OpenCompass Chinese-prompt Natural Questions wrap: zero-shot short-answer generation scored by exact match on local jsonl files.
unassessed
| Category | knowledge |
|---|---|
| Subcategory | Chinese-prompt closed-book short-answer question answering in the Natural Questions style |
| Page status | unknown |
| Metric | exact match after OpenCompass post-processing (NQEvaluatorCN score, 0-100) |
| Direction | higher_is_better |
| Unit | % |
| Publisher | OpenCompass (open-compass/opencompass) |
This id is OpenCompass dataset abbr nq_cn, not English OpenCompass nq, not lm-eval nq_open, and not HELM natural_qa. The model sees a Chinese prompt of the form "问题: {question}?\n答案是:" and must emit a short answer string. The loader NaturalQuestionDatasetCN reads local ./data/nq_cn/dev.jsonl and test.jsonl. Whether those questions are translations of English Natural Questions or a new Chinese set is not stated in the config or loader. The reader evaluates the test split (train_split is set to test).
Zero-shot generation. ZeroRetriever, GenInferencer. Chinese instruction wrapper around a {question} field. pred_role BOT.
No model card in ModelSpec reports this benchmark yet.