We denote the set of n-grams of m q as W n (m q ) and use W n (m q ) to retrieve the subgraph as Next, to select the correct fact (the answer) in the subgraph, we match the mention m q with candidate subjects in S q , and match the pattern p q with candidate relations in R q .
we want to maximize the log-likelihood ( 1)The probabilities in (1) are modeled by s ∈Sq e h(f (mq ),f (s )) (2) r ∈Rq e h(g(pq ),g(r )) , where f : M S → R d maps the mention and the subject onto a d-dimensional differentiable manifold embedded in the Hilbert space and similarly, g : P R → R d .