A generative re-ranking model for dependency parsing
نویسندگان
چکیده
We propose a framework for dependency parsing based on a combination of discriminative and generative models. We use a discriminative model to obtain a kbest list of candidate parses, and subsequently rerank those candidates using a generative model. We show how this approach allows us to evaluate a variety of generative models, without needing different parser implementations. Moreover, we present empirical results that show a small improvement over state-of-the-art dependency parsing of English sentences.
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