Severing the Edge Between Before and After: Neural Architectures for Temporal Ordering of Events (2020.emnlp-main)
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Miguel Ballesteros, Rishita Anubhai, Shuai Wang, Nima Pourdamghani, Yogarshi Vyas, Jie Ma, Parminder Bhatia, Kathleen McKeown, Yaser Al-Onaizan
| Challenge: | Existing models for temporal ordering of events rely on pretrained representations, transfer and multitask learning, and self-training techniques. |
| Approach: | They propose a neural architecture and a set of training methods for ordering events by predicting temporal relations by pre-training models. |
| Outcome: | The proposed models can predict temporal relations between two pairs of events within a span of text and identify temporal relationships between them. |
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