Research Area:  Machine Learning

Abstract:

We present simple BERT-based models for relation extraction and semantic role labeling. In recent years, state-of-the-art performance has been achieved using neural models by incorporating lexical and syntactic features such as part-of-speech tags and dependency trees. In this paper, extensive experiments on datasets for these two tasks show that without using any external features, a simple BERT-based model can achieve state-of-the-art performance. To our knowledge, we are the first to successfully apply BERT in this manner. Our models provide strong baselines for future research.

Keywords:  

Author(s) Name:  Peng Shi, Jimmy Lin

Publisher name:  arXiv:1904.05255

DOI:  10.48550/arXiv.1904.05255

Volume Information:  

Paper Link:   https://arxiv.org/abs/1904.05255