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Transactions of the Association for Computational Linguistics
This paper proposes a discriminative forest reranking algorithm for dependency parsing that can be seen as a form of efficient stacked parsing. A dynamic programming shift-reduce parser produces a packed derivation forest which is then scored by a discrim-inative reranker, using the 1-best tree output by the shift-reduce parser as guide features in addition to third-order graph-based features. To improve efficiency and accuracy, this paper also proposes a novel shift-reduce parser thatfatcat:7iyq4bnifncebpctx2rb72fmqe