Paper: Discriminative Induction of Sub-Tree Alignment using Limited Labeled Data

ACL ID C10-1118
Title Discriminative Induction of Sub-Tree Alignment using Limited Labeled Data
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2010
Authors

We employ Maximum Entropy model to con- duct sub-tree alignment between bilingual phrasal structure trees. Various lexical and structural knowledge is explored to measure the syntactic similarity across Chinese-English bi- lingual tree pairs. In the experiment, we evalu- ate the sub-tree alignment using both gold standard tree bank and the automatically parsed corpus with manually annotated sub-tree align- ment. Compared with a heuristic similarity based method, the proposed method significant- ly improves the performance with only limited sub-tree aligned data. To examine its effective- ness for multilingual applications, we further at- tempt different approaches to apply the sub-tree alignment in both phrase and syntax based SMT systems. We then compare the performance with th...