This is the code for the paper Enhancing Geometric Ontology Embeddings for $\mathcal{EL++}$ with Negative Sampling and Deductive Closure Filtering.

Repository Overview

• run.py is an example of how to train and evaluate the model
• evaluation_utils.py: rank-based evaluator and evaluation score
• elembeddings_losses.py: GCI loss functions
• data_utils/data.py dataset classes
• data_utils/dataloader.py: ontology dataloader
• data_utils/deductive_closure.py: deductive closure computation
• models/elembeddings.py: ELEmbeddings model
• models/naive.py: naive predictor implementation

Dependencies

• Python 3.9
• Anaconda

Set up environment

git clone https://github.com/bio-ontology-research-group/geometric_embeddings.git
cd geometric_embeddings
conda env create -f environment.yml
conda activate embeddings