Multilingual Knowledge Graph

Multilingual knowledge graphs (MLKGs) aim to represent factual information across multiple languages, overcoming the limitations of English-centric knowledge bases. Current research focuses on improving knowledge graph completion, particularly for low-resource languages, often leveraging pretrained multilingual language models (MLLMs) and incorporating knowledge constraints or graph alignment techniques to enhance accuracy and coverage. These advancements are significant for improving cross-lingual information retrieval, machine translation evaluation, and various knowledge-intensive NLP tasks, ultimately fostering more inclusive and comprehensive knowledge representation.