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https://github.com/facebookresearch/kbc
Tools for state of the art Knowledge Base Completion.
https://github.com/facebookresearch/kbc
Last synced: 8 days ago
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Tools for state of the art Knowledge Base Completion.
- Host: GitHub
- URL: https://github.com/facebookresearch/kbc
- Owner: facebookresearch
- License: other
- Created: 2017-11-16T14:51:38.000Z (almost 7 years ago)
- Default Branch: main
- Last Pushed: 2021-08-16T09:12:01.000Z (about 3 years ago)
- Last Synced: 2024-03-04T16:44:27.017Z (8 months ago)
- Language: Python
- Homepage:
- Size: 43 KB
- Stars: 250
- Watchers: 59
- Forks: 39
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
README
# Knowledge Base Completion (kbc)
This code reproduces results in [Canonical Tensor Decomposition for Knowledge Base Completion](https://arxiv.org/abs/1806.07297) (ICML 2018).
## Installation
Create a conda environment with pytorch cython and scikit-learn :
```
conda create --name kbc_env python=3.7
source activate kbc_env
conda install --file requirements.txt -c pytorch
```
Then install the kbc package to this environment
```
python setup.py install
```
## Datasets
To download the datasets, go to the kbc/scripts folder and run:
```
chmod +x download_data.sh
./download_data.sh
```
Once the datasets are download, add them to the package data folder by running :
```
python kbc/process_datasets.py
```
This will create the files required to compute the filtered metrics.
## Running the code
Reproduce the results below with the following command :
```
python kbc/learn.py --dataset FB15K --model ComplEx --rank 500 --optimizer
Adagrad --learning_rate 1e-1 --batch_size 1000 --regularizer N3 --reg 1e-2
--max_epochs 100 --valid 5
```
## Results
In addition to the results in the [paper](https://arxiv.org/abs/1806.07297), here are the performances of ComplEx
regularized with the weighted N3 on several datasets, for several dimensions. We use an init scale of 1e-3, a learning rate of 0.1, a batch size of 1000 and 100 max epochs unless specified otherwise. We use the Adagrad optimizer.
### FB15k
For rank 2000 : learning rate 1e-2, batch-size 100, max epochs 200.
| rank | 5|25|50|100|500|2000|
|------------|--|--|--|---|---|----|
| MRR | 0.36|0.61|0.78|0.83|0.84|0.86 |
| H@1 | 0.27|0.52|0.73|0.79|0.80|0.83 |
| H@3 | 0.41|0.67|0.81|0.85|0.87|0.87 |
| H@10 | 0.55|0.77|0.86|0.89|0.91|0.91 |
| | | | | | | |
| | | | | | | |
| reg | 1e-5|1e-5|1e-5|7.5e-4|1e-2|2.5e-3 |
| #Params | 163k|815k|1.630M|3.259M|1.630M|65.184M |
### WN18
Max Epochs : 20
| rank | 5|8|16|25|50|100|500|2000 |
|------------| -|-|-|-|-|-|-|- |
| MRR | 0.19|0.45|0.92|0.94|0.95|0.95|0.95|0.95 |
| H@1 | 0.14|0.37|0.91|0.94|0.94|0.94|0.94|0.94 |
| H@3 | 0.20|0.50|0.93|0.94|0.95|0.95|0.95|0.95 |
| H@10 | 0.29|0.60|0.94|0.95|0.95|0.95|0.96|0.96 |
| | | | | | | | | |
| | | | | | | | | |
| reg | 1e-3|5e-4|5e-4|1e-3|5e-3|5e-2|5e-2|5e-2 |
| #Params | 410k|656k|1.311M|2.049M|4.098M|8.196M|40.979M|163.916M|
### FB15K-237
Batch Size : 100 (1000 for rank 1000)
| rank | 5|25|50|100|500|1000|2000 |
|------------| -|-|-|-|-|-|- |
| MRR | 0.28|0.33|0.34|0.35|0.36|0.37|0.37 |
| H@1 | 0.20|0.24|0.25|0.26|0.27|0.27|0.27 |
| H@3 | 0.31|0.36|0.37|0.39|0.40|0.40|0.40 |
| H@10 | 0.44|0.51|0.52|0.54|0.56|0.56|0.56 |
| | | | | | | | |
| | | | | | | | |
| reg | 5e-4|5e-2|5e-2|5e-2|5e-2|5e-2|5e-2 |
| #Params | 150k|751k|1.502M|3.003M|15.015M|30.030M|60.060M |
### WN18RR
Batch Size : 100 (1000 for rank 8)
| rank | 5|8|16|25|50|100|500|2000 |
|------------| -|-|-|-|-|-|-|- |
| MRR | 0.26|0.36|0.42|0.44|0.46|0.47|0.49|0.49 |
| H@1 | 0.20|0.38|0.39|0.41|0.43|0.43|0.44|0.44 |
| H@3 | 0.29|0.38|0.42|0.45|0.47|0.49|0.50|0.50 |
| H@10 | 0.36|0.41|0.46|0.49|0.52|0.56|0.58|0.58 |
| | | | | | | | | |
| | | | | | | | | |
| reg | 5e-4|5e-4|5e-2|1e-1|1e-1|1e-1|1e-1|1e-1 |
| #Params | 410k|655k|1.311M|2.048M|4.097M|8.193M|40.975M|163.860M |
### YAGO3-10
| rank | 5|16|25|50|100|500|1000 |
|------------| -|-|-|-|-|-|- |
| MRR | 0.15|0.34|0.46|0.54|0.56|0.57|0.58 |
| H@1 | 0.10|0.26|0.38|0.47|0.49|0.50|0.50 |
| H@3 | 0.16|0.37|0.50|0.58|0.60|0.62|0.62 |
| H@10 | 0.25|0.50|0.60|0.67|0.69|0.71|0.71 |
| | | | | | | | |
| | | | | | | | | |
| reg | 1e-3|1e-4|5e-3|5e-3|5e-3|5e-3|5e-3 |
| #Params | 1.233M|3.944M|6.163M|12.326M|24.652M|123.262M|246.524M|
## License
kbc is CC-BY-NC licensed, as found in the LICENSE file.