  In this paper, we attempt to solve the problem of Prepositional Phrase (PP)
attachments in English. The motivation for the work comes from NLP applications
like Machine Translation, for which, getting the correct attachment of
prepositions is very crucial. The idea is to correct the PP-attachments for a
sentence with the help of alignments from parallel data in another language.
The novelty of our work lies in the formulation of the problem into a dual
decomposition based algorithm that enforces agreement between the parse trees
from two languages as a constraint. Experiments were performed on the
English-Hindi language pair and the performance improved by 10% over the
baseline, where the baseline is the attachment predicted by the MSTParser model
trained for English.
