CLUE's multiple-choice reading task, adopted from the separately published C3 dataset spanning Chinese dialogue and mixed-genre text, 2-4 options per question.
unassessed
| Category | composite |
|---|---|
| Subcategory | free-form multiple-choice reading comprehension (Chinese) |
| Page status | active |
| Metric | accuracy |
| Direction | higher_is_better |
| Unit | % |
| Dataset size | 19577 |
| Dataset licence | "C3 dataset is intended for non-commercial research purpose only" (license.txt in the original nlpdata/c3 repository); not separately re-stated by CLUE for its own bundled copy. |
| Publisher | C3 dataset authors (TACL 2020); specific institutional affiliations were not independently confirmed from the sources read for this page |
C3 gives a model a Chinese document -- either a two-person dialogue transcript or a more formally written mixed-genre passage -- plus a question and two to four labelled answer options, and asks it to pick the correct one. It was the first free-form multiple-choice Chinese reading-comprehension dataset at publication. CLUE adopted it wholesale from a dataset separately published by Kai Sun, Dian Yu, Dong Yu and Claire Cardie (TACL 2020); Sun and Yu also co-authored the CLUE paper, so, as with CMRC2018, the adoption carried the original authors' direct involvement rather than being a cold reuse.
Multiple-choice question answering (2-4 labelled options, varying per question) over a Chinese document, scored by accuracy.
No model card in ModelSpec reports this benchmark yet.