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Exploiting document graphs for inter-sentence relation extraction

Can, Duy Cat (2020) Exploiting document graphs for inter-sentence relation extraction. Technical Report. BMC Journal of Biomedical Semantics. (Submitted)

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Background: Most previous relation extraction (RE) studies have focused on intra-sentence relations and haveignored relations that span sentences, i.e. inter-sentence relations. Such relations connect entities at thedocument level rather than as relational facts in a single sentence. Extracting facts that are expressed acrosssentences leads to some challenges and requires different approaches than those usually applied in recentintra-sentence relation extraction. Despite recent results, there are still limitations to be overcome.Results:We present a novel representation for a sequence of consecutive sentences, namely documentsub-graph, to extract inter-sentence relations. Experiments on the BioCreative V Chemical-Disease Relationcorpus demonstrate the advantages and robustness of our novel system to extract both intra- andinter-sentence relations in biomedical literature abstracts. The experimental results are comparable tostate-of-the-art approaches and show the potential by demonstrating the effectiveness of graphs, deeplearning-based model and other processing techniques. Experiments were also carried out to verify therationality and impact of various additional information and model components.Conclusions:Our proposed graph-based representation helps to extract∼50% of inter-sentence relations andboosts the model performance on both precision and recall compared to the baseline model.

Item Type: Technical Report (Technical Report)
Subjects: Information Technology (IT)
Divisions: Faculty of Information Technology (FIT)
Depositing User: Duy-Cat Can
Date Deposited: 18 Dec 2020 09:07
Last Modified: 18 Dec 2020 09:07

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