Papers with Multilingual knowledge graphs

3 papers
Cross-lingual Knowledge Graph Alignment via Graph Convolutional Networks (D18-1)

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Challenge: Existing approaches to align multilingual knowledge graphs with counterparts in different languages are not effective.
Approach: They propose a novel approach for cross-lingual KG alignment via graph convolutional networks . they train GCNs to embed entities of each language into a unified vector space .
Outcome: The proposed approach gets the best performance on real multilingual KGs compared with other embedding-based approaches.
Aligning Cross-Lingual Entities with Multi-Aspect Information (D19-1)

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Challenge: Existing knowledge graphs that represent entities in different languages are not covered by existing systems.
Approach: They propose two ways to embed entities from multilingual knowledge graphs into the same vector space, where equivalent entities are close to each other.
Outcome: The proposed method significantly outperforms existing systems on two benchmark datasets.
KG-TRICK: Unifying Textual and Relational Information Completion of Knowledge for Multilingual Knowledge Graphs (2025.coling-main)

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Challenge: Existing studies have shown that combining information from KGs in different languages aids knowledge Graph Completion and Knowledge Graph Enhancement.
Approach: They propose a sequence-to-sequence framework that unifies tasks of textual and relational information completion for multilingual knowledge graphs.
Outcome: The proposed framework unifies tasks of KGC and KGE into a single framework.

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