Search results
Results from the WOW.Com Content Network
Chiang [1] gives the Chinese/English example: X → (yu X 1 you X 2, have X 2 with X 1) This rule indicates that an X phrase can be formed in Chinese with the structure "yu X 1 you X 2", where X 1 and X 2 are variables standing in for subphrases; and that the corresponding structure in English is "have X 2 with X 1" where X 1 and X 2 are ...
To do so technically would require a more sophisticated grammar, like a Chomsky Type 1 grammar, also termed a context-sensitive grammar. However, parser generators for context-free grammars often support the ability for user-written code to introduce limited amounts of context-sensitivity.
An extended context-free grammar (or regular right part grammar) is one in which the right-hand side of the production rules is allowed to be a regular expression over the grammar's terminals and nonterminals. Extended context-free grammars describe exactly the context-free languages.
A lookahead LR parser (LALR) generator is a software tool that reads a context-free grammar (CFG) and creates an LALR parser which is capable of parsing files written in the context-free language defined by the CFG. LALR parsers are desirable because they are very fast and small in comparison to other types of parsers.
In computer science, the Earley parser is an algorithm for parsing strings that belong to a given context-free language, though (depending on the variant) it may suffer problems with certain nullable grammars. [1]
Generalized context-free grammar (GCFG) is a grammar formalism that expands on context-free grammars by adding potentially non-context-free composition functions to rewrite rules. [1] Head grammar (and its weak equivalents) is an instance of such a GCFG which is known to be especially adept at handling a wide variety of non-CF properties of ...
Sequitur (or Nevill-Manning–Witten algorithm) is a recursive algorithm developed by Craig Nevill-Manning and Ian H. Witten in 1997 [1] that infers a hierarchical structure (context-free grammar) from a sequence of discrete symbols. The algorithm operates in linear space and time. It can be used in data compression software applications. [2]
To compress a data sequence =, a grammar-based code transforms into a context-free grammar . The problem of finding a smallest grammar for an input sequence ( smallest grammar problem ) is known to be NP-hard, [ 2 ] so many grammar-transform algorithms are proposed from theoretical and practical viewpoints.