We address this potential issue by building a structural neural model for end-to-end relation extraction, following a recent line of efforts on globally optimized models for neural structured prediction (Zhou et al., 2015;Watanabe and Sumita, 2015;Andor et al., 2016;Wiseman and Rush, 2016).
we follow Miwa and Sasaki (2014), casting the task as an end-to-end tablefilling problem.