relation: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/3983/ title: Exploiting document graphs for inter-sentence relation extraction creator: Can, Duy Cat subject: Information Technology (IT) description: 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. publisher: BMC Journal of Biomedical Semantics date: 2020 type: Technical Report type: NonPeerReviewed format: application/pdf language: en identifier: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/3983/1/BMC_Journal_of_Biomedical_Semantics___manuscript__Copy_.pdf identifier: Can, Duy Cat (2020) Exploiting document graphs for inter-sentence relation extraction. Technical Report. BMC Journal of Biomedical Semantics. (Submitted)