Codebase for analyzing sub-morphemic systematicity using CELEX and word2vec.

Before running, you must have the Google News pretrained word embeddings: http://mccormickml.com/2016/04/12/googles-pretrained-word2vec-model-in-python/

To run:

python main.py

To do:

• Make code more modular
• Save dataset with embeddings so model doesn't have to be reloaded each time
• Validate against other word embedding models?