A Dataset for Inter-Sentence Relation Extraction using Distant Supervision
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)
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 as more useful for the task of intra-sentence relation extraction.Comparing the results of the present work on intra-sentence relation extraction with previous work on inter-sentence relation extraction, the study identifies the need for more sophisticated models to handle long-range information between entities across sentences.