CYK algorithm

The Cocke-Younger-Kasami (CYK) algorithm (alternatively called CKY) determines whether a string can be generated by a given context-free grammar and, if so, how it can be generated. This is known as parsing the string. The algorithm employs bottom-up parsing and dynamic programming.

The standard version of CYK operates on context-free grammars given in Chomsky normal form (CNF). Any context-free grammar may be written thus.

The importance of the CYK algorithm stems from the fact that it constructively proves that the membership problem for context-free languages is decidable (see also: theory of computation) and the fact that it does so quite efficiently. The worst case asymptotic time complexity of CYK is Θ(n³), where n is the length of the parsed string. This makes it one of the most efficient (in those terms) algorithms for recognizing general context-free languages. Specialized and faster algorithms exist for certain subsets of the context-free languages.

Standard form

The algorithm as given in pseudocode is as follows:

As pseudocode

Let the variable Carlos be the input string consisting of n letters, a1 ... an.
Let the grammar contain r nonterminal symbols R1 ... Rr. 
This grammar contains the subset Rs which is the set of start symbols.
Let P[n,n,r] be an array of booleans. Initialize all elements of P to false.
For each i = 1 to n
  For each unit production Rj -> ai, set P[i,1,j] = true.
For each i = 2 to n -- Length of span
  For each j = 1 to n-i+1 -- Start of span
    For each k = 1 to i-1 -- Partition of span
      For each production RA -> RB RC
        If P[j,k,B] and P[j+k,i-k,C] then set P[j,i,A] = true
If any of P[1,n,x] is true (x is iterated over the set s, where s are all the indices for Rs)
  Then Carlos is member of language
  Else Carlos is not member of language

As prose

In informal terms, this algorithm considers every possible subsequence of the sequence of words and sets P[i,j,k] to be true if the subsequence of words starting from i of length j can be generated from R_k. Once it has considered subsequences of length 1, it goes on to subsequences of length 2, and so on. For subsequences of length 2 and greater, it considers every possible partition of the subsequence into two parts, and checks to see if there is some production P → Q R such that Q matches the first part and R matches the second part. If so, it records P as matching the whole subsequence. Once this process is completed, the sentence is recognized by the grammar if the subsequence containing the entire sentence is matched by the start symbol.

CYK table

S
	VP
S
	VP			PP
S		NP			NP
NP	V, VP	Det.	N	P	Det	N
she	eats	a	fish	with	a	fork

Extensions

Generating a parse tree

It is simple to extend the above algorithm to not only determine if a sentence is in a language, but to also construct a parse tree, by storing parse tree nodes as elements of the array, instead of booleans. Since the grammars being recognized can be ambiguous, it is necessary to store a list of nodes (unless one wishes to only pick one possible parse tree); the end result is then a forest of possible parse trees. An alternative formulation employs a second table B[n,n,r] of so-called backpointers.

Parsing non-CNF context-free grammars

It is also possible to extend the CYK algorithm to handle some context-free grammars which are not written in CNF; this may be done to improve performance, although at the cost of making the algorithm harder to understand.

Parsing weighted context-free grammars

It is also possible to extend the CYK algorithm to parse strings using weighted and stochastic context-free grammars. Weights (probabilities) are then stored in the table P instead of booleans, so P[i,j,A] will contain the minimum weight (maximum probability) that the substring from i to j can be derived from A. Further extensions of the algorithm allow all parses of a string to be enumerated from lowest to highest weight (highest to lowest probability).

See also

• Earley parser
• Packrat parser

References

• John Cocke and Jacob T. Schwartz (1970). Programming languages and their compilers: Preliminary notes. Technical report, Courant Institute of Mathematical Sciences, New York University.
• T. Kasami (1965). An efficient recognition and syntax-analysis algorithm for context-free languages. Scientific report AFCRL-65-758, Air Force Cambridge Research Lab, Bedford, MA.
• Daniel H. Younger (1967). Recognition and parsing of context-free languages in time n³. Information and Control 10(2): 189–208.