In this paper, we present three different strategies to utilize Babel-Net resources in SMT systems, namely using direct training data, domain adaptation and OOV post-processing approaches.
the first strategy very straightforwardly appends the bilingual dictionary extracted from Ba-belNet to the initial training data, and then verifies the impact on translation performance; the second uses domainadaptation methods to select in-domain entries from the extracted bilingual dictionary, which are then added to the initial training data in a similar manner; finally we directly call the BabelNet API to post-process OOVs contained in the translation of the source sentence.