Generalized Lr Parsing For General Context Free Grammars
Download Generalized Lr Parsing For General Context Free Grammars PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Generalized Lr Parsing For General Context Free Grammars book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Generalized LR Parsing
Author: Masaru Tomita
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-12-06
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.
Generalized LR Parsing for General Context-free Grammars
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."
Advanced Visual Interfaces - Proceedings Of The International Workshop Avi '92
This volume brings together papers by experts in different areas of computer science, who have a common interest in the design and management of visual interfaces. Since cognitive science and metaphor analysis prove useful for understanding the basic mechanisms which allow visual interfaces to be easy to learn and use, these topics are also featured. Other areas focused on are: visual languages, visual database systems, intelligent agents for system interaction, graphical and pictorial communication tools, multimedia environments and specific technological developments.