Grammars are traditionally used to recognize or parse sentences in a language, but they can also be used to generate sentences. In grammar-based test generation (GBTG), context-free grammars are used to generate sentences that are interpreted as test cases. A generator reads a grammar G and generates L(G), the language accepted by the grammar. Often L(G) is so large that it is not practical to ...

It is often assumed that ‘grounded’ learning tasks are beyond the scope of grammatical inference techniques. In this paper, we show that the grounded task of learning a semantic parser from ambiguous training data as discussed in Kim and Mooney (2010) can be reduced to a Probabilistic Context-Free Grammar learning task in a way that gives state of the art results. We further show that additiona...

Structural and thermodynamic properties of hydrogen molecular clusters formed around an atomic or molecular cation are examined. The shell distribution of H2 molecules and the size of the clusters are discussed. The Bloom-Margenau model for predicting the number of neutral molecules that could bind to a cation core is investigated and its limitations are illustrated using the Li(H2)k clusters a...

In this paper, we present a method which, in practice, allows to use parsers for languages defined by very large context-free grammars (over a million symbol occurrences). The idea is to split the parsing process in two passes. A first pass computes a sub-grammar which is a specialized part of the large grammar selected by the input text and various filtering strategies. The second pass is a tr...