Drit Parser A Generalized Lr Parsing Algorithm Using Dot Reverse System

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Drit Parser A Generalized Lr Parsing Algorithm Using Dot Reverse System

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Author : Hozumi Tanaka
language : en
Publisher:
Release Date : 1992

Drit Parser A Generalized Lr Parsing Algorithm Using Dot Reverse System written by Hozumi Tanaka and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with categories.

Icot Journal

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Author :
language : en
Publisher:
Release Date : 1991

Icot Journal written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991 with Electronic digital computers categories.

Drit Parser A Generalized Lr Parsing Algorithm Using Dot Reverse Item

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Author : Shin Sedai Konpyūta Gijutsu Kaihatsu Kikō (Japan)
language : en
Publisher:
Release Date : 1992

Drit Parser A Generalized Lr Parsing Algorithm Using Dot Reverse Item written by Shin Sedai Konpyūta Gijutsu Kaihatsu Kikō (Japan) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with categories.

Drit Parser

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Author : Hozumi Tanaka
language : en
Publisher:
Release Date : 1992

Drit Parser written by Hozumi Tanaka and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Algorithms categories.

Abstract: "We have developed a new generalized LR parser called Drit parser. The parsing algorithm is based on Kipps recognition algorithm but it creates the parsing results as a set of dot reverse items (drits). The structure of drits is symmetric to the one of Earley's items. It is possible to form parsing trees from a set of drits created after the completion of parsing. This makes Kipps recognition algorithm a practical CFG parser. In order to build a Drit parser, some modifications in the original version of Kipps recognition algorithm are required. The time and space complexity of Drit parser is in the order of n3 and n2 respectively, since Drit parser is based on Kipps recognition algorithm. We will conclude that Drit parser has both the advantages of Earley's and Tomita's parsing algorithm."

Generalized Lr Parsing

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Author : Masaru Tomita
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Generalized Lr Parsing written by Masaru Tomita and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.

The Generalized LR parsing algorithm (some call it "Tomita's algorithm") was originally developed in 1985 as a part of my Ph.D thesis at Carnegie Mellon University. When I was a graduate student at CMU, I tried to build a couple of natural language systems based on existing parsing methods. Their parsing speed, however, always bothered me. I sometimes wondered whether it was ever possible to build a natural language parser that could parse reasonably long sentences in a reasonable time without help from large mainframe machines. At the same time, I was always amazed by the speed of programming language compilers, because they can parse very long sentences (i.e., programs) very quickly even on workstations. There are two reasons. First, programming languages are considerably simpler than natural languages. And secondly, they have very efficient parsing methods, most notably LR. The LR parsing algorithm first precompiles a grammar into an LR parsing table, and at the actual parsing time, it performs shift-reduce parsing guided deterministically by the parsing table. So, the key to the LR efficiency is the grammar precompilation; something that had never been tried for natural languages in 1985. Of course, there was a good reason why LR had never been applied for natural languages; it was simply impossible. If your context-free grammar is sufficiently more complex than programming languages, its LR parsing table will have multiple actions, and deterministic parsing will be no longer possible.

A Computer Language Transformation System Capable Of Generalized Context Dependent Parsing

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Author : Adrian Thurston
language : en
Publisher:
Release Date : 2008

A Computer Language Transformation System Capable Of Generalized Context Dependent Parsing written by Adrian Thurston and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with categories.

Source transformation systems are special-purpose programming languages, or in some cases suites of languages, that are designed for the analysis and transformation of computer languages. They enable rapid prototyping of programming languages, source code renovation, language-to-language translation, design recovery, and other custom analysis techniques. With the emergence of these systems a serious problem is evident: expressing a parser for common computer languages is sometimes very difficult. Source transformation systems employ generalized parsing algorithms, and while these are well suited for the kind of agile parsing techniques in use by transformation practitioners, they are not well suited for parsing languages that are context-dependent. Traditional deterministic parser generators do not stumble in this area, but they sacrifice the generalized parsing abilities that transformation systems depend on. When it is hard to get the input into the system as a correct and accurate parse tree the utility of the unified transformation environment is degraded and more ad hoc approaches become attractive for processing input. This thesis is about the design of a new computer language transformation system with a focus on enhancing the parsing system to support generalized context-dependent parsing. We argue for the use of backtracking LR as the generalized parsing algorithm. We present an enhancement to backtracking LR that allows us to control the parsing of an ambiguous grammar by ordering the productions of the grammar definitions. We add a grammar-dependent lexical solution and integrate it with our ordered choice parsing strategy. We design a transformation language that is closer to general-purpose programming languages, yet enables common transformation techniques. We add semantic actions to our backtracking LR parsing engine and encourage the modification of global state in support of context-dependent parsing. We introduce semantic undo actions for reverting changes to global state during backtracking, thereby enabling generalized context-dependent parsing. Finally, we free the user from having to write undo actions by employing automatic reverse execution. The resulting system allows a wider variety of computer languages to be analyzed. By focusing on improving parsing abilities and moving to a transformation language that resembles general-purpose languages, we aim to extend the transformation paradigm to allow greater use by practitioners who face an immediate need to parse, analyze and transform computer languages.

Generalized Lr Parsing For General Context Free Grammars

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Author : J. Rekers
language : en
Publisher:
Release Date : 1991

Generalized Lr Parsing For General Context Free Grammars written by J. Rekers and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991 with Natural language processing (Computer science) categories.

Abstract: "Which methods for parser generation and parsing are best suited for an interactive development system of syntax definitions? In this chapter we argue that a Generalized LR parsing algorithm is the best choice. We present an enhanced version of Tomita's GLR algorithm, and compare its efficiency with two competitors, YACC and Earley's algorithm."

Recent Advances In Parsing Technology

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Author : H. Bunt
language : en
Publisher: Springer Science & Business Media
Release Date : 1996-08-31

Recent Advances In Parsing Technology written by H. Bunt and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-08-31 with Computers categories.

In Marcus (1980), deterministic parsers were introduced. These are parsers which satisfy the conditions of Marcus's determinism hypothesis, i.e., they are strongly deterministic in the sense that they do not simulate non determinism in any way. In later work (Marcus et al. 1983) these parsers were modified to construct descriptions of trees rather than the trees them selves. The resulting D-theory parsers, by working with these descriptions, are capable of capturing a certain amount of ambiguity in the structures they build. In this context, it is not clear what it means for a parser to meet the conditions of the determinism hypothesis. The object of this work is to clarify this and other issues pertaining to D-theory parsers and to provide a framework within which these issues can be examined formally. Thus we have a very narrow scope. We make no ar guments about the linguistic issues D-theory parsers are meant to address, their relation to other parsing formalisms or the notion of determinism in general. Rather we focus on issues internal to D-theory parsers themselves.

Efficient Parsing For Natural Language

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Author : Masaru Tomita
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-17

Efficient Parsing For Natural Language written by Masaru Tomita and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-17 with Computers categories.

Parsing Efficiency is crucial when building practical natural language systems. 'Ibis is especially the case for interactive systems such as natural language database access, interfaces to expert systems and interactive machine translation. Despite its importance, parsing efficiency has received little attention in the area of natural language processing. In the areas of compiler design and theoretical computer science, on the other hand, parsing algorithms 3 have been evaluated primarily in terms of the theoretical worst case analysis (e.g. lXn», and very few practical comparisons have been made. This book introduces a context-free parsing algorithm that parses natural language more efficiently than any other existing parsing algorithms in practice. Its feasibility for use in practical systems is being proven in its application to Japanese language interface at Carnegie Group Inc., and to the continuous speech recognition project at Carnegie-Mellon University. This work was done while I was pursuing a Ph.D degree at Carnegie-Mellon University. My advisers, Herb Simon and Jaime Carbonell, deserve many thanks for their unfailing support, advice and encouragement during my graduate studies. I would like to thank Phil Hayes and Ralph Grishman for their helpful comments and criticism that in many ways improved the quality of this book. I wish also to thank Steven Brooks for insightful comments on theoretical aspects of the book (chapter 4, appendices A, B and C), and Rich Thomason for improving the linguistic part of tile book (the very beginning of section 1.1).

Implementation And Evaluation Of Yet Another Generalized Lr Parsing Algorithm

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Author : K. G. Suresh
language : en
Publisher:
Release Date : 1992

Implementation And Evaluation Of Yet Another Generalized Lr Parsing Algorithm written by K. G. Suresh and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Algorithms categories.

Abstract: "This paper presents an implementation and evaluation of our new generalized LR parsing algorithm called Yet Another Generalized LR parsing algorithm (YAGLR). In its original version, YAGLR uses graph- structured stack (GSS) whereas in the preliminary implementation we use tree-structured stack (trss). The merge operation of stack in our algorithm is deeper than top nodes and is effective. Hence the parsing time and the reduction in memory space are remarkable. Due to effective merge operations, even when using trss, we retain packed nature of GSS and thus not causing heavy loss of memory space. Through reduce actions, YAGLR creates items called drit which are symmetrically different from Earley's item. The advantages in creating drit are realized. Through our implementation, we practically prove that for a context-free grammar with reasonable size and complexity, YAGLR's parsing time is in the order of n3, where n is the length of an imput sentence. We conclude that YAGLR has the advantages of both Earley's and Tomita's algorithm."