Back close

Relation extraction using convolutional neural networks

Publisher : Lecture Notes in Computational Vision and Biomechanics

Year : 2019

Abstract :

Identifying the relationship between the entities plays a key role in understanding any natural language. The relation extraction is a task, which finds the relationship between entities in a sentence. The relation extraction and named entity recognition are the subtasks of information extraction. In this paper, we have experimented and analyzed the closed-domain relation extraction using three variants of temporal convolutional neural network on SemEval-2018 and SemEval-2010 relation extraction corpus. In this approach, the word-level features are formed from the distributed representation of text and the position information of entity are used as the feature for the model. © Springer Nature Switzerland AG 2019.

Admissions Apply Now