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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 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)

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)

We propose a modular design of tabular parsing algorithms for tree-adjoining languages. The modularity is made possible by a separation of the parsing strategy from the mechanism of tabulation. The parsing strategy is expressed in terms of the construction of a nondeterministic automaton from a grammar; three distinct types of automaton will be discussed.… (More)

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)

Several mathematical distances between probabilistic languages have been investigated in the literature, motivated by applications in language modeling, computational biology, syntactic pattern matching and machine learning. In most cases, only pairs of probabilistic regular languages were considered. In this paper we extend previous results to pairs of… (More)