yao8839836/kg-bert
A BERT-based model for knowledge graph completion through triple classification, relation prediction, and link prediction.
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KG-BERT applies the BERT transformer architecture to knowledge graph completion tasks by treating entity and relation text as token sequences. The model performs triple classification to verify if a head-relation-tail tuple is valid, relation prediction to identify missing relationships between entities, and link prediction to infer missing links in knowledge graphs. It trains on benchmark datasets including WN11, FB13, FB15K, WN18RR, and UMLS using text representations of entities and relations.
Frequently asked
- What is yao8839836/kg-bert?
- A BERT-based model for knowledge graph completion through triple classification, relation prediction, and link prediction.
- Is kg-bert open source?
- Yes — yao8839836/kg-bert is open source, released under the Apache-2.0 license.
- What language is kg-bert written in?
- yao8839836/kg-bert is primarily written in Python.
- How popular is kg-bert?
- yao8839836/kg-bert has 796 stars on GitHub.
- Where can I find kg-bert?
- yao8839836/kg-bert is on GitHub at https://github.com/yao8839836/kg-bert.