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Stochastic Lexicalized ContextFree Grammar
, 1993
"... Stochastic lexicalized contextfree grammar (SLCFG) is an attractive compromise between the parsing efficiency of stochastic contextfree grammar (SCFG) and the lexical sensitivity of stochastic lexicalized treeadjoining grammar (SLTAG). SLCFG is a restricted form of SLTAG that can only generate ..."
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Cited by 44 (7 self)
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Stochastic lexicalized contextfree grammar (SLCFG) is an attractive compromise between the parsing efficiency of stochastic contextfree grammar (SCFG) and the lexical sensitivity of stochastic lexicalized treeadjoining grammar (SLTAG). SLCFG is a restricted form of SLTAG that can only
(Bi)Lexicalized ContextFree Grammars
"... Several recent stochastic parsers use bilexicalized grammars, where each word idiosyncratically prefers particular complements with particular head words. These parsers ' complexity is O(n 5). For two different bilexicalized formalisms, I present an algorithm improving this upper bound to O(n 4 ..."
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Several recent stochastic parsers use bilexicalized grammars, where each word idiosyncratically prefers particular complements with particular head words. These parsers ' complexity is O(n 5). For two different bilexicalized formalisms, I present an algorithm improving this upper bound to O
Parsing Techniques for Lexicalized ContextFree Grammars
, 2000
"... Stateofthe art parsers use lexicalized grammars to achieve high accuracy on realworld texts. Most of these systems are based on traditional parsing algorithms that were originally developed for the unlexicalized versions of the adopted grammar formalisms. We show that these parsing algorithms d ..."
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Cited by 4 (0 self)
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Stateofthe art parsers use lexicalized grammars to achieve high accuracy on realworld texts. Most of these systems are based on traditional parsing algorithms that were originally developed for the unlexicalized versions of the adopted grammar formalisms. We show that these parsing algorithms
Tree Insertion Grammar: A CubicTime, Parsable Formalism that Lexicalizes ContextFree Grammar without Changing the Trees Produced
 Computational Linguistics
, 1994
"... this paper, we study the problem of lexicalizing contextfree grammars and show that it enables faster processing. In previous attempts to take advantage of lexicalization, a variety of lexicalization procedures have been developed that convert contextfree grammars (CFGs) into equivalent lexicalize ..."
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Cited by 83 (2 self)
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this paper, we study the problem of lexicalizing contextfree grammars and show that it enables faster processing. In previous attempts to take advantage of lexicalization, a variety of lexicalization procedures have been developed that convert contextfree grammars (CFGs) into equivalent
Lexicalized ContextFree Grammar: A CubicTime Parsable, Lexicalized Normal Form for ContextFree Grammar That Preserves Tree Structure
, 1993
"... Lexicalized contextfree grammar (LCFG) is a treebased formalism that makes use of both tree substitution and a restricted form of tree adjunction. Because of its use of adjunction, LCFG allows sufficient freedom in the way derivations can be performed that lexicalization of contextfree grammar ..."
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Cited by 7 (4 self)
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Lexicalized contextfree grammar (LCFG) is a treebased formalism that makes use of both tree substitution and a restricted form of tree adjunction. Because of its use of adjunction, LCFG allows sufficient freedom in the way derivations can be performed that lexicalization of contextfree
Semantics of ContextFree Languages
 In Mathematical Systems Theory
, 1968
"... "Meaning " may be assigned to a string in a contextfree language by defining "attributes " of the symbols in a derivation tree for that string. The attributes can be defined by functions associated with each production in the grammar. This paper examines the implications of th ..."
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Cited by 559 (0 self)
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"Meaning " may be assigned to a string in a contextfree language by defining "attributes " of the symbols in a derivation tree for that string. The attributes can be defined by functions associated with each production in the grammar. This paper examines the implications
An Efficient ContextFree Parsing Algorithm
, 1970
"... A parsing algorithm which seems to be the most efficient general contextfree algorithm known is described. It is similar to both Knuth's LR(k) algorithm and the familiar topdown algorithm. It has a time bound proportional to n 3 (where n is the length of the string being parsed) in general; i ..."
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Cited by 794 (0 self)
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; it has an n 2 bound for unambiguous grammars; and it runs in linear time on a large class of grammars, which seems to include most practical contextfree programming language grammars. In an empirical comparison it appears to be superior to the topdown and bottomup algorithms studied by Griffiths
Statistical Parsing with a Contextfree Grammar and Word Statistics
, 1997
"... We describe a parsing system based upon a language model for English that is, in turn, based upon assigning probabilities to possible parses for a sentence. This model is used in a parsing system by finding the parse for the sentence with the highest probability. This system outperforms previou ..."
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Cited by 410 (18 self)
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explain their relative performance. Introduction We present a statistical parser that induces its grammar and probabilities from a handparsed corpus (a treebank). Parsers induced from corpora are of interest both as simply exercises in machine learning and also because they are often the best parsers
Principles and implementation of deductive parsing
 JOURNAL OF LOGIC PROGRAMMING
, 1995
"... We present a system for generating parsers based directly on the metaphor of parsing as deduction. Parsing algorithms can be represented directly as deduction systems, and a single deduction engine can interpret such deduction systems so as to implement the corresponding parser. The method generaliz ..."
Verb Semantics And Lexical Selection
, 1994
"... ... structure. As Levin has addressed (Levin 1985), the decomposition of verbs is proposed for the purposes of accounting for systematic semanticsyntactic correspondences. This results in a series of problems for MT systems: inflexible verb sense definitions; difficulty in handling metaphor and new ..."
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Cited by 520 (4 self)
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and new usages; imprecise lexical selection and insufficient system coverage. It seems one approach is to apply probability methods and statistical models for some of these problems. However, the question reminds: has PSR exhausted the potential of the knowledgebased approach? If not, are there any
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