TODO (2 week deadline)

[bakerwho]

Build Python modules to:

• negatively sample facts (each fact is 3 numbers) from SVO dataset (n_neg_facts, sampling_params?)
• compile datasets using specified numbers/ratios of true & false facts
• adapt torch-kge or other code to run on our datasets
• build 
visualizations (PCA) of embeddings

• build Word2Vec/glove embeddings with BOW for comparison
• build linear classifier + MLP to classify true/false based on embeddings


For June 1 Monday:

• Create a reduced dataset (50-50 T/F) and get it pre-processed enough to run TransE, TransH, HolE
• MAYBE start building visualization code?

Spacy-NOW & WikiHumans:

• List of named entities, or (better) (head, , tail) triples.

[bakerwho]

For June 1 Monday:

• Create a reduced dataset (50-50 T/F) and get it pre-processed enough to run TransE, TransH, HolE
• MAYBE start building visualization code?