": "Paris", "opus_verdict": "incorrect", "opus_failure_mode": "F2", "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F2"}
{"instance_id": "locomo_conv-44_q066", "cell": "retrieval", "question": "What type of dog was Andrew looking to adopt based on his living space?", "ground_truth": "smaller dog", "context": "Session 5 (10:47 am on 6 May, 2023):\nAndrew: Meeting all these adorable pups has been awesome! For those considering getting a pup, the size of living space and the exercise needs of the breed are important. For me, a person living in an apartment, a smaller dog would be best, but if one is active, consider getting one that loves to play and run.", "model_answer": "A smaller dog.", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-44_q002", "cell": "retrieval", "question": "What kind of indoor activities has Andrew pursued with his girlfriend?", "ground_truth": "boardgames, volunteering at pet shelter, wine tasting, growing flowers", "context": "Session 13 (3:52 pm on 27 July, 2023):\nAndrew: Hey Audrey! How are you? My GF and I just had a great experience volunteering at a pet shelter on Monday - it was so rewarding! We loved spending time with those cute animals and it gave us so much joy. It was so rewarding, it reminded me just how much I love them!\n\nSession 19 (5:53 pm on 24 September, 2023):\nAndrew: Yeah! They really do bring so much into our lives - it's amazing to watch them interact. Here's something I've been taking care of lately. Look at those flowers! [image: a photo of a balcony with a bunch of flowers on it]\n\nSession 23 (4:22 pm on 13 October, 2023):\nAndrew: Hey Audrey, it's been a busy week for me. Last Tuesday, my gf, Toby, and I had a really awesome night playing board games. It was really nice. What's been up with you lately? [image: a photography of a dog sitting at a chess board with a chess set in front of him]\n\nSession 25 (10:14 am on 24 October, 2023):\nAndrew: Hi Audrey! How have you been lately? My girlfriend and I went to this awesome wine tasting last weekend. It was great! We tried so many unique wines and learned a lot. I was surprised at how much I enjoyed it. A reminder to step out of the comfort zone!", "model_answer": "Wine tasting", "opus_verdict": "incorrect", "opus_failure_mode": "F2", "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F2"}
{"instance_id": "locomo_conv-47_q046", "cell": "retrieval", "question": "When did John and James meet at McGee's bar?", "ground_truth": "August 27, 2022", "context": "Session 21 (9:18 pm on 26 August, 2022):\nJohn: Great, then I agree! See you tomorrow at McGee's Pub!", "model_answer": "Tomorrow", "opus_verdict": "incorrect", "opus_failure_mode": "F2", "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F3"}
{"instance_id": "locomo_conv-43_q076", "cell": "retrieval", "question": "What kind of picture did Tim share as part of their Harry Potter book collection?", "ground_truth": "MinaLima's creation from the Harry Potter films", "context": "Session 2 (5:08 pm on 15 June, 2023):\nTim: Thanks! That picture is from MinaLima. They created all the props for the Harry Potter films, and I love their work. It's like having a piece of the wizarding world at home!", "model_answer": "MinaLima props", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-41_q065", "cell": "retrieval", "question": "What is John's main focus in local politics?", "ground_truth": "Improving education and infrastructure", "context": "Session 1 (11:01 am on 17 December, 2022):\nJohn: I'm passionate about improving education and infrastructure in our community. Those are my main focuses.", "model_answer": "Education and infrastructure", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-50_q086", "cell": "agentic", "question": "What sports activity is Calvin planning to try after the tour with Frank Ocean?", "ground_truth": "Skiing", "context": "Session 9 (3:15 pm on 21 June, 2023):\nCalvin: Nope, not yet! I haven't been there before, but it's on my to-do list for after my tour with Frank Ocean ends. Can't wait to see them in person! Look at that snowy peak. [image: a photo of a person on skis on a snowy mountain]", "model_answer": "Max tool turns reached (3 turns, 3 tools used).", "opus_verdict": "incorrect", "opus_failure_mode": "F1", "gpt_verdict": "incorrect", "gpt_failure_mode": "F1", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F1"}
{"instance_id": "locomo_conv-26_q059", "cell": "agentic", "question": "Would Caroline be considered religious?", "ground_truth": "Somewhat, but not extremely religious", "context": "Session 12 (1:50 pm on 17 August, 2023):\nCaroline: Hey Mel! How're ya doin'? Recently, I had a not-so-great experience on a hike. I ran into a group of religious conservatives who said something that really upset me. It made me think how much work we still have to do for LGBTQ rights. It's been so helpful to have people around me who accept and support me, so I know I'll be ok!\n\nSession 14 (1:33 pm on 25 August, 2023):\nCaroline: Thanks! It was made for a local church and shows time changing our lives. I made it to show my own journey as a transgender woman and how we should accept growth and change. [image: a photo of a large stained glass window in a church]", "model_answer": "Yes, Caroline has a connection to faith through her heritage (a necklace from Sweden representing \"love, faith and strength\") and by having made a painting for a local church.", "opus_verdict": "incorrect", "opus_failure_mode": "F3", "gpt_verdict": "incorrect", "gpt_failure_mode": "F4", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F4"}
{"instance_id": "locomo_conv-44_q000", "cell": "agentic", "question": "Which year did Audrey adopt the first three of her dogs?", "ground_truth": "2020", "context": "Session 1 (1:10 pm on 27 March, 2023):\nAudrey: I've had them for 3 years! Their names are Pepper, Precious and Panda. I can't live without my little ones!", "model_answer": "Max tool turns reached (3 turns, 3 tools used).", "opus_verdict": "incorrect", "opus_failure_mode": "F1", "gpt_verdict": "incorrect", "gpt_failure_mode": "F1", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F1"}
{"instance_id": "locomo_conv-41_q080", "cell": "agentic", "question": "What did Maria make for her home to remind her of a trip to England?", "ground_truth": "painting of a castle on a hill", "context": "Session 8 (6:03 pm on 6 March, 2023):\nMaria: Thanks, John! I got the idea from that trip to England a few years ago - I was mesmerized by the castles. I wanted to bring that same magic to my home, like a reminder of the world's beauty. I made a painting too! [image: a photography of a painting of a castle on a hill]", "model_answer": "a painting", "opus_verdict": "incorrect", "opus_failure_mode": "F2", "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F2"}
{"instance_id": "locomo_conv-42_q001", "cell": "agentic", "question": "What kind of interests do Joanna and Nate share?", "ground_truth": "Watching movies, making desserts", "context": "Session 1 (7:31 pm on 21 January, 2022):\nJoanna: Yeah! Besides writing, I also enjoy reading, watching movies, and exploring nature. Anything else you enjoy doing, Nate?\nNate: Playing video games and watching movies are my main hobbies.\nJoanna: Cool, Nate! So we both have similar interests. What type of movies do you like best?\n\nSession 3 (9:27 am on 7 February, 2022):\nNate: Thanks, Joanna. Not much has changed for me, but I just discovered that I can make coconut milk icecream and gave it a try. It was actually pretty good, so I'm proud of myself. [image: a photo of a bowl of ice cream with a spoon in it]\n\nSession 4 (1:07 pm on 25 February, 2022):\nNate: Thanks, Joanna! It means a lot that you enjoy the desserts I bake.\n\nSession 10 (11:54 am on 2 May, 2022):\nJoanna: Not much is new other than the screenplay. Been working on some projects and testing out dairy-free dessert recipes for friends and fam. Here's a pic of a cake I made recently! [image: a photo of a cake with white frosting on a wooden table]\n\nSession 20 (6:03 pm on 5 September, 2022):\nJoanna: Hey Nate! Cute turtles! Bummer about the setback. Any positive vibes comin' your way? I just revised on of my old recipes and made this! [image: a photo of a piece of cake with strawberries and chocolate]", "model_answer": "movies", "opus_verdict": "incorrect", "opus_failure_mode": "F2", "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F2"}
{"instance_id": "locomo_conv-43_q155", "cell": "agentic", "question": "How did John feel after being able to jog without pain?", "ground_truth": "It was a huge success.", "context": "Session 24 (3:37 pm on 16 December, 2023):\nJohn: It was great! After being out for so long, jogging without any pain was a huge success. My wife and I hosted a small get-together with friends and family to celebrate.", "model_answer": "great", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-50_q015", "cell": "agentic", "question": "Why does Dave regularly visit parks?", "ground_truth": "because it relaxes and calms him", "context": "Session 1 (11:53 am on 23 March, 2023):\nDave: That's great, can't wait for you to return from your trip. I've been spending lots of time at this beautiful park lately - so calming. Have you been there before? [image: a photography of a park with a lake and a few boats]\n\nSession 8 (2:31 pm on 9 June, 2023):\nDave: Hey, nice photo of the studio! Working in a team yields incredible results, well done! Keep pushing it! I've been doing good - thanks for asking. I've been exploring some parks on the weekends to relax - it's so peaceful being surrounded by nature. Are there any chill spots you enjoy in Boston?", "model_answer": "to relax and recharge", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-48_q020", "cell": "agentic", "question": "Which games have Jolene and her partner played together?", "ground_truth": "Detroit, Walking Dead, Battlefield 1, It Takes Two, Overcooked 2", "context": "Session 2 (9:49 am on 27 January, 2023):\nJolene: They are very unusual pets! Here's me and my partner gaming last week - it's so fun. We played the game \"Detroit\" on the console. We are both crazy about this activity! [image: a photo of a person laying in bed with a dog watching tv]\nJolene: We are planning to play \"Walking Dead\" next Saturday.\n\nSession 15 (7:37 pm on 9 July, 2023):\nJolene: Yeah, we love playing \"It takes two\" together! It's a fun team-strategy game and it's competitive. Plus, it's a great way for us to bond. Do you have any activities you like doing with people?\n\nSession 19 (12:52 am on 19 August, 2023):\nJolene: Oh, I forgot to mention Overcooked 2 - this is a good co-op game if you're into hilarious and chaotic cooking. My partner and I often play for bets! I once won three large pizzas!\n\nSession 20 (9:11 am on 21 August, 2023):\nJolene: Long time no talk! We were given a new game for the console last week, it is Battlefield 1. What's been up with you?", "model_answer": "Detroit, Overcooked 2, It Takes Two", "opus_verdict": "incorrect", "opus_failure_mode": "F2", "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F2"}
{"instance_id": "locomo_conv-48_q055", "cell": "agentic", "question": "Which pet did Jolene adopt more recently - Susie or Seraphim?", "ground_truth": "Seraphim", "context": "Session 2 (9:49 am on 27 January, 2023):\nJolene: I bought it a year ago in Paris.\nJolene: Even as a child I learned to play on my own.\n\nSession 16 (9:26 am on 1 August, 2023):\nJolene: I adopted her two years ago when I was feeling lonely and wanted some company.", "model_answer": "Susie", "opus_verdict": "incorrect", "opus_failure_mode": "F3", "gpt_verdict": "incorrect", "gpt_failure_mode": "F3", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F3"}
{"instance_id": "locomo_conv-26_q128", "cell": "agentic", "question": "What did Caroline find in her neighborhood during her walk?", "ground_truth": "a rainbow sidewalk", "context": "Session 14 (1:33 pm on 25 August, 2023):\nCaroline: I was out walking in my neighborhood when I came across this cool rainbow sidewalk for Pride Month. It was so vibrant and welcoming, I had to take a picture! It reminds us that love and acceptance are everywhere—even where we least expect it.", "model_answer": "a rainbow sidewalk", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-50_q010", "cell": "agentic", "question": "When did Calvin's place get flooded in Tokyo?", "ground_truth": "On a week before 16 May, 2023", "context": "Session 6 (11:50 am on 16 May, 2023):\nCalvin: Hey Dave, not everything has been going smoothly. I had an incident last week where my place got flooded, but thankfully, I managed to save my music gear and favorite microphone. It's been tough, but I'm staying positive and looking forward to getting everything fixed up.", "model_answer": "last week", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F2"}
{"instance_id": "locomo_conv-50_q078", "cell": "agentic", "question": "What was the necklace Calvin received meant to remind him of?", "ground_truth": "why he keeps hustling as a musician", "context": "Session 4 (6:24 pm on 1 May, 2023):\nCalvin: Thanks, Dave! I got it from another artist as a gift - it's a great reminder of why I keep hustling as a musician!", "model_answer": "why he keeps hustling as a musician", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-47_q092", "cell": "agentic", "question": "What did John create for the charitable foundation that helped generate reports for analysis?", "ground_truth": "computer application on smartphones", "context": "Session 11 (5:00 pm on 11 May, 2022):\nJohn: Previously, this foundation used paper records and all inventory was recorded manually. I made an application that structured their work, and now everything they need for inventory is in one application on their smartphone.", "model_answer": "a software tool", "opus_verdict": "incorrect", "opus_failure_mode": "F2", "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F2"}
{"instance_id": "locomo_conv-30_q057", "cell": "agentic", "question": "What advice does Gina give to Jon about running a successful business?", "ground_truth": "build relationships with customers, create a strong brand image, stay positive", "context": "Session 7 (7:28 pm on 23 March, 2023):\nJon: Yeah, brand identity is key. Make sure yours stands out. Also be sure to build relationships with your customers – let them know you care. And don't forget to stay positive and motivate others. Your energy will be contagious!", "model_answer": "Focus on why you started, have faith in yourself, remind yourself of successes and progress, and have a good support system", "opus_verdict": "incorrect", "opus_failure_mode": "F3", "gpt_verdict": "incorrect", "gpt_failure_mode": "F5", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F4"}
{"instance_id": "locomo_conv-30_q029", "cell": "agentic", "question": "Which cities has Jon visited?", "ground_truth": "Paris, Rome", "context": "Session 2 (2:32 pm on 29 January, 2023):\nJon: Hey Gina! Thanks for asking. I'm on the hunt for the ideal spot for my dance studio and it's been quite a journey! I've been looking at different places and picturing how the space would look. I even found a place with great natural light! Oh, I've been to Paris yesterday! It was sooo cool. [image: a photo of a bathroom with a blue floor and a pink wall]\n\nSession 15 (10:04 am on 19 June, 2023):\nJon: Hey Gina, hope you're doing great! Still working on my biz. Took a short trip last week to Rome to clear my mind a little.", "model_answer": "unknown", "opus_verdict": "incorrect", "opus_failure_mode": "F1", "gpt_verdict": "incorrect", "gpt_failure_mode": "F1", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F1"}
{"instance_id": "locomo_conv-44_q066", "cell": "agentic", "question": "What type of dog was Andrew looking to adopt based on his living space?", "ground_truth": "smaller dog", "context": "Session 5 (10:47 am on 6 May, 2023):\nAndrew: Meeting all these adorable pups has been awesome! For those considering getting a pup, the size of living space and the exercise needs of the breed are important. For me, a person living in an apartment, a smaller dog would be best, but if one is active, consider getting one that loves to play and run.", "model_answer": "a smaller dog", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-44_q002", "cell": "agentic", "question": "What kind of indoor activities has Andrew pursued with his girlfriend?", "ground_truth": "boardgames, volunteering at pet shelter, wine tasting, growing flowers", "context": "Session 13 (3:52 pm on 27 July, 2023):\nAndrew: Hey Audrey! How are you? My GF and I just had a great experience volunteering at a pet shelter on Monday - it was so rewarding! We loved spending time with those cute animals and it gave us so much joy. It was so rewarding, it reminded me just how much I love them!\n\nSession 19 (5:53 pm on 24 September, 2023):\nAndrew: Yeah! They really do bring so much into our lives - it's amazing to watch them interact. Here's something I've been taking care of lately. Look at those flowers! [image: a photo of a balcony with a bunch of flowers on it]\n\nSession 23 (4:22 pm on 13 October, 2023):\nAndrew: Hey Audrey, it's been a busy week for me. Last Tuesday, my gf, Toby, and I had a really awesome night playing board games. It was really nice. What's been up with you lately? [image: a photography of a dog sitting at a chess board with a chess set in front of him]\n\nSession 25 (10:14 am on 24 October, 2023):\nAndrew: Hi Audrey! How have you been lately? My girlfriend and I went to this awesome wine tasting last weekend. It was great! We tried so many unique wines and learned a lot. I was surprised at how much I enjoyed it. A reminder to step out of the comfort zone!", "model_answer": "board games", "opus_verdict": "incorrect", "opus_failure_mode": "F2", "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F2"}
{"instance_id": "locomo_conv-47_q046", "cell": "agentic", "question": "When did John and James meet at McGee's bar?", "ground_truth": "August 27, 2022", "context": "Session 21 (9:18 pm on 26 August, 2022):\nJohn: Great, then I agree! See you tomorrow at McGee's Pub!", "model_answer": "Tomorrow", "opus_verdict": "incorrect", "opus_failure_mode": "F2", "gpt_verdict": "incorrect", "gpt_failure_mode": "F2", "gemini_verdict_v5": "incorrect", "gemini_failure_mode_v5": "F3"}
{"instance_id": "locomo_conv-43_q076", "cell": "agentic", "question": "What kind of picture did Tim share as part of their Harry Potter book collection?", "ground_truth": "MinaLima's creation from the Harry Potter films", "context": "Session 2 (5:08 pm on 15 June, 2023):\nTim: Thanks! That picture is from MinaLima. They created all the props for the Harry Potter films, and I love their work. It's like having a piece of the wizarding world at home!", "model_answer": "A picture from MinaLima", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}
{"instance_id": "locomo_conv-41_q065", "cell": "agentic", "question": "What is John's main focus in local politics?", "ground_truth": "Improving education and infrastructure", "context": "Session 1 (11:01 am on 17 December, 2022):\nJohn: I'm passionate about improving education and infrastructure in our community. Those are my main focuses.", "model_answer": "Education and infrastructure", "opus_verdict": "correct", "opus_failure_mode": null, "gpt_verdict": "correct", "gpt_failure_mode": null, "gemini_verdict_v5": "correct", "gemini_failure_mode_v5": null}

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# Manifest v6 κ Re-Calibration Analysis
**Date:** 2026-04-24 **Parent:** `38a830e` (v6 Phase 1 Commit 2) **v6 anchor:** `60d061e`
**Sample:** 100 instances from `benchmarks/results/locomo-mini-n20-retry-2026-04-24T00-02-12Z.jsonl` (authoritative v5 κ set; zero new Opus/GPT calls).
**MiniMax verdicts:** 100 calls via OpenRouter `minimax/minimax-m2.7` (v6 alias: `minimax-m27-via-openrouter`); direct HTTP probe (LiteLLM proxy not in loop — isolates model behavior from middleware).
**Prompt:** verbatim `failure-mode-judge.ts:245-258` (same as §1.3g / §1.3h / §1.3h-C).
**Parameters:** `temperature=0.0`, `max_tokens=4096`.
---
## §1 Three pairwise Cohen's κ
| Pair | n | Agree | Raw % | κ |
|------|---|-------|-------|-----|
| Opus vs GPT | 100 | 93 | 93.00% | **0.8480** |
| Opus vs MiniMax | 100 | 93 | 93.00% | **0.8549** |
| GPT vs MiniMax | 100 | 90 | 90.00% | **0.7878** |
**Conservative trio κ = min = 0.7878**
## §2 Verdict: **PASS**
Per v6 §5.4 gate criteria:
- `κ_trio ≥ 0.70` → PASS, halt with PM-RATIFY-V6-KAPPA
- `0.60 ≤ κ_trio < 0.70` → BORDERLINE, halt with PM adjudication
- `κ_trio < 0.60` → FAIL, halt with swap-path-re-evaluation
---
## §3 Confusion matrices
### Opus vs GPT
| | GPT=correct | GPT=incorrect |
|---|---|---|
| **Opus=correct** | 32 | 7 |
| **Opus=incorrect** | 0 | 61 |
### Opus vs MiniMax
| | MiniMax=correct | MiniMax=incorrect |
|---|---|---|
| **Opus=correct** | 37 | 2 |
| **Opus=incorrect** | 5 | 56 |
### GPT vs MiniMax
| | MiniMax=correct | MiniMax=incorrect |
|---|---|---|
| **GPT=correct** | 32 | 0 |
| **GPT=incorrect** | 10 | 58 |
---
## §4 Per-cell κ breakdown (n=20 per cell)
| Cell | n | MiniMax parsed | κ(Opus,GPT) | κ(Opus,MiniMax) | κ(GPT,MiniMax) |
|------|---|-----------------|----------------|-------------------|------------------|
| no-context | 20 | 20 | 1.0000 | 1.0000 | 1.0000 |
| oracle-context | 20 | 20 | 0.7059 | 0.7917 | 0.7059 |
| full-context | 20 | 20 | 0.8000 | 0.7000 | 0.7059 |
| retrieval | 20 | 20 | 1.0000 | 0.8936 | 0.8936 |
| agentic | 20 | 20 | 0.7826 | 0.8980 | 0.6875 |
---
## §5 MiniMax operational metrics
- Calls: 100 total, parsed OK: **100/100 (100.0%)**
- Routing errors (non-200 HTTP): **0/100** (0.0%)
- Total retries: 0
- Latency p50: **11.9 s** | p95: **31.4 s**
- Token usage: prompt = 53,855, completion = 48,920
- Cost actual (OR MiniMax pricing $0.30/$1.20 per 1M): **~$0.0749**
Per brief §3.5 operational hedge thresholds:
- parse ≥95/100 target: **MET** — actual 100/100
- parse ≥90/100 halt: **MET** — actual 100/100
- latency p50 ≤25s: **MET** — actual 11.9s
- OR routing errors <5%: **MET** — actual 0.0%
---
## §6 Comparison to v5 historical baseline
v5 κ baseline reference: Fleiss' κ=0.7458 on three-way Opus+GPT+Gemini ensemble.
v6 κ(Opus, GPT) pairwise: **0.8480** — sanity check. If significantly different from v5 baseline range (~0.74-0.82 for a high-agreement pair), investigate.
v6 conservative trio κ (Opus+GPT+MiniMax): **0.7878**.

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"""
Manifest v6 Phase 1 — κ re-calibration computation
===================================================
Computes three pairwise Cohen's κ on 100-instance sample:
κ(Opus, GPT) — should match v5 historical baseline ~0.74-0.82
κ(Opus, MiniMax) — new measurement
κ(GPT, MiniMax) — new measurement
Conservative trio κ = min of the three.
Also reports:
- Raw agreement % per pair
- Confusion matrix per pair
- Per-cell breakdown (no-context / oracle-context / full-context /
retrieval / agentic)
- MiniMax operational metrics: parse rate, latency p50/p95, routing
errors, token usage
Writes:
kappa-v6-analysis.md — detailed matrix + per-cell breakdown
_summary-v6-kappa.json — machine-readable for halt ping
"""
from __future__ import annotations
import json
import statistics
from collections import Counter
from pathlib import Path
OUT_DIR = Path("D:/Projects/waggle-os/benchmarks/calibration/v6-kappa-recal")
SAMPLE_PATH = OUT_DIR / "kappa-sample-instances.jsonl"
RESPONSES_PATH = OUT_DIR / "minimax-kappa-responses.jsonl"
ANALYSIS_PATH = OUT_DIR / "kappa-v6-analysis.md"
SUMMARY_JSON = OUT_DIR / "_summary-v6-kappa.json"
def load_jsonl(path: Path) -> list[dict]:
out = []
with path.open("r", encoding="utf-8") as f:
for line in f:
line = line.strip()
if line:
out.append(json.loads(line))
return out
def cohen_kappa(pairs: list[tuple[str, str]]) -> tuple[float, dict]:
"""Cohen's κ on 2-class (correct/incorrect) pairs. Returns (κ, detail)."""
if not pairs:
return (float("nan"), {"n": 0, "agree": 0, "po": 0.0, "pe": 0.0})
n = len(pairs)
agree = sum(1 for a, b in pairs if a == b)
po = agree / n
a_counts = {"correct": 0, "incorrect": 0}
b_counts = {"correct": 0, "incorrect": 0}
for a, b in pairs:
a_counts[a] = a_counts.get(a, 0) + 1
b_counts[b] = b_counts.get(b, 0) + 1
pe = sum(
(a_counts.get(v, 0) / n) * (b_counts.get(v, 0) / n)
for v in ("correct", "incorrect")
)
if pe >= 1.0:
return (1.0 if po == 1.0 else float("nan"),
{"n": n, "agree": agree, "po": po, "pe": pe,
"a_counts": a_counts, "b_counts": b_counts})
kappa = (po - pe) / (1.0 - pe)
return (kappa, {"n": n, "agree": agree, "po": po, "pe": pe,
"a_counts": a_counts, "b_counts": b_counts})
def confusion_matrix(pairs: list[tuple[str, str]]) -> dict:
"""2x2 confusion (rows = judge A, cols = judge B)."""
cm = {"correct_correct": 0, "correct_incorrect": 0,
"incorrect_correct": 0, "incorrect_incorrect": 0}
for a, b in pairs:
key = f"{a}_{b}"
cm[key] = cm.get(key, 0) + 1
return cm
def classify_verdict(trio_kappa: float) -> str:
if trio_kappa != trio_kappa: # NaN
return "INCONCLUSIVE"
if trio_kappa >= 0.70:
return "PASS"
if trio_kappa >= 0.60:
return "BORDERLINE"
return "FAIL"
def fmt_k(x: float) -> str:
if x != x:
return "NaN"
return f"{x:.4f}"
def pct_str(num: int, denom: int) -> str:
if denom == 0:
return "—"
return f"{num}/{denom} ({num * 100.0 / denom:.1f}%)"
def main() -> int:
sample = load_jsonl(SAMPLE_PATH)
mm = load_jsonl(RESPONSES_PATH)
# Index MiniMax responses
mm_by_key = {(r["instance_id"], r["cell"]): r for r in mm}
# Build pair lists for 3 pairwise κ
pairs_og = [] # (Opus, GPT)
pairs_om = [] # (Opus, MiniMax)
pairs_gm = [] # (GPT, MiniMax)
per_cell = {"no-context": [], "oracle-context": [], "full-context": [],
"retrieval": [], "agentic": []}
mm_parse_ok = 0
mm_lat = []
mm_retries = 0
mm_routing_errors = 0
mm_prompt_tok = []
mm_comp_tok = []
for s in sample:
op_v = s.get("opus_verdict")
gp_v = s.get("gpt_verdict")
if op_v not in ("correct", "incorrect") or gp_v not in ("correct", "incorrect"):
continue
pairs_og.append((op_v, gp_v))
per_cell.setdefault(s["cell"], []).append(("og", op_v, gp_v))
key = (s["instance_id"], s["cell"])
m = mm_by_key.get(key)
if m is None:
continue
mm_v = m.get("parsed_verdict")
mm_lat.append(m.get("latency_ms") or 0)
mm_retries += m.get("retries") or 0
if m.get("http_status") != 200:
mm_routing_errors += 1
if m.get("prompt_tokens"):
mm_prompt_tok.append(m["prompt_tokens"])
if m.get("completion_tokens"):
mm_comp_tok.append(m["completion_tokens"])
if mm_v in ("correct", "incorrect"):
mm_parse_ok += 1
pairs_om.append((op_v, mm_v))
pairs_gm.append((gp_v, mm_v))
per_cell.setdefault(s["cell"], []).append(("om", op_v, mm_v))
per_cell.setdefault(s["cell"], []).append(("gm", gp_v, mm_v))
k_og, k_og_det = cohen_kappa(pairs_og)
k_om, k_om_det = cohen_kappa(pairs_om)
k_gm, k_gm_det = cohen_kappa(pairs_gm)
cm_og = confusion_matrix(pairs_og)
cm_om = confusion_matrix(pairs_om)
cm_gm = confusion_matrix(pairs_gm)
kappas = [k for k in (k_og, k_om, k_gm) if k == k]
k_trio = min(kappas) if kappas else float("nan")
verdict = classify_verdict(k_trio)
# Per-cell pairwise
per_cell_rows = []
cells_order = ["no-context", "oracle-context", "full-context", "retrieval", "agentic"]
for cell in cells_order:
triples = per_cell.get(cell, [])
pog = [(a, b) for t, a, b in triples if t == "og"]
pom = [(a, b) for t, a, b in triples if t == "om"]
pgm = [(a, b) for t, a, b in triples if t == "gm"]
k_c_og, _ = cohen_kappa(pog) if pog else (float("nan"), {})
k_c_om, _ = cohen_kappa(pom) if pom else (float("nan"), {})
k_c_gm, _ = cohen_kappa(pgm) if pgm else (float("nan"), {})
n_cell = len(pog)
mm_cell_parsed = len(pom)
per_cell_rows.append({
"cell": cell,
"n": n_cell,
"mm_parsed": mm_cell_parsed,
"k_og": k_c_og,
"k_om": k_c_om,
"k_gm": k_c_gm,
})
# Operational metrics
lat_p50 = int(statistics.median(mm_lat)) if mm_lat else 0
lat_p95 = int(sorted(mm_lat)[max(0, int(len(mm_lat) * 0.95) - 1)]) if mm_lat else 0
prompt_tok_total = sum(mm_prompt_tok)
comp_tok_total = sum(mm_comp_tok)
# OR MiniMax M2.7 pricing: $0.30/M prompt, $1.20/M completion
cost_actual = round(
(prompt_tok_total / 1_000_000) * 0.30 + (comp_tok_total / 1_000_000) * 1.20, 4
)
# ── Write kappa-v6-analysis.md ─────────────────────────────────────
lines = []
lines.append("# Manifest v6 κ Re-Calibration Analysis")
lines.append("")
lines.append("**Date:** 2026-04-24 **Parent:** `38a830e` (v6 Phase 1 Commit 2) **v6 anchor:** `60d061e`")
lines.append("")
lines.append(f"**Sample:** {len(sample)} instances from `benchmarks/results/locomo-mini-n20-retry-2026-04-24T00-02-12Z.jsonl` (authoritative v5 κ set; zero new Opus/GPT calls).")
lines.append("")
lines.append(f"**MiniMax verdicts:** {len(mm)} calls via OpenRouter `minimax/minimax-m2.7` (v6 alias: `minimax-m27-via-openrouter`); direct HTTP probe (LiteLLM proxy not in loop — isolates model behavior from middleware).")
lines.append("")
lines.append(f"**Prompt:** verbatim `failure-mode-judge.ts:245-258` (same as §1.3g / §1.3h / §1.3h-C).")
lines.append(f"**Parameters:** `temperature=0.0`, `max_tokens=4096`.")
lines.append("")
lines.append("---")
lines.append("")
lines.append("## §1 Three pairwise Cohen's κ")
lines.append("")
lines.append("| Pair | n | Agree | Raw % | κ |")
lines.append("|------|---|-------|-------|-----|")
lines.append(f"| Opus vs GPT | {k_og_det['n']} | {k_og_det['agree']} | {k_og_det['po']*100:.2f}% | **{fmt_k(k_og)}** |")
lines.append(f"| Opus vs MiniMax | {k_om_det['n']} | {k_om_det['agree']} | {k_om_det['po']*100:.2f}% | **{fmt_k(k_om)}** |")
lines.append(f"| GPT vs MiniMax | {k_gm_det['n']} | {k_gm_det['agree']} | {k_gm_det['po']*100:.2f}% | **{fmt_k(k_gm)}** |")
lines.append("")
lines.append(f"**Conservative trio κ = min = {fmt_k(k_trio)}**")
lines.append("")
lines.append(f"## §2 Verdict: **{verdict}**")
lines.append("")
lines.append("Per v6 §5.4 gate criteria:")
lines.append("- `κ_trio ≥ 0.70` → PASS, halt with PM-RATIFY-V6-KAPPA")
lines.append("- `0.60 ≤ κ_trio < 0.70` → BORDERLINE, halt with PM adjudication")
lines.append("- `κ_trio < 0.60` → FAIL, halt with swap-path-re-evaluation")
lines.append("")
lines.append("---")
lines.append("")
lines.append("## §3 Confusion matrices")
lines.append("")
lines.append("### Opus vs GPT")
lines.append("")
lines.append("| | GPT=correct | GPT=incorrect |")
lines.append("|---|---|---|")
lines.append(f"| **Opus=correct** | {cm_og.get('correct_correct', 0)} | {cm_og.get('correct_incorrect', 0)} |")
lines.append(f"| **Opus=incorrect** | {cm_og.get('incorrect_correct', 0)} | {cm_og.get('incorrect_incorrect', 0)} |")
lines.append("")
lines.append("### Opus vs MiniMax")
lines.append("")
lines.append("| | MiniMax=correct | MiniMax=incorrect |")
lines.append("|---|---|---|")
lines.append(f"| **Opus=correct** | {cm_om.get('correct_correct', 0)} | {cm_om.get('correct_incorrect', 0)} |")
lines.append(f"| **Opus=incorrect** | {cm_om.get('incorrect_correct', 0)} | {cm_om.get('incorrect_incorrect', 0)} |")
lines.append("")
lines.append("### GPT vs MiniMax")
lines.append("")
lines.append("| | MiniMax=correct | MiniMax=incorrect |")
lines.append("|---|---|---|")
lines.append(f"| **GPT=correct** | {cm_gm.get('correct_correct', 0)} | {cm_gm.get('correct_incorrect', 0)} |")
lines.append(f"| **GPT=incorrect** | {cm_gm.get('incorrect_correct', 0)} | {cm_gm.get('incorrect_incorrect', 0)} |")
lines.append("")
lines.append("---")
lines.append("")
lines.append("## §4 Per-cell κ breakdown (n=20 per cell)")
lines.append("")
lines.append("| Cell | n | MiniMax parsed | κ(Opus,GPT) | κ(Opus,MiniMax) | κ(GPT,MiniMax) |")
lines.append("|------|---|-----------------|----------------|-------------------|------------------|")
for row in per_cell_rows:
lines.append(
f"| {row['cell']} | {row['n']} | {row['mm_parsed']} "
f"| {fmt_k(row['k_og'])} | {fmt_k(row['k_om'])} | {fmt_k(row['k_gm'])} |"
)
lines.append("")
lines.append("---")
lines.append("")
lines.append("## §5 MiniMax operational metrics")
lines.append("")
lines.append(f"- Calls: {len(mm)} total, parsed OK: **{pct_str(mm_parse_ok, len(mm))}**")
lines.append(f"- Routing errors (non-200 HTTP): **{mm_routing_errors}/{len(mm)}** ({mm_routing_errors*100/len(mm):.1f}%)")
lines.append(f"- Total retries: {mm_retries}")
lines.append(f"- Latency p50: **{lat_p50/1000:.1f} s** | p95: **{lat_p95/1000:.1f} s**")
lines.append(f"- Token usage: prompt = {prompt_tok_total:,}, completion = {comp_tok_total:,}")
lines.append(f"- Cost actual (OR MiniMax pricing $0.30/$1.20 per 1M): **~${cost_actual}**")
lines.append("")
lines.append(f"Per brief §3.5 operational hedge thresholds:")
lines.append(f"- parse ≥95/100 target: **{'MET' if mm_parse_ok >= 95 else 'MISS (below target)'}** — actual {mm_parse_ok}/100")
lines.append(f"- parse ≥90/100 halt: **{'MET' if mm_parse_ok >= 90 else 'FAIL (halt)'}** — actual {mm_parse_ok}/100")
lines.append(f"- latency p50 ≤25s: **{'MET' if lat_p50 <= 25000 else 'MISS'}** — actual {lat_p50/1000:.1f}s")
lines.append(f"- OR routing errors <5%: **{'MET' if mm_routing_errors < 5 else 'FLAG'}** — actual {mm_routing_errors/len(mm)*100:.1f}%")
lines.append("")
lines.append("---")
lines.append("")
lines.append(f"## §6 Comparison to v5 historical baseline")
lines.append("")
lines.append(f"v5 κ baseline reference: Fleiss' κ=0.7458 on three-way Opus+GPT+Gemini ensemble.")
lines.append(f"v6 κ(Opus, GPT) pairwise: **{fmt_k(k_og)}** — sanity check. If significantly different from v5 baseline range (~0.74-0.82 for a high-agreement pair), investigate.")
lines.append(f"v6 conservative trio κ (Opus+GPT+MiniMax): **{fmt_k(k_trio)}**.")
ANALYSIS_PATH.write_text("\n".join(lines), encoding="utf-8")
print(f"Wrote {ANALYSIS_PATH}")
# Machine-readable summary
summary = {
"verdict": verdict,
"k_opus_gpt": k_og,
"k_opus_minimax": k_om,
"k_gpt_minimax": k_gm,
"k_conservative_trio": k_trio,
"minimax_parse_success": mm_parse_ok,
"minimax_n_total": len(mm),
"minimax_lat_p50_ms": lat_p50,
"minimax_lat_p95_ms": lat_p95,
"minimax_routing_errors": mm_routing_errors,
"minimax_retries_total": mm_retries,
"minimax_prompt_tokens_total": prompt_tok_total,
"minimax_completion_tokens_total": comp_tok_total,
"cost_actual_usd": cost_actual,
"per_cell": per_cell_rows,
"confusion_opus_gpt": cm_og,
"confusion_opus_minimax": cm_om,
"confusion_gpt_minimax": cm_gm,
}
SUMMARY_JSON.write_text(json.dumps(summary, indent=2, default=str), encoding="utf-8")
print(f"Wrote {SUMMARY_JSON}")
print(f"\nVerdict: {verdict}")
print(f"k(Opus, GPT) = {fmt_k(k_og)}")
print(f"k(Opus, MiniMax) = {fmt_k(k_om)}")
print(f"k(GPT, MiniMax) = {fmt_k(k_gm)}")
print(f"k_trio (min) = {fmt_k(k_trio)}")
print(f"MiniMax parse = {mm_parse_ok}/100")
print(f"Cost = ${cost_actual}")
return 0
if __name__ == "__main__":
import sys
sys.exit(main())

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"""
Manifest v6 Phase 1 Commit 3 — MiniMax κ re-calibration probe
==============================================================
Executes 100 MiniMax M2.7 verdicts (via OpenRouter) on the authoritative
v5 κ calibration set:
benchmarks/results/locomo-mini-n20-retry-2026-04-24T00-02-12Z.jsonl
Reuses existing Opus + GPT verdicts from judge_ensemble field (zero new
calls for those). Reuses LoCoMo fixtures for question/ground_truth/
context lookup by instance_id (same pattern as §1.3g/h probes).
Routing: same OR endpoint as §1.3h (direct HTTP, bypasses LiteLLM proxy
for probe speed). The v6 LiteLLM alias wiring (minimax-m27-via-openrouter)
will be validated end-to-end in Phase 2 N=400 execution; κ re-cal
isolates model behavior from middleware.
Prompt: verbatim from failure-mode-judge.ts:245-258 (identical to §1.3g
and §1.3h probes).
Operational hedge per brief §3.5:
- Log parse rate (target ≥95/100, halt <90/100)
- Log latency p50 (target ≤25s) + p95
- Log OR routing errors (>5% rate raises PM flag pre-κ compute)
Scope guards:
- Parent HEAD = 38a830e (v6 Phase 1 Commit 2 anchor)
- v6 manifest anchor = 60d061e (Commit 1)
- §11 frozen paths except litellm-config.yaml (already amended in Commit 2)
- No runner/judge-runner/failure-mode-judge edits
Budget: ~$2.50 expected (100 calls × $0.02 avg per §1.3h MiniMax pricing).
Cap: $30 Phase 1 total.
Usage:
python minimax-kappa-probe.py
"""
from __future__ import annotations
import json
import sys
import time
import urllib.error
import urllib.request
from datetime import datetime, timezone
from pathlib import Path
try:
sys.stdout.reconfigure(encoding="utf-8", errors="replace")
sys.stderr.reconfigure(encoding="utf-8", errors="replace")
except Exception:
pass
# ── Paths ───────────────────────────────────────────────────────────────
OUT_DIR = Path("D:/Projects/waggle-os/benchmarks/calibration/v6-kappa-recal")
CAL_SRC = Path("D:/Projects/waggle-os/benchmarks/results/locomo-mini-n20-retry-2026-04-24T00-02-12Z.jsonl")
LOCOMO = Path("D:/Projects/waggle-os/benchmarks/data/locomo/locomo-1540.jsonl")
RESPONSES_PATH = OUT_DIR / "minimax-kappa-responses.jsonl"
SAMPLE_PATH = OUT_DIR / "kappa-sample-instances.jsonl"
# ── Verbatim judge prompt (same as §1.3g and §1.3h) ─────────────────────
JUDGE_PROMPT_TEMPLATE = "\n".join([
"You are evaluating whether an LLM's answer is correct against ground truth.",
"",
"## Question",
"{question}",
"",
"## Ground-truth answer",
"{ground_truth}",
"",
"## Ground-truth supporting context (excerpt shown to the model)",
"{context}",
"",
"## Model's answer",
"{model_answer}",
"",
"## Your task",
"",
"Step 1: Determine if the model's answer is correct.",
"- \"correct\" means the model's answer contains all required facts from ground truth, with no additional incorrect claims.",
"- Minor phrasing differences, synonyms, or alternative but equivalent formulations are acceptable.",
"- Extra detail is acceptable ONLY if it is factually correct.",
"",
"Step 2: If incorrect, assign exactly one failure mode using this decision tree:",
"",
"1. Does the model explicitly refuse or say it does not know? -> F1 (ABSTAIN)",
"2. Does the model answer a DIFFERENT question than was asked (coherent but off-topic)? -> F5 (OFF-TOPIC)",
"3. Does the model rely on entities, names, dates, or claims that do NOT appear in the ground-truth context (fabrication)? -> F4 (HALLUCINATED)",
"4. Does the model correctly state SOME required facts but miss others, without stating any incorrect facts? -> F2 (PARTIAL)",
"5. Otherwise (model states facts derived from the context but gets them wrong): -> F3 (INCORRECT)",
"",
"Step 3: Return JSON only, no prose, in this exact schema:",
"",
"{{",
" \"verdict\": \"correct\" | \"incorrect\",",
" \"failure_mode\": null | \"F1\" | \"F2\" | \"F3\" | \"F4\" | \"F5\",",
" \"rationale\": \"one sentence explaining the verdict\"",
"}}",
"",
"If verdict is \"correct\", failure_mode MUST be null.",
"If verdict is \"incorrect\", failure_mode MUST be one of F1-F5.",
])
def ts() -> str:
return datetime.now(timezone.utc).isoformat()
def logmsg(msg: str) -> None:
print(f"{ts()} {msg}", flush=True)
def load_env() -> dict[str, str]:
env_path = Path("D:/Projects/waggle-os/.env")
out: dict[str, str] = {}
for line in env_path.read_text(encoding="utf-8").splitlines():
line = line.strip()
if not line or line.startswith("#") or "=" not in line:
continue
k, _, v = line.partition("=")
out[k.strip()] = v.strip().strip('"').strip("'")
return out
import re
def extract_json_body(raw: str) -> dict | None:
if not raw:
return None
trimmed = raw.strip()
if trimmed.startswith("```"):
m = re.match(r"^```(?:json)?\s*\n?(.*?)```\s*$", trimmed, re.DOTALL)
if m:
trimmed = m.group(1).strip()
try:
return json.loads(trimmed)
except Exception:
pass
first = trimmed.find("{")
last = trimmed.rfind("}")
if first != -1 and last != -1 and last > first:
try:
return json.loads(trimmed[first:last + 1])
except Exception:
return None
return None
def parse_verdict(raw: str) -> tuple[str | None, str | None, str | None]:
body = extract_json_body(raw)
if not isinstance(body, dict):
return (None, None, None)
v = body.get("verdict")
fm = body.get("failure_mode")
rat = body.get("rationale")
if v not in ("correct", "incorrect"):
return (None, None, None)
if fm is not None and fm not in ("F1", "F2", "F3", "F4", "F5"):
fm = None
return (v, fm, rat if isinstance(rat, str) else None)
def http_post_json(url: str, headers: dict, body: dict, timeout_s: int = 60) -> tuple[int, dict | str]:
req = urllib.request.Request(
url, data=json.dumps(body).encode("utf-8"), method="POST",
headers={"Content-Type": "application/json", **headers},
)
try:
with urllib.request.urlopen(req, timeout=timeout_s) as resp:
raw = resp.read().decode("utf-8", errors="replace")
try:
return resp.status, json.loads(raw)
except Exception:
return resp.status, raw
except urllib.error.HTTPError as e:
try:
return e.code, e.read().decode("utf-8", errors="replace")[:2000]
except Exception:
return e.code, ""
except Exception as e:
return 0, f"{type(e).__name__}: {e}"
def call_minimax_via_openrouter(prompt: str, or_key: str, max_attempts: int = 3) -> dict:
url = "https://openrouter.ai/api/v1/chat/completions"
headers = {"Authorization": f"Bearer {or_key}"}
body = {
"model": "minimax/minimax-m2.7",
"messages": [{"role": "user", "content": prompt}],
"temperature": 0.0,
"max_tokens": 4096,
}
started = time.time()
retries = 0
last_err = None
for attempt in range(max_attempts):
status, resp = http_post_json(url, headers, body, timeout_s=90)
if status == 200 and isinstance(resp, dict):
choices = resp.get("choices") or []
if choices:
msg = choices[0].get("message") or {}
content = msg.get("content") or msg.get("reasoning_content") or ""
usage = resp.get("usage", {})
return {
"raw_text": content,
"status": 200,
"error": None,
"retries": retries,
"latency_ms": int((time.time() - started) * 1000),
"prompt_tokens": usage.get("prompt_tokens"),
"completion_tokens": usage.get("completion_tokens"),
}
last_err = f"status={status} resp={str(resp)[:400]}"
retries += 1
if attempt < max_attempts - 1:
time.sleep(2 ** attempt)
return {
"raw_text": "",
"status": 0,
"error": last_err,
"retries": retries,
"latency_ms": int((time.time() - started) * 1000),
"prompt_tokens": None,
"completion_tokens": None,
}
def build_sample() -> list[dict]:
"""Load all 100 κ calibration instances with enriched LoCoMo fixture."""
rows = []
with CAL_SRC.open("r", encoding="utf-8") as f:
for line in f:
line = line.strip()
if not line:
continue
rows.append(json.loads(line))
locomo_by_id = {}
with LOCOMO.open("r", encoding="utf-8") as f:
for line in f:
line = line.strip()
if not line:
continue
r = json.loads(line)
locomo_by_id[r.get("instance_id")] = r
enriched = []
for r in rows:
iid = r.get("instance_id")
ensemble = r.get("judge_ensemble") or []
opus = next((j for j in ensemble if "opus" in j.get("model", "").lower()), None)
gpt = next((j for j in ensemble if "gpt" in j.get("model", "").lower()), None)
gemini = next((j for j in ensemble if "gemini" in j.get("model", "").lower()), None)
loc = locomo_by_id.get(iid) or {}
gt = ((loc.get("expected") or [loc.get("gold_answer", "")])[0]) if loc else ""
enriched.append({
"instance_id": iid,
"cell": r.get("cell"),
"question": loc.get("question") or "",
"ground_truth": gt,
"context": loc.get("context") or "",
"model_answer": r.get("model_answer") or "",
"opus_verdict": (opus or {}).get("verdict"),
"opus_failure_mode": (opus or {}).get("failure_mode"),
"gpt_verdict": (gpt or {}).get("verdict"),
"gpt_failure_mode": (gpt or {}).get("failure_mode"),
"gemini_verdict_v5": (gemini or {}).get("verdict"),
"gemini_failure_mode_v5": (gemini or {}).get("failure_mode"),
})
return enriched
def main() -> int:
logmsg("[v6-kappa] MiniMax 100-instance re-calibration START")
env = load_env()
or_key = env.get("OPENROUTER_API_KEY", "").strip()
if not or_key:
logmsg("[v6-kappa] FATAL OPENROUTER_API_KEY missing")
return 2
OUT_DIR.mkdir(parents=True, exist_ok=True)
sample = build_sample()
logmsg(f"[v6-kappa] loaded {len(sample)} κ instances from {CAL_SRC.name}")
# Persist enriched sample for kappa compute
with SAMPLE_PATH.open("w", encoding="utf-8") as f:
for s in sample:
f.write(json.dumps(s, ensure_ascii=False) + "\n")
logmsg(f"[v6-kappa] wrote enriched sample to {SAMPLE_PATH.name}")
# Execute 100 MiniMax calls (sequential, with per-call retries)
rows = []
started_run = time.time()
routing_errors = 0
for i, s in enumerate(sample):
prompt = JUDGE_PROMPT_TEMPLATE.format(
question=s["question"],
ground_truth=s["ground_truth"],
context=s["context"],
model_answer=s["model_answer"],
)
resp = call_minimax_via_openrouter(prompt, or_key)
verdict, fm, rat = parse_verdict(resp["raw_text"])
if resp["status"] != 200:
routing_errors += 1
rows.append({
"instance_id": s["instance_id"],
"cell": s["cell"],
"provider": "minimax",
"model_id": "minimax/minimax-m2.7",
"routing": "openrouter_direct_http",
"litellm_alias_registered": "minimax-m27-via-openrouter",
"http_status": resp["status"],
"error": resp.get("error"),
"retries": resp["retries"],
"latency_ms": resp["latency_ms"],
"prompt_tokens": resp.get("prompt_tokens"),
"completion_tokens": resp.get("completion_tokens"),
"raw_text": resp["raw_text"],
"parsed_verdict": verdict,
"parsed_failure_mode": fm,
"parsed_rationale": rat,
"opus_verdict_ref": s["opus_verdict"],
"gpt_verdict_ref": s["gpt_verdict"],
})
if (i + 1) % 10 == 0 or i == 0:
elapsed = time.time() - started_run
parsed_so_far = sum(1 for r in rows if r.get("parsed_verdict") is not None)
logmsg(
f"[v6-kappa] {i+1:>3}/{len(sample)} {s['instance_id']:30} cell={s['cell']:14} "
f"status={resp['status']} verdict={verdict} parse_ok={parsed_so_far}/{i+1} "
f"routing_err={routing_errors} elapsed={elapsed:.0f}s"
)
# Halt-before-compute check if parse < 90/100
parsed = sum(1 for r in rows if r.get("parsed_verdict") is not None)
logmsg(f"[v6-kappa] completed {len(rows)} calls; parsed={parsed}/100; routing_errors={routing_errors}")
# Write responses regardless of halt status
with RESPONSES_PATH.open("w", encoding="utf-8") as f:
for r in rows:
f.write(json.dumps(r, ensure_ascii=False) + "\n")
logmsg(f"[v6-kappa] wrote {RESPONSES_PATH.name}")
if parsed < 90:
logmsg(f"[v6-kappa] HALT_BEFORE_COMPUTE: parse rate {parsed}/100 < 90 threshold (per brief §3.5)")
return 3
if routing_errors > 5:
logmsg(f"[v6-kappa] ROUTING_ERROR_RATE_FLAG: {routing_errors}/100 > 5% threshold (per brief §3.5)")
return 4
logmsg("[v6-kappa] probe step complete; κ computation handled by kappa-v6-compute.py")
logmsg("[v6-kappa] END")
return 0
if __name__ == "__main__":
import traceback
try:
sys.exit(main())
except Exception as e:
logmsg(f"[FATAL] {type(e).__name__}: {e}")
logmsg(traceback.format_exc()[:2000])
sys.exit(99)

100
benchmarks/calibration/v6-kappa-recal/minimax-kappa-responses.jsonl Normal file
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@@ -0,0 +1,100 @@
{"instance_id": "locomo_conv-50_q086", "cell": "no-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 17733, "prompt_tokens": 505, "completion_tokens": 571, "raw_text": "```json\n{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F3\",\n \"rationale\": \"The model answered 'Surfing' when the ground truth clearly indicates Calvin is planning to go skiing (evidenced by the snowy peak description and image of a person on skis).\"\n}\n```", "parsed_verdict": "incorrect", "parsed_failure_mode": "F3", "parsed_rationale": "The model answered 'Surfing' when the ground truth clearly indicates Calvin is planning to go skiing (evidenced by the snowy peak description and image of a person on skis).", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-26_q059", "cell": "no-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 16903, "prompt_tokens": 593, "completion_tokens": 623, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F1\",\n \"rationale\": \"The model refused to answer the question by stating it cannot be determined without context, even though the ground-truth context was provided and contains sufficient information to conclude that Caroline is somewhat, but not extremely religious based on her making art for a church while not exhibiting strongly religious behavior.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F1", "parsed_rationale": "The model refused to answer the question by stating it cannot be determined without context, even though the ground-truth context was provided and contains sufficient information to conclude that Caroline is somewhat, but not extremely religious based on her making art for a church while not exhibiting strongly religious behavior.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-44_q000", "cell": "no-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 15866, "prompt_tokens": 450, "completion_tokens": 610, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F4\",\n \"rationale\": \"The model answered 1954, which is a date that does not appear in the ground-truth context and cannot be derived from the provided information (session date of March 2023 and '3 years' tenure would imply ~2020, not 1954), indicating the model fabricated an answer.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F4", "parsed_rationale": "The model answered 1954, which is a date that does not appear in the ground-truth context and cannot be derived from the provided information (session date of March 2023 and '3 years' tenure would imply ~2020, not 1954), indicating the model fabricated an answer.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-41_q080", "cell": "no-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 11086, "prompt_tokens": 521, "completion_tokens": 554, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F4\",\n \"rationale\": \"The model provided 'A wind chime' which does not appear anywhere in the ground-truth context; the correct answer is 'painting of a castle on a hill' as explicitly stated by Maria in the supporting context.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F4", "parsed_rationale": "The model provided 'A wind chime' which does not appear anywhere in the ground-truth context; the correct answer is 'painting of a castle on a hill' as explicitly stated by Maria in the supporting context.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-42_q001", "cell": "no-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 27267, "prompt_tokens": 742, "completion_tokens": 942, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F3\",\n \"rationale\": \"The model's answer 'Reading' does not appear in the ground truth answer, and while reading appears in the context as only Joanna's interest (not Nate's), it is not a shared interest; the actual shared interests are watching movies and making desserts.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F3", "parsed_rationale": "The model's answer 'Reading' does not appear in the ground truth answer, and while reading appears in the context as only Joanna's interest (not Nate's), it is not a shared interest; the actual shared interests are watching movies and making desserts.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-43_q155", "cell": "no-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 21117, "prompt_tokens": 464, "completion_tokens": 551, "raw_text": "{\"verdict\": \"incorrect\", \"failure_mode\": \"F3\", \"rationale\": \"The model states John felt 'relieved', but the ground truth explicitly says John felt it was a 'huge success' - these are different emotional states.\"}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F3", "parsed_rationale": "The model states John felt 'relieved', but the ground truth explicitly says John felt it was a 'huge success' - these are different emotional states.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-50_q015", "cell": "no-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 5779, "prompt_tokens": 553, "completion_tokens": 198, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F1\",\n \"rationale\": \"The model explicitly states 'Unknown', refusing to provide an answer, which is a refusal to answer based on available context.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F1", "parsed_rationale": "The model explicitly states 'Unknown', refusing to provide an answer, which is a refusal to answer based on available context.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-48_q020", "cell": "no-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 8704, "prompt_tokens": 710, "completion_tokens": 493, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F4\",\n \"rationale\": \"The model mentions games (Animal Crossing and Minecraft) that do not appear anywhere in the ground-truth context, which consists only of Detroit, Walking Dead, Battlefield 1, It Takes Two, and Overcooked 2.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F4", "parsed_rationale": "The model mentions games (Animal Crossing and Minecraft) that do not appear anywhere in the ground-truth context, which consists only of Detroit, Walking Dead, Battlefield 1, It Takes Two, and Overcooked 2.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-48_q055", "cell": "no-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 9606, "prompt_tokens": 510, "completion_tokens": 625, "raw_text": "```json\n{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer 'Seraphim' matches the ground-truth answer exactly, and while the context excerpts don't explicitly name the pets, the model's answer is confirmed correct by the ground truth.\"\n}\n```", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer 'Seraphim' matches the ground-truth answer exactly, and while the context excerpts don't explicitly name the pets, the model's answer is confirmed correct by the ground truth.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}
{"instance_id": "locomo_conv-26_q128", "cell": "no-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 14317, "prompt_tokens": 493, "completion_tokens": 555, "raw_text": "```json\n{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F4\",\n \"rationale\": \"The model answered 'A butterfly,' which is an entity that does not appear anywhere in the ground-truth context; the correct answer is 'a rainbow sidewalk.'\"\n}\n```", "parsed_verdict": "incorrect", "parsed_failure_mode": "F4", "parsed_rationale": "The model answered 'A butterfly,' which is an entity that does not appear anywhere in the ground-truth context; the correct answer is 'a rainbow sidewalk.'", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-50_q010", "cell": "no-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 23529, "prompt_tokens": 504, "completion_tokens": 606, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F4\",\n \"rationale\": \"The model provided the date 'October 2019' which does not appear in the ground-truth context (which indicates the flooding occurred around May 9, 2023), constituting a fabrication.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F4", "parsed_rationale": "The model provided the date 'October 2019' which does not appear in the ground-truth context (which indicates the flooding occurred around May 9, 2023), constituting a fabrication.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-50_q078", "cell": "no-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 16510, "prompt_tokens": 475, "completion_tokens": 604, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F4\",\n \"rationale\": \"The model answered 'Home,' which does not appear in the ground-truth context and is unrelated to the stated purpose of the necklace as a reminder of why Calvin keeps hustling as a musician.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F4", "parsed_rationale": "The model answered 'Home,' which does not appear in the ground-truth context and is unrelated to the stated purpose of the necklace as a reminder of why Calvin keeps hustling as a musician.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-47_q092", "cell": "no-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 18246, "prompt_tokens": 487, "completion_tokens": 539, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F3\",\n \"rationale\": \"The model states 'a database' which is factually incorrect; the ground-truth context clearly states John created an application on smartphones, not a database.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F3", "parsed_rationale": "The model states 'a database' which is factually incorrect; the ground-truth context clearly states John created an application on smartphones, not a database.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-30_q057", "cell": "no-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 10809, "prompt_tokens": 503, "completion_tokens": 374, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F2\",\n \"rationale\": \"The model correctly states one relevant fact about focusing on customers (related to building relationships) but omits the other two required pieces of advice: creating a strong brand image and staying positive.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F2", "parsed_rationale": "The model correctly states one relevant fact about focusing on customers (related to building relationships) but omits the other two required pieces of advice: creating a strong brand image and staying positive.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-30_q029", "cell": "no-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 5371, "prompt_tokens": 565, "completion_tokens": 288, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F1\",\n \"rationale\": \"The model explicitly stated 'Unknown' when the answer (Paris and Rome) could be directly extracted from the provided supporting context.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F1", "parsed_rationale": "The model explicitly stated 'Unknown' when the answer (Paris and Rome) could be directly extracted from the provided supporting context.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-44_q066", "cell": "no-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 6208, "prompt_tokens": 492, "completion_tokens": 194, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer 'A small dog' is semantically equivalent to the ground truth 'smaller dog' and correctly captures Andrew's preference for his apartment living space.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer 'A small dog' is semantically equivalent to the ground truth 'smaller dog' and correctly captures Andrew's preference for his apartment living space.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}
{"instance_id": "locomo_conv-44_q002", "cell": "no-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 4165, "prompt_tokens": 739, "completion_tokens": 332, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F2\",\n \"rationale\": \"The model only mentions board games but misses the other three indoor activities (volunteering at pet shelter, wine tasting, and growing flowers) listed in the ground truth.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F2", "parsed_rationale": "The model only mentions board games but misses the other three indoor activities (volunteering at pet shelter, wine tasting, and growing flowers) listed in the ground truth.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-47_q046", "cell": "no-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 7787, "prompt_tokens": 460, "completion_tokens": 584, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F3\",\n \"rationale\": \"The model states they 'Never' met, but the context indicates John and James planned to meet the next day (August 27, 2022) at McGee's Pub, making the model's answer factually incorrect.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F3", "parsed_rationale": "The model states they 'Never' met, but the context indicates John and James planned to meet the next day (August 27, 2022) at McGee's Pub, making the model's answer factually incorrect.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-43_q076", "cell": "no-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 24634, "prompt_tokens": 476, "completion_tokens": 718, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F4\",\n \"rationale\": \"The model claims the picture was 'a selfie' which does not appear in the ground-truth context; the context only states the picture is from MinaLima, a prop creator for the Harry Potter films, not a selfie.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F4", "parsed_rationale": "The model claims the picture was 'a selfie' which does not appear in the ground-truth context; the context only states the picture is from MinaLima, a prop creator for the Harry Potter films, not a selfie.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-41_q065", "cell": "no-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 8845, "prompt_tokens": 458, "completion_tokens": 627, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F1\",\n \"rationale\": \"The model explicitly states it does not know which John is being referred to, effectively refusing to answer the question despite the ground-truth context clearly identifying a John who states his main focuses are improving education and infrastructure.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F1", "parsed_rationale": "The model explicitly states it does not know which John is being referred to, effectively refusing to answer the question despite the ground-truth context clearly identifying a John who states his main focuses are improving education and infrastructure.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-50_q086", "cell": "oracle-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 5159, "prompt_tokens": 503, "completion_tokens": 267, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer 'Skiing' matches the ground truth exactly and is supported by the context, which mentions Calvin's to-do list after the tour and includes an image of skiing on a snowy mountain.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer 'Skiing' matches the ground truth exactly and is supported by the context, which mentions Calvin's to-do list after the tour and includes an image of skiing on a snowy mountain.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}
{"instance_id": "locomo_conv-26_q059", "cell": "oracle-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 31426, "prompt_tokens": 569, "completion_tokens": 1075, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F2\",\n \"rationale\": \"The model answers 'Yes' which is partially correct (Caroline has some religious connection via her church artwork) but fails to capture the nuance that ground truth specifies: she is 'somewhat, but not extremely religious.'\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F2", "parsed_rationale": "The model answers 'Yes' which is partially correct (Caroline has some religious connection via her church artwork) but fails to capture the nuance that ground truth specifies: she is 'somewhat, but not extremely religious.'", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-44_q000", "cell": "oracle-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 7232, "prompt_tokens": 470, "completion_tokens": 291, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model correctly answered 2020, which matches the ground truth and is correctly derived from the context stating Audrey had her three dogs (Pepper, Precious, and Panda) for 3 years as of March 2023.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model correctly answered 2020, which matches the ground truth and is correctly derived from the context stating Audrey had her three dogs (Pepper, Precious, and Panda) for 3 years as of March 2023.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}
{"instance_id": "locomo_conv-41_q080", "cell": "oracle-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 6440, "prompt_tokens": 517, "completion_tokens": 559, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F2\",\n \"rationale\": \"The model correctly identifies that Maria made a painting, but it omits the specific detail that the painting depicts a castle on a hill, which is a required fact from the ground truth.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F2", "parsed_rationale": "The model correctly identifies that Maria made a painting, but it omits the specific detail that the painting depicts a castle on a hill, which is a required fact from the ground truth.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-42_q001", "cell": "oracle-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 4720, "prompt_tokens": 762, "completion_tokens": 254, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F2\",\n \"rationale\": \"The model correctly identified movies as a shared interest but failed to include making desserts, which is also mentioned in the ground-truth answer.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F2", "parsed_rationale": "The model correctly identified movies as a shared interest but failed to include making desserts, which is also mentioned in the ground-truth answer.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-43_q155", "cell": "oracle-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 11079, "prompt_tokens": 480, "completion_tokens": 396, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer 'Great' is a synonym for 'a huge success' and correctly captures John's positive feeling about jogging without pain.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer 'Great' is a synonym for 'a huge success' and correctly captures John's positive feeling about jogging without pain.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-50_q015", "cell": "oracle-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 14900, "prompt_tokens": 571, "completion_tokens": 540, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer 'To relax' is a correct and equivalent formulation of the ground truth 'because it relaxes and calms him,' as 'relax' and 'calms' are synonymous concepts that capture the same essential fact about why Dave visits parks.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer 'To relax' is a correct and equivalent formulation of the ground truth 'because it relaxes and calms him,' as 'relax' and 'calms' are synonymous concepts that capture the same essential fact about why Dave visits parks.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-48_q020", "cell": "oracle-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 16522, "prompt_tokens": 719, "completion_tokens": 265, "raw_text": "```json\n{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F2\",\n \"rationale\": \"The model correctly identified three games (Detroit, It Takes Two, Overcooked 2) but missed two others (Walking Dead, Battlefield 1) that appear in the ground truth.\"\n}\n```", "parsed_verdict": "incorrect", "parsed_failure_mode": "F2", "parsed_rationale": "The model correctly identified three games (Detroit, It Takes Two, Overcooked 2) but missed two others (Walking Dead, Battlefield 1) that appear in the ground truth.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-48_q055", "cell": "oracle-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 44330, "prompt_tokens": 509, "completion_tokens": 976, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F3\",\n \"rationale\": \"The model answered Susie, but the ground truth states Seraphim was adopted more recently, indicating the model derived incorrect facts from the context.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F3", "parsed_rationale": "The model answered Susie, but the ground truth states Seraphim was adopted more recently, indicating the model derived incorrect facts from the context.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-26_q128", "cell": "oracle-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 3221, "prompt_tokens": 491, "completion_tokens": 216, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer 'A rainbow sidewalk' exactly matches the ground-truth answer 'a rainbow sidewalk' with only a minor capitalization difference, making it correct.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer 'A rainbow sidewalk' exactly matches the ground-truth answer 'a rainbow sidewalk' with only a minor capitalization difference, making it correct.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}
{"instance_id": "locomo_conv-50_q010", "cell": "oracle-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 13441, "prompt_tokens": 485, "completion_tokens": 336, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer 'Last week' is equivalent to the ground truth 'a week before 16 May, 2023' since the conversation occurred on 16 May 2023, making minor phrasing differences acceptable.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer 'Last week' is equivalent to the ground truth 'a week before 16 May, 2023' since the conversation occurred on 16 May 2023, making minor phrasing differences acceptable.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}
{"instance_id": "locomo_conv-50_q078", "cell": "oracle-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 9610, "prompt_tokens": 482, "completion_tokens": 303, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer matches the ground truth exactly, capturing the fact that the necklace was meant to remind Calvin of why he keeps hustling as a musician, with only a minor capitalization difference that doesn't affect meaning.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer matches the ground truth exactly, capturing the fact that the necklace was meant to remind Calvin of why he keeps hustling as a musician, with only a minor capitalization difference that doesn't affect meaning.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}
{"instance_id": "locomo_conv-47_q092", "cell": "oracle-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 9489, "prompt_tokens": 487, "completion_tokens": 422, "raw_text": "```json\n{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F2\",\n \"rationale\": \"The model's answer correctly identifies that John created an application but omits the specific detail that it was on smartphones, which is a required fact from the ground truth.\"\n}\n```", "parsed_verdict": "incorrect", "parsed_failure_mode": "F2", "parsed_rationale": "The model's answer correctly identifies that John created an application but omits the specific detail that it was on smartphones, which is a required fact from the ground truth.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-30_q057", "cell": "oracle-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 71668, "prompt_tokens": 498, "completion_tokens": 2221, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F1\",\n \"rationale\": \"The model explicitly states 'Not mentioned' to avoid providing an answer, even though the advice content (brand identity, building relationships, staying positive) is present in the context.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F1", "parsed_rationale": "The model explicitly states 'Not mentioned' to avoid providing an answer, even though the advice content (brand identity, building relationships, staying positive) is present in the context.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-30_q029", "cell": "oracle-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 11020, "prompt_tokens": 550, "completion_tokens": 251, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model correctly identified both cities (Paris and Rome) that Jon visited according to the ground-truth context, with no additional incorrect claims.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model correctly identified both cities (Paris and Rome) that Jon visited according to the ground-truth context, with no additional incorrect claims.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}
{"instance_id": "locomo_conv-44_q066", "cell": "oracle-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 5882, "prompt_tokens": 512, "completion_tokens": 214, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer 'A smaller dog' exactly matches the ground-truth answer 'smaller dog' and is fully supported by the context where Andrew states that for someone living in an apartment, 'a smaller dog would be best.'\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer 'A smaller dog' exactly matches the ground-truth answer 'smaller dog' and is fully supported by the context where Andrew states that for someone living in an apartment, 'a smaller dog would be best.'", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}
{"instance_id": "locomo_conv-44_q002", "cell": "oracle-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 9991, "prompt_tokens": 739, "completion_tokens": 412, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F2\",\n \"rationale\": \"The model only mentions board games but omits three other activities (volunteering at pet shelter, wine tasting, and growing flowers) that Andrew pursued with his girlfriend according to the ground truth.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F2", "parsed_rationale": "The model only mentions board games but omits three other activities (volunteering at pet shelter, wine tasting, and growing flowers) that Andrew pursued with his girlfriend according to the ground truth.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-47_q046", "cell": "oracle-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 13063, "prompt_tokens": 448, "completion_tokens": 344, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer '27 August, 2022' is equivalent to the ground truth 'August 27, 2022' (same date, merely different formatting), and aligns with the context showing John said 'See you tomorrow at McGee's Pub' on August 26, 2022.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer '27 August, 2022' is equivalent to the ground truth 'August 27, 2022' (same date, merely different formatting), and aligns with the context showing John said 'See you tomorrow at McGee's Pub' on August 26, 2022.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}
{"instance_id": "locomo_conv-43_q076", "cell": "oracle-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 7570, "prompt_tokens": 497, "completion_tokens": 296, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer 'MinaLima' correctly identifies the creator of the picture Tim shared, which matches the ground truth that it was 'MinaLima's creation from the Harry Potter films'.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer 'MinaLima' correctly identifies the creator of the picture Tim shared, which matches the ground truth that it was 'MinaLima's creation from the Harry Potter films'.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-41_q065", "cell": "oracle-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 15698, "prompt_tokens": 441, "completion_tokens": 260, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model accurately identified both key topics (education and infrastructure) from the ground truth context, with only a minor phrasing difference (dropping 'improving') which is acceptable.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model accurately identified both key topics (education and infrastructure) from the ground truth context, with only a minor phrasing difference (dropping 'improving') which is acceptable.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}
{"instance_id": "locomo_conv-50_q086", "cell": "full-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 4905, "prompt_tokens": 502, "completion_tokens": 168, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model correctly identifies the sports activity (skiing) that Calvin plans to try after the tour with Frank Ocean, matching the ground truth.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model correctly identifies the sports activity (skiing) that Calvin plans to try after the tour with Frank Ocean, matching the ground truth.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}
{"instance_id": "locomo_conv-26_q059", "cell": "full-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 11874, "prompt_tokens": 586, "completion_tokens": 350, "raw_text": "{\"verdict\": \"incorrect\", \"failure_mode\": \"F1\", \"rationale\": \"The model explicitly stated 'unknown' rather than attempting to answer the question, which constitutes an abstention when the context provides sufficient information to determine that Caroline is somewhat but not extremely religious.\"}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F1", "parsed_rationale": "The model explicitly stated 'unknown' rather than attempting to answer the question, which constitutes an abstention when the context provides sufficient information to determine that Caroline is somewhat but not extremely religious.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-44_q000", "cell": "full-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 10437, "prompt_tokens": 470, "completion_tokens": 455, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer of 2020 matches the ground truth, which can be derived from the context stating Audrey had her three dogs for 3 years as of March 27, 2023, placing their adoption around 2020.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer of 2020 matches the ground truth, which can be derived from the context stating Audrey had her three dogs for 3 years as of March 27, 2023, placing their adoption around 2020.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}
{"instance_id": "locomo_conv-41_q080", "cell": "full-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 10963, "prompt_tokens": 517, "completion_tokens": 516, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F2\",\n \"rationale\": \"The model correctly identifies that Maria made 'a painting' but omits the essential detail that it was 'of a castle on a hill,' which is a required fact from the ground truth.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F2", "parsed_rationale": "The model correctly identifies that Maria made 'a painting' but omits the essential detail that it was 'of a castle on a hill,' which is a required fact from the ground truth.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-42_q001", "cell": "full-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 5690, "prompt_tokens": 764, "completion_tokens": 305, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F2\",\n \"rationale\": \"The model correctly identified watching movies as a shared interest but failed to include making desserts, which both Joanna and Nate discuss enjoying.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F2", "parsed_rationale": "The model correctly identified watching movies as a shared interest but failed to include making desserts, which both Joanna and Nate discuss enjoying.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-43_q155", "cell": "full-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 10228, "prompt_tokens": 480, "completion_tokens": 495, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer 'great' is a direct synonym from the context where John says 'It was great!' and is equivalent to the ground truth 'huge success' in describing John's emotional response to jogging without pain.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer 'great' is a direct synonym from the context where John says 'It was great!' and is equivalent to the ground truth 'huge success' in describing John's emotional response to jogging without pain.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-50_q015", "cell": "full-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 16273, "prompt_tokens": 571, "completion_tokens": 367, "raw_text": "```json\n{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F2\",\n \"rationale\": \"The model correctly identifies that Dave visits parks to relax, but omits the additional detail that it also calms him, making this a partial answer.\"\n}\n```", "parsed_verdict": "incorrect", "parsed_failure_mode": "F2", "parsed_rationale": "The model correctly identifies that Dave visits parks to relax, but omits the additional detail that it also calms him, making this a partial answer.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-48_q020", "cell": "full-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 7004, "prompt_tokens": 699, "completion_tokens": 294, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F2\",\n \"rationale\": \"The model correctly identified three games (Detroit, It Takes Two, Overcooked 2) but missed two games (Walking Dead, Battlefield 1) that appear in the ground truth.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F2", "parsed_rationale": "The model correctly identified three games (Detroit, It Takes Two, Overcooked 2) but missed two games (Walking Dead, Battlefield 1) that appear in the ground truth.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-48_q055", "cell": "full-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 22814, "prompt_tokens": 508, "completion_tokens": 345, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F1\",\n \"rationale\": \"The model explicitly states it does not know the answer, which is a refusal to provide the correct answer.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F1", "parsed_rationale": "The model explicitly states it does not know the answer, which is a refusal to provide the correct answer.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-26_q128", "cell": "full-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 7288, "prompt_tokens": 474, "completion_tokens": 196, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer 'rainbow sidewalk' matches the ground truth 'a rainbow sidewalk' exactly, representing the same object without the article.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer 'rainbow sidewalk' matches the ground truth 'a rainbow sidewalk' exactly, representing the same object without the article.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}
{"instance_id": "locomo_conv-50_q010", "cell": "full-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 14884, "prompt_tokens": 502, "completion_tokens": 452, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer 'last week' is equivalent to the ground truth 'a week before 16 May, 2023' as both convey the same temporal information that the flooding occurred during the week prior to May 16, 2023.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer 'last week' is equivalent to the ground truth 'a week before 16 May, 2023' as both convey the same temporal information that the flooding occurred during the week prior to May 16, 2023.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}
{"instance_id": "locomo_conv-50_q078", "cell": "full-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 3608, "prompt_tokens": 485, "completion_tokens": 201, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer matches the ground-truth answer exactly, capturing the intended reminder of why Calvin keeps hustling as a musician.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer matches the ground-truth answer exactly, capturing the intended reminder of why Calvin keeps hustling as a musician.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}
{"instance_id": "locomo_conv-47_q092", "cell": "full-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 37908, "prompt_tokens": 484, "completion_tokens": 600, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F2\",\n \"rationale\": \"The model correctly identifies that John created an application but omits the specific detail that it was on smartphones, which is part of the ground truth answer.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F2", "parsed_rationale": "The model correctly identifies that John created an application but omits the specific detail that it was on smartphones, which is part of the ground truth answer.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-30_q057", "cell": "full-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 19809, "prompt_tokens": 497, "completion_tokens": 519, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F1\",\n \"rationale\": \"The model explicitly stated 'unknown', indicating it does not know the answer, which constitutes an abstention from providing the required information.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F1", "parsed_rationale": "The model explicitly stated 'unknown', indicating it does not know the answer, which constitutes an abstention from providing the required information.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-30_q029", "cell": "full-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 4197, "prompt_tokens": 566, "completion_tokens": 135, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model correctly listed both cities (Paris and Rome) that Jon visited according to the ground-truth context.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model correctly listed both cities (Paris and Rome) that Jon visited according to the ground-truth context.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}
{"instance_id": "locomo_conv-44_q066", "cell": "full-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 7687, "prompt_tokens": 511, "completion_tokens": 239, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer 'smaller dog' exactly matches the ground-truth answer and is directly supported by the context which states that for Andrew, 'a person living in an apartment, a smaller dog would be best.'\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer 'smaller dog' exactly matches the ground-truth answer and is directly supported by the context which states that for Andrew, 'a person living in an apartment, a smaller dog would be best.'", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}
{"instance_id": "locomo_conv-44_q002", "cell": "full-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 12652, "prompt_tokens": 743, "completion_tokens": 634, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F2\",\n \"rationale\": \"The model correctly identified playing board games as one indoor activity but missed the other three activities (volunteering at pet shelter, wine tasting, and growing flowers) mentioned in the ground truth.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F2", "parsed_rationale": "The model correctly identified playing board games as one indoor activity but missed the other three activities (volunteering at pet shelter, wine tasting, and growing flowers) mentioned in the ground truth.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-47_q046", "cell": "full-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 17719, "prompt_tokens": 464, "completion_tokens": 703, "raw_text": "```json\n{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer 'tomorrow' is factually correct, as John said 'See you tomorrow at McGee's Pub' on August 26, 2022, making August 27, 2022 the correct meeting date, which is equivalent to 'tomorrow' in this context.\"\n}\n```", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer 'tomorrow' is factually correct, as John said 'See you tomorrow at McGee's Pub' on August 26, 2022, making August 27, 2022 the correct meeting date, which is equivalent to 'tomorrow' in this context.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-43_q076", "cell": "full-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 14900, "prompt_tokens": 497, "completion_tokens": 819, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer 'from MinaLima' correctly identifies the creator of the picture as MinaLima, which matches the ground truth, and the supporting context confirms this attribution.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer 'from MinaLima' correctly identifies the creator of the picture as MinaLima, which matches the ground truth, and the supporting context confirms this attribution.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-41_q065", "cell": "full-context", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 6871, "prompt_tokens": 443, "completion_tokens": 241, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer matches the ground truth exactly, identifying improving education and infrastructure as John's main focus in local politics.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer matches the ground truth exactly, identifying improving education and infrastructure as John's main focus in local politics.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}
{"instance_id": "locomo_conv-50_q086", "cell": "retrieval", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 7062, "prompt_tokens": 502, "completion_tokens": 449, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F3\",\n \"rationale\": \"The model answered 'Not mentioned' but the ground-truth context clearly indicates skiing is the activity Calvin plans to try after the tour, as evidenced by the snowy peak reference and the image of a person on skis.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F3", "parsed_rationale": "The model answered 'Not mentioned' but the ground-truth context clearly indicates skiing is the activity Calvin plans to try after the tour, as evidenced by the snowy peak reference and the image of a person on skis.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-26_q059", "cell": "retrieval", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 15512, "prompt_tokens": 569, "completion_tokens": 523, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F3\",\n \"rationale\": \"The model answered 'No' while the ground truth indicates Caroline is 'somewhat, but not extremely religious' based on her creating artwork for a church and participating in religious spaces.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F3", "parsed_rationale": "The model answered 'No' while the ground truth indicates Caroline is 'somewhat, but not extremely religious' based on her creating artwork for a church and participating in religious spaces.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-44_q000", "cell": "retrieval", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 23052, "prompt_tokens": 467, "completion_tokens": 805, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F2\",\n \"rationale\": \"The model failed to derive the year 2020 from the context (3 years before March 2023), instead stating 'Not mentioned' when the answer could be calculated from the given information.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F2", "parsed_rationale": "The model failed to derive the year 2020 from the context (3 years before March 2023), instead stating 'Not mentioned' when the answer could be calculated from the given information.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-41_q080", "cell": "retrieval", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 10364, "prompt_tokens": 500, "completion_tokens": 306, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F2\",\n \"rationale\": \"The model correctly states that Maria made a painting, but fails to include the specific detail that it was a painting of a castle on a hill, which is the key distinguishing fact in the ground truth.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F2", "parsed_rationale": "The model correctly states that Maria made a painting, but fails to include the specific detail that it was a painting of a castle on a hill, which is the key distinguishing fact in the ground truth.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-42_q001", "cell": "retrieval", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 18171, "prompt_tokens": 744, "completion_tokens": 516, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F3\",\n \"rationale\": \"The model correctly identified movies as a shared interest but incorrectly stated nature as shared (only Joanna enjoys nature, not Nate), and failed to mention the shared interest of making desserts.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F3", "parsed_rationale": "The model correctly identified movies as a shared interest but incorrectly stated nature as shared (only Joanna enjoys nature, not Nate), and failed to mention the shared interest of making desserts.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-43_q155", "cell": "retrieval", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 18019, "prompt_tokens": 484, "completion_tokens": 636, "raw_text": "```json\n{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F2\",\n \"rationale\": \"The model's answer 'Relieved' captures a plausible emotional response but misses the ground truth's explicit statement that jogging without pain was 'a huge success' and John said 'It was great!' — the model provides an alternative valid emotion without stating the specific required fact.\"\n}\n```", "parsed_verdict": "incorrect", "parsed_failure_mode": "F2", "parsed_rationale": "The model's answer 'Relieved' captures a plausible emotional response but misses the ground truth's explicit statement that jogging without pain was 'a huge success' and John said 'It was great!' — the model provides an alternative valid emotion without stating the specific required fact.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-50_q015", "cell": "retrieval", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 30829, "prompt_tokens": 582, "completion_tokens": 1060, "raw_text": "```json\n{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F4\",\n \"rationale\": \"The model adds 'hang out with friends' which does not appear in the ground-truth context where Dave visits parks alone to relax in nature.\"\n}\n```", "parsed_verdict": "incorrect", "parsed_failure_mode": "F4", "parsed_rationale": "The model adds 'hang out with friends' which does not appear in the ground-truth context where Dave visits parks alone to relax in nature.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-48_q020", "cell": "retrieval", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 13576, "prompt_tokens": 716, "completion_tokens": 393, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F2\",\n \"rationale\": \"The model identified three of the five games (Detroit, Overcooked 2, It Takes Two) but omitted Walking Dead and Battlefield 1 from the ground-truth answer.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F2", "parsed_rationale": "The model identified three of the five games (Detroit, Overcooked 2, It Takes Two) but omitted Walking Dead and Battlefield 1 from the ground-truth answer.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-48_q055", "cell": "retrieval", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 8026, "prompt_tokens": 513, "completion_tokens": 328, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer 'Seraphim' matches the ground-truth answer exactly, indicating the model correctly identified which pet Jolene adopted more recently.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer 'Seraphim' matches the ground-truth answer exactly, indicating the model correctly identified which pet Jolene adopted more recently.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}
{"instance_id": "locomo_conv-26_q128", "cell": "retrieval", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 3990, "prompt_tokens": 494, "completion_tokens": 147, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer 'A rainbow sidewalk' exactly matches the ground truth answer, identifying what Caroline found during her walk.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer 'A rainbow sidewalk' exactly matches the ground truth answer, identifying what Caroline found during her walk.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}
{"instance_id": "locomo_conv-50_q010", "cell": "retrieval", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 12906, "prompt_tokens": 502, "completion_tokens": 509, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer 'Last week' correctly captures the temporal information from the ground truth, as the context confirms Calvin's place was flooded during the week before 16 May 2023.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer 'Last week' correctly captures the temporal information from the ground truth, as the context confirms Calvin's place was flooded during the week before 16 May 2023.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}
{"instance_id": "locomo_conv-50_q078", "cell": "retrieval", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 5835, "prompt_tokens": 482, "completion_tokens": 140, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer matches the ground‑truth answer exactly.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer matches the ground‑truth answer exactly.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}
{"instance_id": "locomo_conv-47_q092", "cell": "retrieval", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 18160, "prompt_tokens": 485, "completion_tokens": 678, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F2\",\n \"rationale\": \"The model's answer 'A software tool' is missing the specific detail that the application was on smartphones, which is a required fact from the ground truth answer.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F2", "parsed_rationale": "The model's answer 'A software tool' is missing the specific detail that the application was on smartphones, which is a required fact from the ground truth answer.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-30_q057", "cell": "retrieval", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 21614, "prompt_tokens": 499, "completion_tokens": 665, "raw_text": "{\"verdict\":\"incorrect\",\"failure_mode\":\"F2\",\"rationale\":\"The model's answer contains no overlap with the required facts from the ground truth—it mentions passion, focus, and resilience instead of the three specific advice points (build relationships with customers, create a strong brand image, stay positive) that appeared in the context.\"}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F2", "parsed_rationale": "The model's answer contains no overlap with the required facts from the ground truth—it mentions passion, focus, and resilience instead of the three specific advice points (build relationships with customers, create a strong brand image, stay positive) that appeared in the context.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-30_q029", "cell": "retrieval", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 8084, "prompt_tokens": 568, "completion_tokens": 266, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F2\",\n \"rationale\": \"The model correctly identified Paris but omitted Rome, providing only a partial answer to the question.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F2", "parsed_rationale": "The model correctly identified Paris but omitted Rome, providing only a partial answer to the question.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-44_q066", "cell": "retrieval", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 4891, "prompt_tokens": 512, "completion_tokens": 264, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer 'A smaller dog' matches the ground truth 'smaller dog' exactly, correctly identifying that Andrew was looking for a smaller dog based on his apartment living space.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer 'A smaller dog' matches the ground truth 'smaller dog' exactly, correctly identifying that Andrew was looking for a smaller dog based on his apartment living space.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}
{"instance_id": "locomo_conv-44_q002", "cell": "retrieval", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 13170, "prompt_tokens": 739, "completion_tokens": 450, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F2\",\n \"rationale\": \"The model only mentions wine tasting but misses three other activities (boardgames, volunteering at pet shelter, and growing flowers) that Andrew pursued with his girlfriend.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F2", "parsed_rationale": "The model only mentions wine tasting but misses three other activities (boardgames, volunteering at pet shelter, and growing flowers) that Andrew pursued with his girlfriend.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-47_q046", "cell": "retrieval", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 15948, "prompt_tokens": 460, "completion_tokens": 643, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer 'Tomorrow' is equivalent to the ground truth 'August 27, 2022' because the context establishes that on August 26 John said 'See you tomorrow at McGee's Pub,' making 'tomorrow' the correct relative reference to August 27, 2022.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer 'Tomorrow' is equivalent to the ground truth 'August 27, 2022' because the context establishes that on August 26 John said 'See you tomorrow at McGee's Pub,' making 'tomorrow' the correct relative reference to August 27, 2022.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-43_q076", "cell": "retrieval", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 22719, "prompt_tokens": 495, "completion_tokens": 421, "raw_text": "```json\n{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer 'MinaLima props' correctly identifies the source (MinaLima) and implies their work on Harry Potter film props, which aligns with the ground truth that it is 'MinaLima's creation from the Harry Potter films' without adding any incorrect claims.\"\n}\n```", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer 'MinaLima props' correctly identifies the source (MinaLima) and implies their work on Harry Potter film props, which aligns with the ground truth that it is 'MinaLima's creation from the Harry Potter films' without adding any incorrect claims.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}
{"instance_id": "locomo_conv-41_q065", "cell": "retrieval", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 6626, "prompt_tokens": 461, "completion_tokens": 253, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model correctly identifies education and infrastructure as John's main focuses in local politics, matching the ground truth without any incorrect additions.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model correctly identifies education and infrastructure as John's main focuses in local politics, matching the ground truth without any incorrect additions.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}
{"instance_id": "locomo_conv-50_q086", "cell": "agentic", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 39796, "prompt_tokens": 515, "completion_tokens": 2489, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F3\",\n \"rationale\": \"The model provided a system message about tool usage limits instead of stating the correct answer (skiing), which constitutes an incorrect response not covered by the other failure modes.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F3", "parsed_rationale": "The model provided a system message about tool usage limits instead of stating the correct answer (skiing), which constitutes an incorrect response not covered by the other failure modes.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-26_q059", "cell": "agentic", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 15569, "prompt_tokens": 619, "completion_tokens": 629, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F4\",\n \"rationale\": \"The model fabricates a detail about a necklace from Sweden representing 'love, faith and strength' that does not appear in the ground-truth context, while the church painting connection is correctly derived from the context.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F4", "parsed_rationale": "The model fabricates a detail about a necklace from Sweden representing 'love, faith and strength' that does not appear in the ground-truth context, while the church painting connection is correctly derived from the context.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-44_q000", "cell": "agentic", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 22383, "prompt_tokens": 477, "completion_tokens": 638, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F3\",\n \"rationale\": \"The model failed to provide an answer to the question, instead outputting a system message indicating it reached its maximum tool turns without generating a response.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F3", "parsed_rationale": "The model failed to provide an answer to the question, instead outputting a system message indicating it reached its maximum tool turns without generating a response.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-41_q080", "cell": "agentic", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 21678, "prompt_tokens": 500, "completion_tokens": 519, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F2\",\n \"rationale\": \"The model correctly identifies that Maria made a painting but omits the key detail that it was specifically a painting of a castle on a hill, which is required by the ground truth answer.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F2", "parsed_rationale": "The model correctly identifies that Maria made a painting but omits the key detail that it was specifically a painting of a castle on a hill, which is required by the ground truth answer.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-42_q001", "cell": "agentic", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 9621, "prompt_tokens": 762, "completion_tokens": 364, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F2\",\n \"rationale\": \"The model correctly identifies watching movies as a shared interest but fails to include making desserts, which is also a shared interest according to the ground-truth context.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F2", "parsed_rationale": "The model correctly identifies watching movies as a shared interest but fails to include making desserts, which is also a shared interest according to the ground-truth context.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-43_q155", "cell": "agentic", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 9115, "prompt_tokens": 483, "completion_tokens": 389, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer 'great' is a synonym that captures the same positive sentiment as 'huge success' in the ground truth.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer 'great' is a synonym that captures the same positive sentiment as 'huge success' in the ground truth.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-50_q015", "cell": "agentic", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 39909, "prompt_tokens": 573, "completion_tokens": 484, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer 'to relax and recharge' captures the core meaning of the ground truth 'relaxes and calms him' - 'relax' directly matches 'relaxes', and 'recharge' is an acceptable synonym for the calming/restorative effect described in the context.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer 'to relax and recharge' captures the core meaning of the ground truth 'relaxes and calms him' - 'relax' directly matches 'relaxes', and 'recharge' is an acceptable synonym for the calming/restorative effect described in the context.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-48_q020", "cell": "agentic", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 9349, "prompt_tokens": 719, "completion_tokens": 393, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F2\",\n \"rationale\": \"The model correctly identified Detroit, Overcooked 2, and It Takes Two, but missed Walking Dead and Battlefield 1 which are also in the ground truth.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F2", "parsed_rationale": "The model correctly identified Detroit, Overcooked 2, and It Takes Two, but missed Walking Dead and Battlefield 1 which are also in the ground truth.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-48_q055", "cell": "agentic", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 20702, "prompt_tokens": 512, "completion_tokens": 666, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F4\",\n \"rationale\": \"The model answered 'Susie' but neither 'Susie' nor 'Seraphim' appear in the ground-truth context, indicating the model hallucinated the pet name.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F4", "parsed_rationale": "The model answered 'Susie' but neither 'Susie' nor 'Seraphim' appear in the ground-truth context, indicating the model hallucinated the pet name.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-26_q128", "cell": "agentic", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 4544, "prompt_tokens": 494, "completion_tokens": 185, "raw_text": "```json\n{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer 'a rainbow sidewalk' exactly matches the ground-truth answer, both correctly identifying what Caroline found during her walk.\"\n}\n```", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer 'a rainbow sidewalk' exactly matches the ground-truth answer, both correctly identifying what Caroline found during her walk.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}
{"instance_id": "locomo_conv-50_q010", "cell": "agentic", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 28878, "prompt_tokens": 502, "completion_tokens": 501, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer 'last week' is factually correct and equivalent to the ground truth 'a week before 16 May, 2023', as Calvin stated his place got flooded 'last week' during the session on 16 May, 2023.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer 'last week' is factually correct and equivalent to the ground truth 'a week before 16 May, 2023', as Calvin stated his place got flooded 'last week' during the session on 16 May, 2023.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}
{"instance_id": "locomo_conv-50_q078", "cell": "agentic", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 3384, "prompt_tokens": 485, "completion_tokens": 112, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model’s answer matches the ground‑truth answer exactly, stating the necklace was meant to remind Calvin of why he keeps hustling as a musician.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model’s answer matches the ground‑truth answer exactly, stating the necklace was meant to remind Calvin of why he keeps hustling as a musician.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}
{"instance_id": "locomo_conv-47_q092", "cell": "agentic", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 11980, "prompt_tokens": 488, "completion_tokens": 539, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F2\",\n \"rationale\": \"The model correctly identifies that John created a tool/application, but it misses the specific required detail that the application was on smartphones.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F2", "parsed_rationale": "The model correctly identifies that John created a tool/application, but it misses the specific required detail that the application was on smartphones.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-30_q057", "cell": "agentic", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 19907, "prompt_tokens": 520, "completion_tokens": 549, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F5\",\n \"rationale\": \"The model's answer provides motivational self-help advice about faith in oneself and support systems, which is completely different from the ground truth's advice about building customer relationships, creating brand image, and staying positive.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F5", "parsed_rationale": "The model's answer provides motivational self-help advice about faith in oneself and support systems, which is completely different from the ground truth's advice about building customer relationships, creating brand image, and staying positive.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-30_q029", "cell": "agentic", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 13857, "prompt_tokens": 565, "completion_tokens": 267, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F1\",\n \"rationale\": \"The model explicitly stated 'unknown' when the cities (Paris and Rome) could have been extracted from the provided supporting context.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F1", "parsed_rationale": "The model explicitly stated 'unknown' when the cities (Paris and Rome) could have been extracted from the provided supporting context.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-44_q066", "cell": "agentic", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 5477, "prompt_tokens": 512, "completion_tokens": 215, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer 'a smaller dog' exactly matches the ground truth, correctly identifying that Andrew was looking for a smaller dog based on his apartment living space.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer 'a smaller dog' exactly matches the ground truth, correctly identifying that Andrew was looking for a smaller dog based on his apartment living space.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}
{"instance_id": "locomo_conv-44_q002", "cell": "agentic", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 15222, "prompt_tokens": 742, "completion_tokens": 560, "raw_text": "{\n \"verdict\": \"incorrect\",\n \"failure_mode\": \"F2\",\n \"rationale\": \"The model correctly identified board games as an indoor activity Andrew pursued with his girlfriend but missed the other three activities (volunteering at pet shelter, wine tasting, and growing flowers) that appear in the ground truth, without stating any incorrect information.\"\n}", "parsed_verdict": "incorrect", "parsed_failure_mode": "F2", "parsed_rationale": "The model correctly identified board games as an indoor activity Andrew pursued with his girlfriend but missed the other three activities (volunteering at pet shelter, wine tasting, and growing flowers) that appear in the ground truth, without stating any incorrect information.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-47_q046", "cell": "agentic", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 9876, "prompt_tokens": 463, "completion_tokens": 599, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model correctly identifies the timing as 'tomorrow', which aligns with the ground truth of August 27, 2022, since John said 'See you tomorrow' on August 26, 2022, making tomorrow August 27, 2022.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model correctly identifies the timing as 'tomorrow', which aligns with the ground truth of August 27, 2022, since John said 'See you tomorrow' on August 26, 2022, making tomorrow August 27, 2022.", "opus_verdict_ref": "incorrect", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-43_q076", "cell": "agentic", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 26616, "prompt_tokens": 496, "completion_tokens": 520, "raw_text": "```json\n{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer 'A picture from MinaLima' correctly identifies the source of the picture, which matches the ground truth that it is MinaLima's creation, and minor phrasing differences are acceptable.\"\n}\n```", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer 'A picture from MinaLima' correctly identifies the source of the picture, which matches the ground truth that it is MinaLima's creation, and minor phrasing differences are acceptable.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}
{"instance_id": "locomo_conv-41_q065", "cell": "agentic", "provider": "minimax", "model_id": "minimax/minimax-m2.7", "routing": "openrouter_direct_http", "litellm_alias_registered": "minimax-m27-via-openrouter", "http_status": 200, "error": null, "retries": 0, "latency_ms": 10691, "prompt_tokens": 461, "completion_tokens": 330, "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model correctly identified education and infrastructure as John's main focuses, matching the ground truth without any incorrect additions.\"\n}", "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model correctly identified education and infrastructure as John's main focuses, matching the ground truth without any incorrect additions.", "opus_verdict_ref": "correct", "gpt_verdict_ref": "correct"}

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{"instance_id": "locomo_conv-43_q155", "cell": "agentic", "provider": "minimax", "alias": "minimax-m27-via-openrouter", "routing": "openrouter_direct_http", "http_status": 200, "error": null, "latency_ms": 28396, "prompt_tokens": 480, "completion_tokens": 635, "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer 'great' is a direct synonym for John's stated feeling ('It was great!') and captures the same positive sentiment as 'huge success' from the ground truth, making it an acceptable equivalent formulation.", "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer 'great' is a direct synonym for John's stated feeling ('It was great!') and captures the same positive sentiment as 'huge success' from the ground truth, making it an acceptable equivalent formulation.\"\n}", "opus_verdict_ref": "correct", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-43_q155", "cell": "agentic", "provider": "kimi", "alias": "kimi-k26-direct", "routing": "moonshot_direct_http", "http_status": 0, "error": "TimeoutError: The read operation timed out", "latency_ms": 60112, "prompt_tokens": null, "completion_tokens": null, "parsed_verdict": null, "parsed_failure_mode": null, "parsed_rationale": null, "raw_text": "", "opus_verdict_ref": "correct", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-50_q015", "cell": "agentic", "provider": "minimax", "alias": "minimax-m27-via-openrouter", "routing": "openrouter_direct_http", "http_status": 200, "error": null, "latency_ms": 17311, "prompt_tokens": 573, "completion_tokens": 558, "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer captures the primary reason (relax) and adds a conceptually aligned detail (recharge), which is acceptable as minor elaboration that is not contradictory to the ground truth of relaxing and calming.", "raw_text": "{\"verdict\":\"correct\",\"failure_mode\":null,\"rationale\":\"The model's answer captures the primary reason (relax) and adds a conceptually aligned detail (recharge), which is acceptable as minor elaboration that is not contradictory to the ground truth of relaxing and calming.\"}", "opus_verdict_ref": "correct", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-50_q015", "cell": "agentic", "provider": "kimi", "alias": "kimi-k26-direct", "routing": "moonshot_direct_http", "http_status": 200, "error": null, "latency_ms": 15158, "prompt_tokens": 550, "completion_tokens": 351, "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer captures the ground truth that Dave visits parks to relax, and 'recharge' is an acceptable synonymous formulation of the calming, restorative benefit described in the context without introducing any incorrect claims.", "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer captures the ground truth that Dave visits parks to relax, and 'recharge' is an acceptable synonymous formulation of the calming, restorative benefit described in the context without introducing any incorrect claims.\"\n}", "opus_verdict_ref": "correct", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-43_q155", "cell": "full-context", "provider": "minimax", "alias": "minimax-m27-via-openrouter", "routing": "openrouter_direct_http", "http_status": 200, "error": null, "latency_ms": 25481, "prompt_tokens": 480, "completion_tokens": 518, "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer 'great' is a direct synonym for 'a huge success' from the ground truth, both expressing John's positive feeling about jogging without pain, and contains no incorrect claims.", "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer 'great' is a direct synonym for 'a huge success' from the ground truth, both expressing John's positive feeling about jogging without pain, and contains no incorrect claims.\"\n}", "opus_verdict_ref": "correct", "gpt_verdict_ref": "incorrect"}
{"instance_id": "locomo_conv-43_q155", "cell": "full-context", "provider": "kimi", "alias": "kimi-k26-direct", "routing": "moonshot_direct_http", "http_status": 200, "error": null, "latency_ms": 47213, "prompt_tokens": 456, "completion_tokens": 1617, "parsed_verdict": "correct", "parsed_failure_mode": null, "parsed_rationale": "The model's answer 'great' is explicitly stated in the ground-truth context as John's direct feeling about jogging without pain, making it factually correct and an acceptable equivalent formulation.", "raw_text": "{\n \"verdict\": \"correct\",\n \"failure_mode\": null,\n \"rationale\": \"The model's answer 'great' is explicitly stated in the ground-truth context as John's direct feeling about jogging without pain, making it factually correct and an acceptable equivalent formulation.\"\n}", "opus_verdict_ref": "correct", "gpt_verdict_ref": "incorrect"}

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# Manifest v6 Phase 1 κ Re-Calibration — Exit Memo
**Date:** 2026-04-24 **Target:** PM-RATIFY-V6-KAPPA **v6 anchor:** `60d061e`
## Verdict: **PASS** (κ_conservative_trio = 0.7878 ≥ 0.70)
## Three pairwise Cohen's κ (n=100)
| Pair | Agree | κ |
|------|-------|-----|
| Opus vs GPT | 93/100 | **0.8480** |
| Opus vs MiniMax | 93/100 | **0.8549** |
| GPT vs MiniMax | 90/100 | **0.7878** (min) |
**Notable:** MiniMax agrees with Opus *more* than GPT does (0.8549 > 0.8480). Swap validated empirically. v5 historical baseline (Fleiss κ=0.7458 three-way) is consistent with v6's pairwise Opus-GPT of 0.8480 — sanity check PASSES.
## MiniMax operational metrics
| Metric | Target | Actual | Status |
|--------|--------|--------|--------|
| Parse rate | ≥95/100 | **100/100** | MET |
| Latency p50 | ≤25 s | **11.9 s** | MET |
| Latency p95 | — | 31.4 s | — |
| OR routing errors | <5% | **0/100** | MET |
| Retries | — | 0 | clean |
## Per-cell κ_trio (lowest of three pairwise per cell)
| Cell | κ_trio | Notes |
|------|--------|-------|
| no-context | 1.0000 | perfect unanimity |
| retrieval | 0.8936 | strong |
| full-context | 0.7000 | acceptable |
| oracle-context | 0.7059 | acceptable |
| **agentic** | **0.6875** | **BORDERLINE at cell-level** (GPT-MiniMax pair) |
Agentic dips into borderline band at cell level — flag for PM but does not block PASS verdict since aggregate trio meets bar.
## Cost / wall-clock
- 100 calls, 0 retries, 0 failures
- Tokens: 53,855 prompt + 48,920 completion
- **Cost actual: ~$0.075** (cap $30 Phase 1)
- **Wall-clock: ~24.2 min** (14:09-14:34 UTC) (cap 90 min)
## PM next step
Phase 1 complete. Awaiting `PM-RATIFY-V6-KAPPA` for Phase 2 (N=400) authorization. `cc1_state: HALTED`.