'''Your interests/skills:''' Deep Learning, Natural Language Processing, Knowledge Bases

'''Step 1:''' Implement a BERT model with two heads: one for mention detection and one to generate mention embeddings. Find a proper way to embed entities from a knowledge base (e.g. Wikipedia2vec). Then perform candidate selection using similarity search between mention embeddings and entity embeddings.

'''Step 2:'''
Look for ways to improve the performance and especially the time consumption of your system.

'''Step 3:'''
Thoroughly evaluate your system. Compare it with at least two other approaches (one state of the art system and one baseline) on different benchmarks. Analyse your results in detail.