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Context-sensitive grammar

About: Context-sensitive grammar is a research topic. Over the lifetime, 1938 publications have been published within this topic receiving 45911 citations. The topic is also known as: CSG.


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Proceedings ArticleDOI
24 Aug 1993
TL;DR: A new class of positional grammars is characterized, the extended pLALR Grammars, which can be translated into traditional LALR context free grammar with positional actions, and properly contains the class of pSLR grammARS for which a Yacc implementation has already been given.
Abstract: While in a string grammar the only possible spatial relation is the string concatenation, in a positional grammar other spatial relations can be defined and then used for describing high dimensional languages. We characterize a new class of positional grammars, the extended pLALR grammars, which can be translated into traditional LALR context free grammars with positional actions. A positional action is a procedure implementing a spatial relation. In this way, the parser for an extended pLALR language can be generated automatically by the tool Yacc with no more effort. Moreover, we show that the class of extended pLALR grammars properly contains the class of pSLR grammars for which a Yacc implementation has already been given. >

13 citations

Journal ArticleDOI
TL;DR: This work considers simulating finite automata (both deterministic and nondeterministic) with context-free grammars in Chomsky normal form (CNF), and shows that any unary DFA with n states can be simulated by a CNF grammar with O(n1/3) variables.

13 citations

Proceedings Article
11 Aug 1986
TL;DR: The reasoning behind the selection and design of a parser for the Lingo project on natural language interfaces at MCC is presented, and a variant of chart parsing that uses a best-first control structure managed on an agenda as a control structure is chosen.
Abstract: This paper presents the reasoning behind the selection and design of a parser for the Lingo project on natural language interfaces at MCC. The major factors in the selection of the parsing algorithm were the choices of having a syntactically based grammar, using a graph-unification-based representation language, using Combinatory Categorial Grammars, and adopting a one-to-many mapping from syntactic bracketings to semantic representations in certain cases. The algorithm chosen is a variant of chart parsing that uses a best-first control structure managed on an agenda. It offers flexibility for these natural language processing applications by allowing for best-first tuning of parsing for particular grammars in particular domains while at the same time allowing exhaustive enumeration of the search space during grammar development. Efficiency advantages of this choice for graph-unification-based representation languages are outlined, as well as a number of other advantages that acrue to this approach by virtue of its use of an agenda as a control structure. We also mention two useful refinements to the basic best-first chart parsing algorithm that have been implemented in the Lingo project.

13 citations

Book ChapterDOI
20 Sep 2009
TL;DR: In this article, the global grammar constraint over restricted classes of context free grammars like deterministic and unambiguous context-free grammar was investigated, and it was shown that detecting disentailment for the GRAMMAR constraint in these cases is as hard as parsing an unrestricted context free grammar.
Abstract: We investigate the global GRAMMAR constraint over restricted classes of context free grammars like deterministic and unambiguous context-free grammars. We show that detecting disentailment for the GRAMMAR constraint in these cases is as hard as parsing an unrestricted context free grammar.We also consider the class of linear grammars and give a propagator that runs in quadratic time. Finally, to demonstrate the use of linear grammars, we show that a weighted linear GRAMMAR constraint can efficiently encode the EDITDISTANCE constraint, and a conjunction of the EDITDISTANCE constraint and the REGULAR constraint.

13 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202311
202212
20211
20204
20191
20181