| Dataset | MRR | Hits@10 | Hits@3 | Hits@1 |
|---|---|---|---|---|
| WikiPeople-3 | 0.373 | 0.588 | 0.401 | 0.284 |
| WikiPeople-4 | 0.386 | 0.596 | 0.462 | 0.265 |
| JF17K-3 | 0.732 | 0.856 | 0.764 | 0.669 |
| JF17K-4 | 0.810 | 0.913 | 0.844 | 0.755 |
To run the model, execute the following command:
CUDA_VISIBLE_DEVICES=0 python main.py --dataset dataset --num_iterations 200 --batch_size batch_size
--edim edim --rdim rdim --k k --n_i n_i --TR_ranks TR_ranks --dr dr --lr lr --input_dropout --input_d
--hidden_dropout --hidden_d
Available datasets are:
WikiPeople-3, WikiPeople-4, JF17K-3, JF17K-4
To reproduce the results from the paper, use the following hyperparameters settings:
| Dataset | batch_size | edim | rdim | k | n_i | TR_ranks | dr | lr | input_d | hidden_d |
|---|---|---|---|---|---|---|---|---|---|---|
| WikiPeople-3 | 128 | 50 | 50 | 4 | 50 | 50 | 0.995 | 0.0009267003174594345 | 0.3740776415163665 | 0.45137914784181227 |
| WikiPeople-4 | 128 | 25 | 25 | 5 | 25 | 40 | 0.995 | 0.006701566797680926 | 0.46694419227220374 | 0.18148844341064124 |
| JF17K-3 | 128 | 50 | 50 | 4 | 50 | 50 | 0.99 | 0.0008658318809880197 | 0.12747824547053027 | 0.501929359180091 |
| JF17K-4 | 128 | 25 | 25 | 5 | 25 | 40 | 0.995 | 0.0006071265071591076 | 0.010309222253012645 | 0.43198147413900445 |
| Dataset | MRR | Hits@10 | Hits@3 | Hits@1 |
|---|---|---|---|---|
| WN18 | 0.948 | 0.954 | 0.950 | 0.945 |
| FB15k | 0.824 | 0.888 | 0.847 | 0.787 |
CUDA_VISIBLE_DEVICES=0 python main.py --dataset dataset --num_iterations 200 --batch_size batch_size
--edim edim --rdim rdim --k k --n_i n_i --TR_ranks TR_ranks --dr dr --lr lr --input_dropout --input_d
--hidden_dropout1 hidden_d1 --hidden_dropout2 hidden_d2
Available datasets are:
WN18, FB15K
| Dataset | batch_size | edim | rdim | k | n_i | TR_ranks | dr | lr | input_d | hidden_d1 | hidden_d2 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| WN18 | 128 | 200 | 200 | 3 | 200 | 50 | 0.995 | 0.0005 | 0.2 | 0.1 | 0.2 |
| FB15k | 512 | 200 | 200 | 3 | 200 | 50 | 0.995 | 0.0005 | 0.3 | 0.5 | 0.0 |
python 3.6.8
numpy 1.16.3.1
pytorch 1.0.1
@inproceddings{liu2020getd,
title = {Generalizing Tensor Decomposition for N-ary Relational Knowledge Base},
author = {Liu, Yu and Yao, Quanming and Li, Yong},
booktitle = {The World Wide Web Conference},
year = {2020},
}The codes of this paper are based on the codes of TuckER (https://github.com/ibalazevic/TuckER) . We appreciate TuckER's codes and thank the authors of TuckER.
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