We present a novel learning framework for pipeline models aimed at improving the communication between consecutive stages in a pipeline. Our method exploits the confidence scores ...
We present a noun chunker for German which is based on a head-lexicalised probabilistic contextfl'ee grammar. A manually developed grammar was semi-automatically extended wit...
We present a probabilistic model extension to the Tesni`ere Dependency Structure (TDS) framework formulated in (Sangati and Mazza, 2009). This representation incorporates aspects ...
We examine the expressive power of probabilistic context free grammars (PCFGs), with a special focus on the use of probabilities as a mechanism for reducing ambiguity by filtering ...
Abstract. A mismatch between differenteventspaceshasbeen used toargue against rank equivalence of classic probabilistic models of information retrieval and language models. We ques...