However, the global optimum is expensive, in which each mention gets an optimum sense, to search over the space of all mention senses of all mentions in the document.
we approximately assign each mention independently: where P (C(m l )|s l j ) is proportional to cosine similarity between context vector and mention sense cluster center µ l j to measure the mention's local similarity, namely local probability.