This is the source code for: Context-aware Entity Typing in Knowledge Graphs.

Related tags

Deep LearningCET
Overview

Context-aware Entity Typing in Knowledge Graphs

This is the source code for: Context-aware Entity Typing in Knowledge Graphs.

Requirements

  • Python 3
  • PyTorch >= 1.6.0
  • dgl >= 0.5.3

Usage

Data preprocessing:

cd data
python preprocess.py --dataset FB15kET
python preprocess.py --dataset YAGO43kET

Train:

########### FB15kET ###########
# CET
python run.py --model CET --dataset FB15kET --load_ET --load_KG --neighbor_sampling \
--hidden_dim 100 --temperature 0.5 --lr 0.001 --loss FNA --beta 4.0 --cuda

# R-GCN
python run.py --model RGCN --dataset FB15kET --load_ET --load_KG --neighbor_sampling \
--hidden_dim 100 --lr 0.001 --loss FNA --beta 3.0 --cuda

# CompGCN
python run.py --model CompGCN --dataset FB15kET --load_ET --load_KG --neighbor_sampling \
--hidden_dim 100 --lr 0.001 --loss FNA --activation relu --cuda

########### YAGO43kET ###########
# CET
python run.py --model CET --dataset YAGO43kET --load_ET --load_KG --neighbor_sampling \
--hidden_dim 100 --temperature 0.5 --lr 0.001 --loss FNA --beta 2.0 --cuda

# R-GCN
python run.py --model RGCN --dataset YAGO43kET --load_ET --load_KG --neighbor_sampling \
--hidden_dim 100 --lr 0.001 --loss FNA --beta 2.0 --cuda

# CompGCN
python run.py --model CompGCN --dataset YAGO43kET --load_ET --load_KG --neighbor_sampling \
--hidden_dim 100 --lr 0.001 --loss FNA --activation relu --cuda

The KGE baselines can be found in KGE_baselines.

Acknowledgement

We refer to the code of DGL. Thanks for their contributions.

Owner
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