A large annotated corpus for learning natural language inference
Bowman et al., 2015, A large annotated corpus for learning natural language inference (Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing (EMNLP))
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1 cards in “3.1 Excitement Open Platform models” · whole deck
3.1 Excitement Open Platform models
- How did existing RTE systems (Excitement Open Platform) fare on SNLI?On 2-class entailment (majority baseline 66% on SNLI): an edit-distance system 71.9%, a classifier 72.2%, and the classifier with WordNet, VerbOcean and tree features 75.0%, showing the task is hard for standard systems.
- Bowman et al., 2015, A large annotated corpus for learning natural language inference (Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing (EMNLP)), §3.1, pp. 636–637
Source
- Samuel R. Bowman, Gabor Angeli, Christopher Potts and Christopher D. Manning. 2015. A large annotated corpus for learning natural language inference. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 632–642. doi:10.18653/v1/D15-1075 https://aclanthology.org/D15-1075/