These rules make sense because a justification that discusses its assertion's topic's effects frequently is likely to be very topically coherent, thus having a clear justification.
recall that for each error type t, our heuristics only label a subset of the training arguments with error severity values for t. 11 To label the remain- 11 The heuristics for GE, LO, IS, UA, and UJ can label 39%, 66.%, 86%, 50%, and 87% of the training arguments, ing training arguments, we apply EM to bootstrap from the heuristically labeled seeds for t. we initialize the model parameters using only the seeds for t. After that, we iterate the E-step and the M-step until convergence.