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KG-BERT: BERT for Knowledge Graph Completion
| Date | Stars |
|---|---|
| 2026-07-31 | 796 |
| 2026-08-06 | 796 |
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# KG-BERT: BERT for Knowledge Graph Completion The repository is modified from [pytorch-pretrained-BERT](https://github.com/huggingface/pytorch-pretrained-BERT) and tested on Python 3.5+. ## Installing requirement packages ```bash pip install -r requirements.txt ``` ## Data (1) The benchmark knowledge graph datasets are in ./data. (2) entity2text.txt or entity2textlong.txt in each dataset contains entity textual sequences. (3) relation2text.txt in each dataset contains relation textual sequences. ## Reproducing results ### 1. Triple Classification #### WN11 ```shell python run_bert_triple_classifier.py --task_name kg --do_train --do_eval --do_predict --data_dir ./data/WN11 --bert_model bert-base-uncased --max_seq_length 20 --train_batch_size 32 --learning_rate 5e-5 --num_train_epochs 3.0 --output_dir ./output_WN11/ --gradient_accumulation_steps 1 --eval_batch_size 512 ``` #### FB13 ```shell python run_bert_triple_classifier.py --task_name kg --do_train --do_eval --do_predict --data_dir ./data/FB13 --bert_model bert-base-cased --max_seq_length 200 --train_batch_size 32 --learning_rate 5e-5 --num_train_epochs 3.0 --output_dir ./output_FB13/ --gradient_accumulation_steps 1 --eval_batch_size 512 ``` ### 2. Relation Prediction #### FB15K ```shell python3 run_bert_relation_prediction.py --task_name kg --do_train --do_eval --do_predict --data_dir ./data/FB15K --bert_model bert-base-cased --max_seq_length 25 --train_batch_size 32 --learning_rate 5e-5 --num_train_epochs 20.0 --output_dir ./output_FB15K/ --gradient_accumulation_steps 1 --eval_batch_size 512 ``` ### 3. Link Prediction #### WN18RR ```shell python3 run_bert_link_prediction.py --task_name kg --do_train --do_eval --do_predict --data_dir ./data/WN18RR--bert_model bert-base-cased --max_seq_length 50 --train_batch_size 32 --learning_rate 5e-5 --num_train_epochs 5.0 --output_dir ./output_WN18RR/ --gradient_accumulation_steps 1 --eval_batch_size 5000 ``` #### UMLS ```shell python3 run_bert_link_prediction.py --task_name kg --do_train --do_eval --do_predict --data_dir ./data/umls --bert_model bert-base-uncased --max_seq_length 15 --train_batch_size 32 --learning_rate 5e-5 --num_train_epochs 5.0 --output_dir ./output_umls/ --gradient_accumulation_steps 1 --eval_batch_size 135 ``` #### FB15k-237 ```shell python3 run_bert_link_prediction.py --task_name kg --do_train --do_eval --do_predict --data_dir ./data/FB15k-237 --bert_model bert-base-cased --max_seq_length 150 --train_batch_size 32 --learning_rate 5e-5 --num_train_epochs 5.0 --output_dir ./output_FB15k-237/ --gradient_accumulation_steps 1 --eval_batch_size 1500 ```
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matched fp:84b5a9d183813bf6, topic:knowledge-graph, desc:knowledge graph