Such a representation is able to capture alignment between the natural language words and semantics at the span level.
we marginalize t in the above equation and the resulting model is a latent-variable CRF (Quattoni et al., 2005): Given a dataset D of (n, m) pairs, our objective is to minimize the negative log-likelihood: 7 The gradient for model parameter w k is: where f k (n, m, t) represents the number of occurrences of the k-th feature.