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Generalized LR Parsing (Paperback, Softcover reprint of the original 1st ed. 1991)
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Generalized LR Parsing (Paperback, Softcover reprint of the original 1st ed. 1991)
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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.
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