pykeen 0.0.14

A package for training and evaluating knowledge graph embeddings

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.

Citation

If you use PyKEEN in your work, please cite:

[1]

Ali, M., et al. (2018). BioKEEN: A library for learning and evaluating biological knowledge graph embeddings. bioRxiv 475202.

Installation

1. PyKEEN can be installed with the following commands:

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

2. 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