TY  - JOUR
AB  - Relation extraction plays a fundamental role in applications of various research fields such as knowledge graph construction, event extraction, and question answering over knowledge graphs, as they often rely on extracting relationships between named entities. Relation extraction has been extensively studied in high-resource languages like English. However, there remains a significant gap in supporting languages with limited resources, defined as those lacking comprehensive annotated corpora, linguistic tools, or pre-trained models, limiting the completeness and accuracy of applications that rely on multilingual data. This paper provides a comprehensive survey of recent advances in relation extraction, focusing on multilingual approaches. We systematically review state-of-the-art methods, datasets used for evaluation, and key features leveraged in these approaches. Additionally, we perform a detailed comparative analysis of the surveyed methods, examining their methodologies, target domains, levels of extraction, explored languages, and effectiveness. Finally, we identify promising directions for future research, with an emphasis on enhancing multilingual relation extraction.
AU  - Ali, Manzoor
AU  - Speck, René
AU  - M. Zahera, Hamada
AU  - Saleem, Muhammad
AU  - Moussallem, Diego
AU  - Ngonga Ngomo, Axel-Cyrille
DO  - 10.17619/UNIPB/1-2442
PB  - Universitätsbibliothek
DP  - Universität Paderborn
LA  - eng
PY  - 2025
SN  - 2169-3536
SP  - 1 Online-Ressource (Seite 151907-151933) : Diagramme
T2  - IEEE Access
TI  - Multilingual Relation Extraction: A Survey
UR  - https://nbn-resolving.org/urn:nbn:de:hbz:466:2-56640
Y2  - 2026-01-13T04:46:54
ER  -