It is unclear at the first glance how to encode word embeddings into the tree kernels effectively so that word embeddings could help to improve the generalization performance of RE.
we report the performance of these augmented systems in Table 2 for the two scenarios: (i) in-domain: both training and testing are performed on the source domain via 5-fold cross validation and (ii) out-of-domain: models are trained on the source domain but evaluated on the three target domains.