We briefly describe our techniques here and direct the interested readers to the paper.
the EL model computes several similarity/coherence scores S in a "feature abstraction layer" which computes several measures of similarity between the context of the mention m in the query document and the context of the candidate link's Wikipedia page which are fed to a feed-forward neural layer which acts as a binary classifier to predict the correct link for m. the feature abstraction layer computes cosine similarities (Sil and Florian, 2016) between the representations of the source query document and the target Wikipedia pages over various granularities.