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

• Published in: Applied intelligence (Dordrecht, Netherlands) Vol. 54; no. 17-18; pp. 8681 - 8701
• Main Authors: Son, Suhyune, Lim, Jungwoo, Koo, Seonmin, Kim, Jinsung, Kim, Younghoon, Lim, Youngsik, Hyun, Dongseok, Lim, Heuiseok
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.09.2024; Springer Nature B.V
• Subjects: Annotations; Artificial Intelligence; Computer Science; Cultural heritage; Datasets; Documents; Encyclopedias; Korean language; Language; Machines; Manufacturing; Mechanical Engineering; Processes; Qualitative analysis; Statistical analysis; Subject specialists; Document-level Relation Extraction; Information Extraction; Korean Relation Extraction; Natural Language Processing

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 stu...