A large-scale dataset for korean document-level relation extraction from encyclopedia texts-Reference-Cited by-同舟云学术

A large-scale dataset for korean document-level relation extraction from encyclopedia texts

Published:2024-07-02 Issue:17-18 Volume:54 Page:8681-8701
ISSN:0924-669X
Container-title:Applied Intelligence
language:en
Short-container-title:Appl Intell

Author:

Son Suhyune,Lim Jungwoo,Koo Seonmin,Kim Jinsung,Kim Younghoon,Lim Youngsik,Hyun Dongseok,Lim Heuiseok^ORCID

Abstract

AbstractDocument-level relation extraction (RE) aims to predict the relational facts between two given entities from a document. Unlike widespread research on document-level RE in English, Korean document-level RE research is still at the very beginning due to the absence of a dataset. To accelerate the studies, we present (Toward Document-Level Relation Extraction in Korean) dataset constructed from Korean encyclopedia documents written by the domain experts. We provide detailed statistical analyses for our large-scale dataset and human evaluation results suggest the assured quality of . Also, we introduce the document-level RE model that considers the named entity-type while considering the Korean language’s properties. In the experiments, we demonstrate that our proposed model outperforms the baselines and conduct qualitative analysis.

Funder

Institute for Information and Communications Technology Planning & Evaluation

Ministry of Science and ICT

ICT Creative Consilience program

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s10489-024-05605-9.pdf

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