A dataset for inter-sentence relation extraction using distant supervision

Mandya, A, Bollegala, D ORCID: 0000-0003-4476-7003, Coenen, F ORCID: 0000-0003-1026-6649 and Atkinson, K ORCID: 0000-0002-5683-4106 (2019) A dataset for inter-sentence relation extraction using distant supervision. .

Text lrecMandya_2018.pdf - Accepted Version Download (164kB)

Abstract

© LREC 2018 - 11th International Conference on Language Resources and Evaluation. All rights reserved. This paper presents a benchmark dataset for the task of inter-sentence relation extraction. The paper explains the distant supervision method followed for creating the dataset for inter-sentence relation extraction, involving relations previously used for standard intra-sentence relation extraction task. The study evaluates baseline models such as bag-of-words and sequence based recurrent neural network models on the developed dataset and shows that recurrent neural network models are more useful for the task of intra-sentence relation extraction. Comparing the results of the present work on iner-sentence relation extraction with previous work on intra-sentence relation extraction, the study suggests the need for more sophisticated models to handle long-range information between entities across sentences.

Item Type:	Conference or Workshop Item
Depositing User:	Symplectic Admin
Date Deposited:	03 Jul 2018 08:11
Last Modified:	28 Nov 2019 08:24
URI:	http://livrepository.liverpool.ac.uk/id/eprint/3023278

Repository Staff Access