Results 1  10
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18
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 62 (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 59 (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
Robust probabilistic predictive syntactic processing: Motivations, models, and applications. Doctoral dissertation, Brown University. (UMI: AAT 3006783
 Carnegie Mellon University
, 2001
"... 2001 This thesis by Brian E. Roark is accepted in its present form by ..."
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Cited by 12 (0 self)
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2001 This thesis by Brian E. Roark is accepted in its present form by
Parsing linear contextfree rewriting systems
 In Ninth International Workshop on Parsing Technologies, IWPT’05. Craig
, 2005
"... We describe four different parsing algorithms for Linear ContextFree Rewriting Systems (VijayShanker et al., 1987). The algorithms are described as deduction systems, and possible optimizations are discussed. The only parsing algorithms presented for linear contextfree rewriting systems (LCFRS; Vi ..."
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Cited by 9 (1 self)
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We describe four different parsing algorithms for Linear ContextFree Rewriting Systems (VijayShanker et al., 1987). The algorithms are described as deduction systems, and possible optimizations are discussed. The only parsing algorithms presented for linear contextfree rewriting systems (LCFRS; VijayShanker et al., 1987) and the equivalent formalism multiple contextfree grammar (MCFG; Seki et al., 1991) are extensions of the CKY algorithm (Younger, 1967), more designed for their theoretical interest, and not for practical purposes. The reason for this could be that there are not many implementations of these grammar formalisms. However, since a very important subclass of the Grammatical Framework (Ranta, 2004) is equivalent to LCFRS/MCFG (Ljunglöf, 2004a; Ljunglöf, 2004b), there is a need for practical parsing algorithms. In this paper we describe four different parsing algorithms for Linear ContextFree Rewriting Systems. The algorithms are described as deduction systems, and possible optimizations are discussed. 1 Introductory definitions A record is a structure Γ = {r1 = a1;...; rn = an}, where all ri are distinct. That this can be seen as a set of featurevalue pairs. This means that we can define a simple version of record unification Γ1 ⊔ Γ2 as the union Γ1∪Γ2, provided that there is no r such that Γ1.r ̸ = Γ2.r. We sometimes denote a sequence X1,..., Xn by the more compact ⃗ X. To update the ith record in a list of records, we write ⃗Γ[i: = Γ]. To substitute a variable Bk for a record Γk in any data structure Γ, we write
Parsing Schemata and Correctness of Parsing Algorithms
 Theoretical Computer Science
, 1998
"... Parsing schemata provide a highlevel formal description of parsers. These can be used, among others, as an intermediate level of abstraction for deriving the formal correctness of a parser. A parser is correct if it duely implements a parsing schema that is known to be correct. In this paper it is ..."
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Cited by 8 (0 self)
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Parsing schemata provide a highlevel formal description of parsers. These can be used, among others, as an intermediate level of abstraction for deriving the formal correctness of a parser. A parser is correct if it duely implements a parsing schema that is known to be correct. In this paper it is discussed how the correctness of a parsing schema can be proven and how parsing schemata relate to some wellknown classes of parsers, viz. chart parsers and LRtype parsers.
Probabilistic parsing strategies
 In 42nd Annual Meeting of the Association for Computational Linguistics
, 2004
"... We present new results on the relation between purely symbolic contextfree parsing strategies and their probabilistic counterparts. Such parsing strategies are seen as constructions of pushdown devices from grammars. We show that preservation of probability distribution is possible under two condi ..."
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Cited by 6 (1 self)
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We present new results on the relation between purely symbolic contextfree parsing strategies and their probabilistic counterparts. Such parsing strategies are seen as constructions of pushdown devices from grammars. We show that preservation of probability distribution is possible under two conditions, viz. the correctprefix property and the property of strong predictiveness. These results generalize existing results in the literature that were obtained by considering parsing strategies in isolation. From our general results we also derive negative results on socalled generalized LR parsing. 1
LR Parsing for Conjunctive Grammars
 Grammars
, 2002
"... The Generalized LR parsing algorithm for contextfree grammars, introduced by Tomita in 1986, is a polynomialtime implementation of nondeterministic LR parsing that uses graphstructured stack to represent the contents of the nondeterministic parser's pushdown for all possible branches of comp ..."
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Cited by 4 (3 self)
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The Generalized LR parsing algorithm for contextfree grammars, introduced by Tomita in 1986, is a polynomialtime implementation of nondeterministic LR parsing that uses graphstructured stack to represent the contents of the nondeterministic parser's pushdown for all possible branches of computation at a single computation step. It has been specifically developed as a solution for practical parsing tasks arising in computational linguistics, and indeed has proved itself to be very suitable for natural language processing.
Survey of Parallel ContextFree Parsing Techniques
, 1997
"... This report describes research done in the context of a subproject of the HPCN project IMPACT. The IMPACT project is headed by the ING bank and is founded by the organization for High Performance Computing and Networking (HPCN). The aim of the specific subproject, in the context of which this report ..."
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Cited by 4 (3 self)
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This report describes research done in the context of a subproject of the HPCN project IMPACT. The IMPACT project is headed by the ING bank and is founded by the organization for High Performance Computing and Networking (HPCN). The aim of the specific subproject, in the context of which this report has been written, is to develop (techniques for) natural language interfaces to information resources, focusing on the use of highperformance computers to achieve acceptable response times. This report is part of the "Parallel Parsing I" research topic. IMPACTNLI19971 ii Preface IMPACT IMPACTNLI19971 IMPACT iii Contents Preface i 1 Introduction 1 2 Basics 3