2004 MaxMarginParsing
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- (Taskar et al., 2004) ⇒ Ben Taskar, Dan Klein, Michael Collins, Daphne Koller, Christopher D. Manning. (2004). “Max-Margin Parsing."In: Proceedings of the 2004 Conference on Empirical Methods in Natural Language Processing (EMNLP 2004).
Subject Headings: Max-Margin Classification, Natural Language Parsing Task.
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Abstract
- We present a novel discriminative approach to parsing inspired by the large-margin criterion underlying support vector machines. Our formulation uses a factorization analogous to the standard dynamic programs for parsing. In particular, it allows one to efficiently learn a model which discriminates among the entire space of parse trees, as opposed to reranking the top few candidates. Our models can condition on arbitrary features of input sentences, thus incorporating an important kind of lexical information without the added algorithmic coplexity of modeling headedness. We provide an efficient algorithm for learning such models and show experimental evidence of the model’s improved performance over a natural baseline model and a lexicalized probabilistic context-free grammar.
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