CLUE's translated NLI task, built from machine-translated MultiNLI and XNLI merged into one set; formally replaced by OCNLI on CLUE's own leaderboard.
unassessed
| Category | composite |
|---|---|
| Subcategory | natural language inference (Chinese, machine-translated) |
| Page status | active |
| Metric | accuracy |
| Direction | higher_is_better |
| Unit | % |
| Dataset size | 417904 |
| Publisher | CLUE benchmark team; assembled by machine-translating and merging MultiNLI (Williams et al., New York University) and XNLI (Conneau et al., Facebook AI Research and NYU) |
CMNLI asks whether a Chinese premise sentence entails, contradicts, or is neutral toward a second Chinese sentence -- three-way natural language inference. It is a translated, adopted task rather than one collected in Chinese: the CLUE team built it by machine-translating two English NLI corpora, MultiNLI and XNLI, then merging them (MultiNLI's training data becomes CMNLI's training set; XNLI's dev plus MultiNLI's matched dev, shuffled, becomes CMNLI's dev; XNLI's test plus MultiNLI's mismatched test, shuffled, becomes CMNLI's test). No paper, including CLUE's own, documents CMNLI directly; it appears only in the CLUE GitHub README.
Three-way classification (entailment / neutral / contradiction) over a Chinese sentence pair, scored by accuracy.
No model card in ModelSpec reports this benchmark yet.