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Several methods are discussed that construct a nite automaton given a context-free grammar , including both methods that lead to subsets and those that lead to supersets of the original context-free language. Some of these methods of regular approximation are new, and some others are presented here in a more reened form with respect to existing literature.… (More)
A new upper bound is presented for the computational complexity of the parsing problem for TAGs, under the constraint that input is read from left to right in such a way that errors in the input are observed as soon as possible, which is called the "correct-prefix property." The former upper bound, O(n9), is now improved to O(n6), which is the same as that… (More)
We show that for each context-free grammar a new grammar can be constructed that generates a regular language. This construction differs from some existing methods of approximation in that use of a pushdown automaton is avoided. This allows better insight into how the generated language is affected.
We discuss weighted deductive parsing and consider the problem of finding the derivation with the lowest weight. We show that Knuth's generalization of Dijkstra's algorithm for the shortest-path problem offers a general method to solve this problem. Our approach is modular in the sense that Knuth's algorithm is formulated independently from the weighted… (More)
We consider the problem of parsing non-recursive context-free grammars, i.e., context-free grammars that generate finite languages. In natural language processing , this problem arises in several areas of application, including natural language generation, speech recognition and machine translation. We present two tabu-lar algorithms for parsing of… (More)
We present an algorithm for approximating context-free languages with regular languages. The algorithm is based on a simple transformation that applies to any context-free grammar and guarantees that the result can be compiled into a finite automaton. The resulting grammar contains at most one new nonterminal for any nonterminal symbol of the input grammar.… (More)
We investigate the problem of computing the partition function of a prob-abilistic context-free grammar, and consider a number of applicable methods. Particular attention is devoted to PCFGs that result from the intersection of another PCFG and a finite automaton. We report experiments involving the Wall Street Journal corpus.
We show how techniques known from gen-erMized LR parsing can be applied to left-corner parsing. The ~esulting parsing algorithm for context-free grammars has some advantages over generalized LR parsing: the sizes and generation times of the parsers are smaller, the produced output is more compact, and the basic parsing technique can more easily be adapted… (More)