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1. 핵심 요약
- KBC tasks에 pre-trained LM 이용
- knowledge graph의 triples를 textual sequence로 인식 → 이러한 triples를 만들기 위해 KG-BERT라는 새로운 framework 제안
- input : entity, relation description of a triple → computes scoring function of the triple
- 결과 : triple classification, link prediction, relation prediction tasks에서 SOTA 달성
2. 논문 링크
https://arxiv.org/abs/1909.03193
KG-BERT: BERT for Knowledge Graph Completion
Knowledge graphs are important resources for many artificial intelligence tasks but often suffer from incompleteness. In this work, we propose to use pre-trained language models for knowledge graph completion. We treat triples in knowledge graphs as textua
arxiv.org
3. 논문 설명 링크
[KG-BERT] BERT for Knowledge Graph Completion
Abstract
coding-moomin.notion.site
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