Do pre-trained models benefit knowledge graph completion? A reliable evaluation and a reasonable approach

• Main Authors: LV, Xin, LIN, Yankai, CAO, Yixin, HOU, Lei, LI, Juanzi, LIU, Zhiyuan, LI, Peng, ZHOU, Jie
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: Databases and Information Systems; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/7446; https://ink.library.smu.edu.sg/context/sis_research/article/8449/viewcontent/2022.findings_acl.282.pdf
• Institution: Singapore Management University

In recent years, pre-trained language models (PLMs) have been shown to capture factual knowledge from massive texts, which encourages the proposal of PLM-based knowledge graph completion (KGC) models. However, these models are still quite behind the SOTA KGC models in terms of performance. In this w...