Abstract
This paper describes our submission for the SemEval 2018 Task 7 shared task on semantic relation extraction and classification in scientific papers. We extend the end-to-end relation extraction model of (Miwa and Bansal) with enhancements such as a character-level encoding attention mechanism on selecting pretrained concept candidate embeddings. Our official submission ranked the second in relation classification task (Subtask 1.1 and Subtask 2 Senerio 2), and the first in the relation extraction task (Subtask 2 Scenario 1).
Abstract (translated)
本文描述了我们对SemEval 2018任务7共享任务的提交，该任务涉及科学论文中的语义关系提取和分类。我们扩展了（Miwa和Bansal）的端到端关系提取模型，并在选择预训练概念候选嵌入时增强了诸如字符级编码注意机制。我们的官方提交在关系分类任务（子任务1.1和子任务2 Senerio 2）中排名第二，并且在关系提取任务（子任务2场景1）中排名第一。
URL
https://arxiv.org/abs/1808.08643
