Leveraging large language models for efficient representation learning for entity resolution

In this paper, the authors propose TriBERTa, a supervised entity resolution system that utilizes a pre-trained large language model and a triplet loss function to learn representations for entity matching. The system consists of two steps: first, name entity records are fed into a Sentence Bidirecti...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Xu, Xiaowei, Foua, Bi T, Wang, Xingqiao, Gunasekaran, Vivek, Talburt, John R
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Artificial Intelligence Computer Science - Computation and Language
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!