CLUE's simplified-Chinese span-extraction reading task, adopted wholesale from HFL's separately published CMRC 2018 shared-task dataset.
unassessed
| Category | composite |
|---|---|
| Subcategory | span-extraction reading comprehension (Simplified Chinese) |
| Page status | active |
| Metric | exact match (EM) |
| Direction | higher_is_better |
| Unit | % |
| Dataset size | 16363 |
| Dataset licence | CC-BY-SA-4.0, per the original ymcui/cmrc2018 GitHub repository; not separately re-stated by CLUE for its own bundled copy |
| Publisher | Harbin Institute of Technology - iFLYTEK Joint Laboratory (HFL); shared task organised by the Chinese Information Processing Society's Computational Linguistics Committee (CIPS-CL), sponsored by iFLYTEK |
CMRC2018 gives a model a Chinese Wikipedia paragraph and a question, and the model must extract the exact answer span from the passage -- SQuAD-style extractive reading comprehension, over roughly 19,071 human-annotated questions. CLUE did not build this task: it adopted CMRC2018 wholesale from a dataset separately published by Yiming Cui and colleagues at the Harbin Institute of Technology-iFLYTEK Joint Laboratory (HFL), whose original shared task keeps its own test answers hidden. Cui also co-authored the CLUE paper, so the adoption carried the original team's direct involvement rather than being a cold reuse.
Extractive question answering: given a passage and a question, output the answer text span; scored by exact match (and F1, though CLUE's own leaderboard reports EM as the final figure).
No model card in ModelSpec reports this benchmark yet.