A Dataset for Inter-Sentence Relation Extraction using Distant Supervision

Mandya, Angrosh, Bollegala, Danushka ORCID: 0000-0003-4476-7003, Coenen, Frans ORCID: 0000-0003-1026-6649 and Atkinson, Katie ORCID: 0000-0002-5683-4106 (2018) A Dataset for Inter-Sentence Relation Extraction using Distant Supervision In: Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018), 2018-5-7 - 2018-5-12.

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Abstract

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 Item (Unspecified)
Uncontrolled Keywords:	Inter-sentence Relation Extraction, Relation Extraction, Inter-sentence Relation Extraction Dataset, Distant Supervision for Inter-sentence Relation Extraction
Depositing User:	Symplectic Admin
Date Deposited:	03 Jul 2018 08:11
Last Modified:	23 May 2026 01:20
DOI:	10.63317/374gmpeb43yn
Related Websites:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3023278
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