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63
An Efficient Probabilistic ContextFree Parsing Algorithm that Computes Prefix Probabilities
 Computational Linguistics
, 2002
"... this article can compute solutions to all four of these problems in a single flamework, with a number of additional advantages over previously presented isolated solutions ..."
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Cited by 186 (5 self)
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this article can compute solutions to all four of these problems in a single flamework, with a number of additional advantages over previously presented isolated solutions
Gemini: A Natural Language System For SpokenLanguage Understanding
 In Proceedings of the ThirtyFirst Annual Meeting of the Association for Computational Linguistics
, 1993
"... This paper describes the details of the system, and includes relevant measurements of size, efficiency, and performance of each of its components ..."
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Cited by 142 (34 self)
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This paper describes the details of the system, and includes relevant measurements of size, efficiency, and performance of each of its components
Parsing InsideOut
, 1998
"... Probabilistic ContextFree Grammars (PCFGs) and variations on them have recently become some of the most common formalisms for parsing. It is common with PCFGs to compute the inside and outside probabilities. When these probabilities are multiplied together and normalized, they produce the probabili ..."
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Cited by 82 (2 self)
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Probabilistic ContextFree Grammars (PCFGs) and variations on them have recently become some of the most common formalisms for parsing. It is common with PCFGs to compute the inside and outside probabilities. When these probabilities are multiplied together and normalized, they produce the probability that any given nonterminal covers any piece of the input sentence. The traditional use of these probabilities is to improve the probabilities of grammar rules. In this thesis we show that these values are useful for solving many other problems in Statistical Natural Language Processing. We give a framework for describing parsers. The framework generalizes the inside and outside values to semirings. It makes it easy to describe parsers that compute a wide variety of interesting quantities, including the inside and outside probabilities, as well as related quantities such as Viterbi probabilities and nbest lists. We also present three novel uses for the inside and outside probabilities. T...
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 77 (1 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 grammars. However, these procedures typically suffer from one or more of the following problems
Computation of the probability of initial substring generation by stochastic contextfree grammars
 Computational Linguistics
, 1991
"... Speech recognition language models are based on probabilities P(Wk+I = v [ WlW2~..., Wk) that the next word Wk+l will be any particular word v of the vocabulary, given that the word sequence Wl, w2,..., Wk is hypothesized to have been uttered in the past. If probabilistic contextfree grammars are t ..."
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Cited by 76 (0 self)
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Speech recognition language models are based on probabilities P(Wk+I = v [ WlW2~..., Wk) that the next word Wk+l will be any particular word v of the vocabulary, given that the word sequence Wl, w2,..., Wk is hypothesized to have been uttered in the past. If probabilistic contextfree grammars are to be used as the basis of the language model, it will be necessary to compute the probability that successive application of the grammar rewrite rules (beginning with the sentence start symbol s) produces a word string whose initial substring is an arbitrary sequence wl, w2,..., Wk+l. In this paper we describe a new algorithm that achieves the required computation in at most a constant times k3steps. 1.
Semiring Parsing
 Computational Linguistics
, 1999
"... this paper is that all five of these commonly computed quantities can be described as elements of complete semirings (Kuich 1997). The relationship between grammars and semirings was discovered by Chomsky and Schtitzenberger (1963), and for parsing with the CKY algorithm, dates back to Teitelbaum ( ..."
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Cited by 64 (1 self)
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this paper is that all five of these commonly computed quantities can be described as elements of complete semirings (Kuich 1997). The relationship between grammars and semirings was discovered by Chomsky and Schtitzenberger (1963), and for parsing with the CKY algorithm, dates back to Teitelbaum (1973). A complete semiring is a set of values over which a multiplicative operator and a commutative additive operator have been defined, and for which infinite summations are defined. For parsing algorithms satisfying certain conditions, the multiplicative and additive operations of any complete semiring can be used in place of/x and , and correct values will be returned. We will give a simple normal form for describing parsers, then precisely define complete semirings, and the conditions for correctness
A generalized CYK algorithm for parsing stochastic CFG
, 1998
"... We present a bottomup parsing algorithm for stochastic contextfree grammars that is able (1) to deal with multiple interpretations of sentences containing compound words; (2) to extract Nmost probable parses in O(n 3 ) and compute at the same time all possible parses of any portion of the inpu ..."
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Cited by 57 (11 self)
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We present a bottomup parsing algorithm for stochastic contextfree grammars that is able (1) to deal with multiple interpretations of sentences containing compound words; (2) to extract Nmost probable parses in O(n 3 ) and compute at the same time all possible parses of any portion of the input sequence with their probabilities; (3) to deal with #out of vocabulary# words. Explicitly extracting all the parse trees associated to a given input sentence depends on the complexity of the grammar, but even in the case where this number is exponential in n, the chart used by the algorithm for the representation is of O(n 2 ) space complexity. 1 Introduction This article presents CYK+, a bottomup parsing algorithm for stochastic contextfree grammars that is able: 1. to deal multiple interpretations of sentences containing compound words; 2. to extract Nmost probable parses in O(n 3 ) and compute at the same time all possible parses of any portion of the input sequence with their p...
Parsing and hypergraphs
 In IWPT
, 2001
"... While symbolic parsers can be viewed as deduction systems, this view is less natural for probabilistic parsers. We present a view of parsing as directed hypergraph analysis which naturally covers both symbolic and probabilistic parsing. We illustrate the approach by showing how a dynamic extension o ..."
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Cited by 56 (3 self)
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While symbolic parsers can be viewed as deduction systems, this view is less natural for probabilistic parsers. We present a view of parsing as directed hypergraph analysis which naturally covers both symbolic and probabilistic parsing. We illustrate the approach by showing how a dynamic extension of Dijkstra’s algorithm can be used to construct a probabilistic chart parser with an Ç Ò time bound for arbitrary PCFGs, while preserving as much of the flexibility of symbolic chart parsers as allowed by the inherent ordering of probabilistic dependencies. 1
Bilexical Grammars And Their CubicTime Parsing Algorithms
 IN: NEW DEVELOPMENTS IN NATURAL LANGUAGE PARSING
, 2000
"... This chapter introduces weighted bilexical grammars, a formalism in which individual lexical items, such as verbs and their arguments, can have idiosyncratic selectional influences on each other. Such ‘bilexicalism ’ has been a theme of much current work in parsing. The new formalism can be used t ..."
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Cited by 51 (1 self)
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This chapter introduces weighted bilexical grammars, a formalism in which individual lexical items, such as verbs and their arguments, can have idiosyncratic selectional influences on each other. Such ‘bilexicalism ’ has been a theme of much current work in parsing. The new formalism can be used to describe bilexical approaches to both dependency and phrasestructure grammars, and a slight modification yields link grammars. Its scoring approach is compatible with a wide variety of probability models. The obvious parsing algorithm for bilexical grammars (used by most previous authors) takes time O(n^5). A more efficient O(n³) method is exhibited. The new algorithm has been implemented and used in a large parsing experiment (Eisner, 1996b). We also give a useful extension to the case where the parser must undo a stochastic transduction that has altered the input.