Modern Social Science Research

As an important technology for structured knowledge representation, knowledge graphs are widely used in natural language processing and other fields. This paper systematically combs the research status and development trends in this field. Aiming at the shortcomings of existing methods in cross-lingual entity alignment and translation knowledge integration, a BTRM (Bilingual Translation Relationship Modeling) model based on bilingual translation relationship modeling is proposed. The model improves the construction quality of bilingual knowledge graphs through the collaborative work of three integrated modules. Experimental results show that the BTRM model outperforms traditional knowledge graph construction methods in terms of construction difficulty, translation accuracy and cross-lingual applications, especially in bilingual semantic alignment and knowledge fusion. This study not only provides a new theoretical framework and technical path for the construction of bilingual translation knowledge graphs, but also offers more reliable support for applications such as machine translation and cross-lingual information retrieval.

Bilingual translation; Knowledge graph; BTRM model; Language learning