Extracting Entities and Relations with Joint Minimum Risk Training
Changzhi Sun, Yuanbin Wu, Man Lan, Shiliang Sun, Meng Wan, Kuang-Chih Lee, Kewen Wu · 2018
We investigate the task of joint entity relation extraction.Unlike prior efforts, we propose a new lightweight joint learning paradigm based on minimum risk training (MRT).Specifically, our algorithm optimizes a global loss function which is flexible and effective to explore interactions between the entity model and the relation model.We implement a strong and simple neural network where the MRT is executed.Experiment results on the benchmark ACE05 and NYT datasets show that our model is able to achieve state-of-the-art joint extraction performances.