https://github.com/yao8839836/kg-bert

KG-BERT: BERT for Knowledge Graph Completion
https://github.com/yao8839836/kg-bert

bert knowledge-graph

Last synced: 6 days ago
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KG-BERT: BERT for Knowledge Graph Completion

• Host: GitHub
• URL: https://github.com/yao8839836/kg-bert
• Owner: yao8839836
• License: apache-2.0
• Created: 2019-09-04T08:54:05.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2022-07-11T05:16:18.000Z (over 2 years ago)
• Last Synced: 2024-12-08T07:51:39.774Z (13 days ago)
• Topics: bert, knowledge-graph
• Language: Python
• Size: 74.5 MB
• Stars: 708
• Watchers: 15
• Forks: 141
• Open Issues: 25
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# 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

```