We describe a novel approach to machine translation that combines the strengths of the two leading corpus-based approaches: Phrasal SMT and EBMT. We use a syntactically informed d...
Abstract In this paper, we describe our Question Answering (QA) system called QUANTUM. The goal of QUANTUM is to find the answer to a natural language question in a large document ...
Information on subcategorization and selectional restrictions is important for natural language processing tasks such as deep parsing, rule-based machine translation and automatic...
For languages with (semi-) free word order (such as German), labelling grammatical functions on top of phrase-structural constituent analyses is crucial for making them interpreta...
Wolfgang Seeker, Ines Rehbein, Jonas Kuhn, Josef v...
Syntactic machine translation systems currently use word alignments to infer syntactic correspondences between the source and target languages. Instead, we propose an unsupervised...