Fusing topology contexts and logical rules in language models for knowledge graph completion
Knowledge graph completion (KGC) aims to infer missing facts based on the observed ones, which is significant for many downstream applications. Given the success of deep learning and pre-trained language models (LMs), some LM-based methods are proposed for the KGC task. However, most of them focus o...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/170544 |