1 code implementation • 29 Nov 2022 • Bing Liu, Harrisen Scells, Wen Hua, Guido Zuccon, Genghong Zhao, Xia Zhang
Making compatible predictions thus should be one of the goals of training an EA model along with fitting the labelled data: this aspect however is neglected in current methods.
1 code implementation • 22 Aug 2022 • Bing Liu, Wen Hua, Guido Zuccon, Genghong Zhao, Xia Zhang
To include in the EA subtasks a high proportion of the potential mappings originally present in the large EA task, we devise a counterpart discovery method that exploits the locality principle of the EA task and the power of trained EA models.
1 code implementation • EMNLP 2021 • Bing Liu, Harrisen Scells, Guido Zuccon, Wen Hua, Genghong Zhao
Entity Alignment (EA) aims to match equivalent entities across different Knowledge Graphs (KGs) and is an essential step of KG fusion.