Using Cross-Lingual Projections to Generate Semantic Role Labeled Annotated Corpus for Urdu - A Resource Poor Language

摘要: In this paper we explore the possibility of using cross lingual projections that help to automatically induce role-semantic annotations in PropBank paradigm for Urdu, a resource poor language. This technique provides annotation based on word alignments. It is relatively inexpensive and has potential reduce human effort involved creating semantic role resources. The projection model exploits lexical as well syntactic information an English-Urdu parallel corpus. We show our method generates reasonably good with accuracy 92% short structured sentences. Using generated annotated corpus, conduct preliminary experiments create labeler Urdu. results though modest, are promising indicate generate large scale