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  1. Accurate Unlexicalized Parsing.Dan Klein & Christopher D. Manning - unknown
    We demonstrate that an unlexicalized PCFG can parse much more accurately than previously shown, by making use of simple, linguistically motivated state splits, which break down false independence assumptions latent in a vanilla treebank grammar. Indeed, its performance of 86.36% (LP/LR F1) is better than that of early lexicalized PCFG models, and surprisingly close to the current state-of-theart. This result has potential uses beyond establishing a strong lower bound on the maximum possible accuracy of unlexicalized models: an unlexicalized PCFG is (...)
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  • Syntactic Gradience: The Nature of Grammatical Indeterminacy.Bas Aarts - 2007 - Oxford University Press UK.
    This is the first exhaustive investigation of gradience in syntax, conceived of as grammatical indeterminacy. It looks at gradience in English word classes, phrases, clauses and constructions, and examines how it may be defined and differentiated. Professor Aarts addresses the tension between linguistic concepts and the continuous phenomena they describe by testing and categorizing grammatical vagueness and indeterminacy. He considers to what extent gradience is a grammatical phenomenon or a by-product of imperfect linguistic description, and makes a series of linked (...)
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  • Feature-rich part-of-speech tagging with a cyclic dependency network.Christopher Manning - manuscript
    first-order HMM, the current tag t0 is predicted based on the previous tag t−1 (and the current word).1 The back- We present a new part-of-speech tagger that ward interaction between t0 and the next tag t+1 shows demonstrates the following ideas: (i) explicit up implicitly later, when t+1 is generated in turn. While unidirectional models are therefore able to capture both use of both preceding and following tag con-.
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  • Foundations of Statistical Natural Language Processing.Christopher Manning & Hinrich Schutze - 1999 - MIT Press.
    Statistical approaches to processing natural language text have become dominant in recent years. This foundational text is the first comprehensive introduction to statistical natural language processing to appear. The book contains all the theory and algorithms needed for building NLP tools. It provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students and researchers to construct their own implementations. The book covers collocation finding, word sense disambiguation, probabilistic parsing, information retrieval, (...)
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