# Conversion audit — rubric for annotators **This is the audit the paper reports.** Three annotators, 248 items, independent, 2-of-3 majority, Fleiss' κ reported. It measures the error rate of the conversion filter, which is the instrument the whole open-ended corpus rests on. There are **two passes**, and the order matters. 1. `annotate_.json` — 248 items, the original question only. Do this first. 2. `annotate2_.json` — 152 items, with the rewrite shown. **Do not open this until pass one is completely finished**, because it reveals which items the filter kept, and pass one depends on you not knowing that. The `annotate*` files are **read-only reading packages** — they are gitignored, so anything typed into them can be lost. Type your answers into `verdicts_.json` (pass one) and `verdicts2_.json` (pass two) instead: they list the same items, by blind `id`, in your reading order, and they are tracked in git. Commit them as you go. **Do not open `KEY.json`, and do not discuss items with the other two until both verdicts files are done.** Disagreement is the measurement; agreeing in advance destroys it. Your rows are in a different order from the other annotators' — that is deliberate, so that tiredness late in the file doesn't hit the same items for all three of us. Items are identified by `id`, never by position. --- ## Pass one — does the item convert? You are shown the **original** MMLU-Pro question, its options, and which answer is correct — the same view for every item. You are *not* told what the filter decided, whether a rewrite exists, or what the other annotators thought. Every item looks identical, deliberately. ### 1. `converts` — would this question survive losing its options? Imagine the options deleted and the question reworded to stand alone. **Would a knowledgeable person give the reference answer, rather than a different, equally correct one?** - `yes` — the reference is the single correct answer. - `no` — stripped of options it admits many correct answers, or stops meaning anything. - `borderline` — you genuinely cannot decide. Use this sparingly. Two kinds fail whatever else is true of them: - **It excludes rather than identifies** — "which is NOT", "EXCEPT", "is false", "least likely". Everything in the world outside the answer set answers it correctly. - **The answer only means something beside the others** — "all of the above", "both A and C". Exception: if the stem itself sets out the alternatives ("i) … ii) … iii) …"), an answer like "i and iii" names real things and is fine. Common failures: asking for one member of a large category ("an example of X", "a true statement about X"); ranking the options ("best", "closest", "greatest"); an answer true among these ten choices but false as a claim about the world; leaning on a unit or convention only the options supplied. A superlative is not automatically a ranking — ask what it compares. "Which is the most persuasive argument", with ten arguments supplied, ranks the list and fails. "Which best approximates the ratio of nonterminal to total nodes in a complete K-ary tree", answer "1/K", does not: the ratio has one value and "best approximates" hedges the rounding. If the stem itself fixes the quantity, the superlative has nothing left to rank. **Not failures:** asking for several things at once ("calculate the efficiency and the reheat factor") — judge whether the answer is *unique*, not whether it is simple. Working the answer out from figures the stem supplies. Clumsy phrasing, which a rewrite fixes. And the reference answer's *wording* does not matter here — a later stage accepts any phrasing of the same fact. ### 2. `answer_stands_alone` — does the reference work as a grading target? **Judge this independently of question 1.** An item can have a perfect question and an unusable answer; that combination is the reason this field exists. A grader will see the question, this reference answer, and a model's response, and must decide whether the response is correct. - `yes` — the reference is a usable target. - `no` — it is not, for one of these reasons: - **units or magnitude stripped** — `1.12` where the question asks for a speed, and the real answer is 1.12 × 10⁴ m/s. Fine as one of ten numeric options; meaningless alone. - **a fragment** — `greater and grander`, which only completes the stem it came from. - **it does not answer the question asked** — the question says "describe the differences" and the reference is a single word like `Alcoholism`. - **it names option labels** — "I and II only", "b and c are Hermitian". - `borderline` — as above, use sparingly. MMLU-Pro option texts were written to be told apart from nine alternatives, not to stand alone. That property does not survive conversion, and nothing in the pipeline checks it — which is why we are asking you. ### 3. `why` — one short clause What decided it. Half a line is enough: *"many true statements about X"*, *"units stripped, answer is 1.12e4 m/s"*, *"unique: only one canonical answer"*. These are read when the three of us disagree, so write the reason you would give to the other two. ### Worked examples | question | reference | `converts` | `answer_stands_alone` | |---|---|---|---| | "Which of the following is NOT a phase of matter?" | `plasma` | `no` — excludes | `yes` | | "Calculate the minimum muzzle speed for a shell to escape Earth…" | `1.12` | `yes` — determinate | **`no`** — units stripped | | "Which of the following statements about photosynthesis is true?" | (a true statement) | `no` — large category | `yes` | | "The boiling point of water at sea level is" | `100 degrees Celsius` | `yes` | `yes` | | "According to Paley, what is the key difference…" | `greater and grander` | `yes` | **`no`** — fragment | | "Which of these are noble gases? i) helium ii) nitrogen iii) argon" | `i and iii` | `yes` — stem lists them | `yes` | --- ## Pass two — is the rewrite faithful? Only after pass one is finished. You now see the original question, its options, the reference answer, **and the rewritten open-ended question the filter produced**. Pass one asked whether the item *could* convert. This asks whether it actually *did*. ### 1. `same_question` — does the rewrite ask what the original asked? - `yes` — a reader answering the rewrite would give the same answer they'd have given the original. - `no` — it drifted. Two ways this happens and both matter: - **it was written from the answer** — the rewrite names a topic, property or scenario the stem never mentioned, narrowing a vague question until the reference is the obvious answer. "Which of the following is true?" becoming "Which statement about compact and complete spaces is true?" is the type case. - **it makes the question easier or harder** than the original. - `borderline`. ### 2. `self_contained` — can it be answered with no options in view? - `yes` — everything needed is present. - `no` — it still points at a list that is gone ("which of the following", "the statements above"), or **context was dropped**: a passage, table, formula or case description the original supplied and the rewrite left out. Watch for items that began "This question refers to the following information" — if the passage is missing, the question is unanswerable however well it reads. - `borderline`. ### 3. `why` — one short clause, as before. --- ## Why the sample looks the way it does 248 items drawn from five strata — kept by the judge, kept at re-score, dropped at re-score, dropped at rewrite, and a **borderline** stratum of items whose re-score landed in bands 4–7. The strata differ by orders of magnitude in size, and the small ones are over-drawn on purpose, so **the raw agreement rate over these 248 is not the filter's error rate**; each stratum is reweighted by its share of the corpus afterwards. The borderline stratum exists for a specific reason. The filter readmits a re-scored item at 5 or above, a threshold inherited from the method we adapted. Reading the run's own stated reasons, items scored 5 and 6 concede that the answer is not unique about as often as items scored 4 — which are *rejected* — while items scored 8 and above almost never do. That suggests the cut is in the wrong place, but it was measured by pattern-matching the model's prose, which is not evidence anyone should act on. **Your verdicts on these 50 items decide where the threshold goes.** They deliberately include items the filter both kept and dropped, so please don't try to infer which is which. The sample is not a picture of the corpus and you should not expect your answers to look like one. Do not track your own yes/no ratio: judge each item on its own and let the total land wherever it lands.