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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.

Installation Current version on PyPI Stable Supported Python Versions MIT License

  1. PyKEEN can be installed with the following commands:

python3 -m pip install git+https://github.com/SmartDataAnalytics/PyKEEN.git@master
  1. or 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:

pykeen

or alternatively:

python3 -m pykeen

then 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.json

or alternatively:

python3 -m pykeen -c /path/to/config.json

then 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/directory

or alternatively:

python3 -m pykeen-predict -m /path/to/model/directory -d /path/to/data/directory

Summarize the results of all experiments

To summarize the results of all experiments, please run following command:

pykeen-summarize -d /path/to/experiments/directory -o /path/to/output/file.csv

or alternatively:

python3 -m pykeen-summarize -d /path/to/experiments/directory -o /path/to/output/file.csv

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