The paper introduces an LR-based algorithm for efficient phrase structure parsing of morpholog- ically rich languages. The algorithm generalizes lexicalized parsing (Collins, 2003) by allowing a structured representation of the lexical items. Together with a discriminative weighting com- ponent (Collins, 2002), we show that this representation allows us to achieve state of the art accurracy results on a morphologically rich language such as French while achieving more effi- cient parsing times than the state of the art parsers on the French data set. A comparison with English, a lexically poor language, is also provided.

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