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Probabilistic context-free grammar. Grammar theory to model symbol strings originated from work in computational linguistics aiming to understand the structure of natural languages. [1] [2] [3] Probabilistic context free grammars ( PCFGs) have been applied in probabilistic modeling of RNA structures almost 40 years after they were introduced in ...
e. A stochastic grammar ( statistical grammar) is a grammar framework with a probabilistic notion of grammaticality : Stochastic context-free grammar. Statistical parsing. Data-oriented parsing. Hidden Markov model. Estimation theory. The grammar is realized as a language model. Allowed sentences are stored in a database together with the ...
In formal language theory, a context-free grammar ( CFG) is a formal grammar whose production rules can be applied to a nonterminal symbol regardless of its context. In particular, in a context-free grammar, each production rule is of the form. with a single nonterminal symbol, and a string of terminals and/or nonterminals ( can be empty).
is the size of the CNF grammar. In computer science, the Cocke–Younger–Kasami algorithm (alternatively called CYK, or CKY) is a parsing algorithm for context-free grammars published by Itiroo Sakai in 1961. [1] [2] The algorithm is named after some of its rediscoverers: John Cocke, Daniel Younger, Tadao Kasami, and Jacob T. Schwartz.
The Earley parser executes in cubic time in the general case (), where n is the length of the parsed string, quadratic time for unambiguous grammars (), [4] and linear time for all deterministic context-free grammars. It performs particularly well when the rules are written left-recursively.
In his 2014 book titled The Language Myth: Why Language Is Not An Instinct, British cognitive linguist and digital communication technologist Vyvyan Evans mapped out the role of probabilistic context-free grammar (PCFG) in enabling NLP to model cognitive patterns and generate human like language. [112] [113]
In formal language theory, a context-free grammar, G, is said to be in Chomsky normal form (first described by Noam Chomsky) [ 1] if all of its production rules are of the form: [ 2][ 3] A → BC, or. A → a, or. S → ε,
One way to do this is by using a probabilistic context-free grammar (PCFG) which has a probability of each constituency rule, and modifying CKY to maximise probabilities when parsing bottom-up. A further modification is the lexicalized PCFG, which assigns a head to each constituent and encodes rule for each lexeme in that head slot.
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