Mark-Jan Nederhof

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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 re ned form with respect to existing literature.(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. Introduction In existing literature, a number of methods(More)
We argue that grammatical analysis is a viable alternative to concept spotting for processing spoken input in a practical spoken dialogue system. We discuss the structure of the grammar, and a model for robust parsing which combines linguistic sources of information and statistical sources of information. We discuss test results suggesting that grammatical(More)
As for algorithms in general, there are significant advantages to specifying parsing algorithms in a modular way (i.e., as the combination of subalgorithms). First, modular specifications often allow simpler implementations. Secondly, if otherwise seemingly distinct types of parser are described in a modular way, the common parts can often be more readily(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 how techniques known from generMized LR parsing can be applied to leftcorner 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 to(More)
In this paper we relate a number of parsing algorithms which have been developed in very different areas of parsing theory, and which include deterministic algorithms, tabular algorithms, and a parallel algorithm. We show that these algorithms are based on the same underlying ideas. By relating existing ideas, we hope to provide an opportunity to improve(More)