A package for training and evaluating knowledge graph embeddings
Project description
PyKEEN (Python KnowlEdge EmbeddiNgs) is a package for training and evaluating knowledge graph embeddings.
The system has a modular architecture, and can be configured by the user through the command line interface.
Currently, the framework is under development.
Installation
PyKEEN can be installed with the following commands:
python3 -m pip install git+https://github.com/SmartDataAnalytics/PyKEEN.git@masteror in editable mode with:
$ git clone https://github.com/SmartDataAnalytics/PyKEEN.git pykeen
$ cd pykeen
$ python3 -m pip install -e .How to Use
To start PyKEEN, please run the following command:
pykeenor alternatively:
python3 -m pykeenthen the command line interface will assist you to configure your experiments.
To start PyKEEN with an existing configuration file, please run the following command:
pykeen -c /path/to/config.jsonor alternatively:
python3 -m pykeen -c /path/to/config.jsonthen the command line interface won’t be called, instead the pipeline will be started immediately.
Starting PyKEEN’s prediction pipeline
To make prediction based on a trained model, please run following command:
pykeen-predict -m /path/to/model/directory -d /path/to/data/directoryor alternatively:
python3 -m pykeen-predict -m /path/to/model/directory -d /path/to/data/directorySummarize the results of all experiments
To summarize the results of all experiments, please switch to root directory containing the directories for each experiment, and run following command:
pykeen-summarizeor alternatively:
python3 -m pykeen-summarizeRelease history Release notifications | RSS feed
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