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Due to labor-intensive human labeling, this phenomenon deteriorates when handling knowledge represented in various languages. In this paper, we explore multilingual KG completion, which leverages limited seed alignment as a bridge, to embrace the collective knowledge from multiple languages. However, language alignment used in prior works is still not fully exploited: (1) alignment pairs are treated equally to maximally push parallel entities to be close, which ignores KG capacity inconsistency; (2) seed alignment is scarce and new alignment identification is usually in a noisily unsupervised manner. To tackle these issues, we propose a novel self-supervised adaptive graph alignment (SS-AGA) method. Specifically, SS-AGA fuses all KGs as a whole graph by regarding alignment as a new edge type. As such, information propagation and noise influence across KGs can be adaptively controlled via relation-aware attention weights. 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Extensive experiments on both the public multilingual DBPedia KG and newly-created industrial multilingual E-commerce KG empirically demonstrate the effectiveness of SS-AG","url_abs":"https://arxiv.org/abs/2203.14987v1","url_pdf":"https://arxiv.org/pdf/2203.14987v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"multilingual-knowledge-graph-completion-with-1","repo_url":"https://github.com/amzn/ss-aga-kgc","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"knowledge-graph-completion","task_name":"Knowledge Graph Completion"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/knowledge-graph-completion-on-dbp-5l-english","task":"Knowledge Graph Completion","dataset":"DBP-5L (English)","model":"SS-AGA","rank_in_archive_order":3,"of":3,"metrics":{"MRR":"32.1"},"uses_additional_data":false},{"leaderboard":"/sota/knowledge-graph-completion-on-dbp-5l","task":"Knowledge Graph Completion","dataset":"DBP-5L (Greek)","model":"SS-AGA","rank_in_archive_order":3,"of":3,"metrics":{"MRR":"35.3"},"uses_additional_data":false},{"leaderboard":"/sota/knowledge-graph-completion-on-dpb-5l-french","task":"Knowledge Graph Completion","dataset":"DPB-5L (French)","model":"SS-AGA","rank_in_archive_order":3,"of":3,"metrics":{"MRR":"36.6"},"uses_additional_data":false}],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=2203.14987","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.14987"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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