- Comparison with ALIGN could be better. ALIGN used content window size 10 vs this paper's 5, vector dimension of 500 vs this paper's 200. Also its not clear to me whether N(e_j) includes only entities that link to e_j. The graph is directed and consists of wikipedia outlinks, but is adjacency defined as it would be for an undirected graph? For ALIGN, the context of an entity is the set of entities that link to that entity. If N(e_j) is different, we cannot tell how much impact this change has on the learned vectors, and this could contribute to the difference in scores on the entity similarity task. - It is sometimes difficult to follow whether "mention" means a string type, or a particular mention in a particular document. The phrase "mention embedding" is used, but it appears that embeddings are only learned for mention senses.
- It is difficult to determine the impact of sense disambiguation order without comparison to other unsupervised entity linking methods. - General Discussion:
- It is difficult to determine the impact of sense disambiguation order without comparison to other unsupervised entity linking methods.