Paper: Comparing Representations of Semantic Roles for String-To-Tree Decoding

ACL ID D14-1188
Title Comparing Representations of Semantic Roles for String-To-Tree Decoding
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2014
Authors

We introduce new features for incorpo- rating semantic predicate-argument struc- tures in machine translation (MT). The methods focus on the completeness of the semantic structures of the translations, as well as the order of the translated seman- tic roles. We experiment with translation rules which contain the core arguments for the predicates in the source side of a MT system, and observe that using these rules significantly improves the translation quality. We also present a new semantic feature that resembles a language model. Our results show that the language model feature can also significantly improve MT results.