Paper: Handling Ambiguities of Bilingual Predicate-Argument Structures for Statistical Machine Translation

ACL ID P13-1111
Title Handling Ambiguities of Bilingual Predicate-Argument Structures for Statistical Machine Translation
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2013
Authors

Predicate-argument structure (PAS) has been demonstrated to be very effective in improving SMT performance. However, since a source- side PAS might correspond to multiple differ- ent target-side PASs, there usually exist many PAS ambiguities during translation. In this pa- per, we group PAS ambiguities into two types: role ambiguity and gap ambiguity. Then we propose two novel methods to handle the two PAS ambiguities for SMT accordingly: 1) in- side context integration; 2) a novel maximum entropy PAS disambiguation (MEPD) model. In this way, we incorporate rich context in- formation of PAS for disambiguation. Then we integrate the two methods into a PAS- based translation framework. Experiments show that our approach helps to achieve sig- nificant improvements on translation qua...