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

被引:0
|
作者
Son, Suhyune [1 ]
Lim, Jungwoo [1 ]
Koo, Seonmin [1 ]
Kim, Jinsung [1 ]
Kim, Younghoon [2 ]
Lim, Youngsik [2 ]
Hyun, Dongseok [2 ]
Lim, Heuiseok [1 ]
机构
[1] Korea Univ, Comp Sci & Engn, 1 5-ka,Anam Dong, Seoul 02841, South Korea
[2] NAVER, 5 Jeongjail ro,Buljeong ro, Seongnam 13561, South Korea
基金
新加坡国家研究基金会;
关键词
Natural Language Processing; Information Extraction; Document-level Relation Extraction; Korean Relation Extraction; ENTITY;
D O I
10.1007/s10489-024-05605-9
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Document-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 TREK (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 TREK . 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.
引用
收藏
页码:8681 / 8701
页数:21
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