To estimate the coherence score, we again use cosine similarity between the vector of entity v e and that of context entities v ce .
to combine the proposed contextual information described above with standard NED features, we employ a method of supervised machine learning to rank the candidate entities given mention m and document d. we use Gradient Boosted Regression trees (GBRt) (Friedman, 2001), a stateof-the-art point-wise learning-to-rank algorithm widely used for various tasks, which has been recently adopted for the sort of tasks for which we employ it here (Meij et al., 2012).