Improving Temporal Relation Extraction with Training Instance Augmentation ; Anthology ID: W16-2914 ; Volume: Proceedings of the 15th Workshop on Biomedical ...

This method notably improves clinical temporal relation extraction, works beyond featurizing or duplicating the same information, can generalize ...

Dive into the research topics of 'Improving temporal relation extraction with training instance augmentation'. Together they form a unique fingerprint. Temporal ...

We describe a method for increasing the number of high-quality training instances available to a temporal relation extraction task, with an adaptation to ...

Improving Temporal Relation Extraction with Training Instance Augmentation. Lin, C., Miller, T., Dligach, D., Bethard, S., & Savova, G. In Proceedings of ...

Improving Temporal Relation Extraction with Training Instance Augmentation. Author. Lin, Chen and Miller, Timothy and Dligach, Dmitriy and Bethard, Steven and ...

In this paper, we propose to use a set of simple, uniform in architecture LSTM-based models to recover different kinds of temporal relations from text. Paper

This paper devel- ops such a resource – a probabilistic knowl- edge base acquired in the news domain – by extracting temporal relations between events from the ...

The fundamental research objective of our study is to improve the performance of temporal relation extraction for Electronic Health Records. Specifically, we ...

This technique leverages multilingual data to augment the training set. Fine-Tuned. Language Models such as GPT-2 is used to generate augmented data directly.