The problem of inferring an agent’s intentions from her spatio-temporal behavior is called mobile intention recognition problem. Using formal grammars we can state these problems as parsing problems. We argue that context-free formalisms are not sufficient for important use cases. We introduce Spatially Constrained Tree-Adjoining Grammars which enrich TAGs with knowledge about the structure of ...

The paper describes an extensive experiment in inside-outside estimation of a lexicalized proba-bilistic context free grammar for German verb-final clauses. Grammar and formalism features which make the experiment feasible are described. Successive models are evaluated on precision and recall of phrase markup.

Modular grammatical formalisms provide an essential step towards improved grammar engineering practices. However, as we depart from traditional deterministic models, some intrinsic static checks are lost. The paper shows why grammar verification is necessary for reliable uses of context-free grammars (CFGs) and parsing expression grammars (PEGs) as modular syntax definitions. Simple conservativ...

We present a method for probabilistic parsing of German words. Our approach uses a morphological analyzer based on weighted finitestate transducers to segment words into lexical units and a probabilistic context free grammar trained on a manually created set of word trees for the parsing step.

This paper discusses the terminating derivation mode in cooperating distributed grammar systems where components are forbidding grammars instead of context-free grammars. Such systems are called forbidding cooperating distributed grammar systems, and it is demonstrated that the number of their components can be reduced to two without changing the generative power and that these systems are comp...

This paper investigates adapting a lexicalized probabilistic context-free grammar (PCFG) to a novel domain, using maximum a posteriori (MAP) estimation. The MAP framework is general enough to include some previous model adaptation approaches, such as corpus mixing in Gildea (2001), for example. Other approaches falling within this framework are more effective. In contrast to the results in Gild...

We propose the design of deterministic constituent parsers that choose parser actions according to the probabilities of parses of a given probabilistic context-free grammar. Several variants are presented. One of these deterministically constructs a parse structure while postponing commitment to labels. We investigate theoretical time complexities and report experiments.

We present a hierarchical chunk-to-string translation model, which can be seen as a compromise between the hierarchical phrasebased model and the tree-to-string model, to combine the merits of the two models. With the help of shallow parsing, our model learns rules consisting of words and chunks and meanwhile introduce syntax cohesion. Under the weighed synchronous context-free grammar defined ...

The application of Genetic Programming (GP) to the discovery of empirical laws most often suffers from two limitations. The first one is the size of the search space; the second one is the growth of non-coding segments, the introns, which exhausts the memory resources as GP evolution proceeds. These limitations are addressed by combining Genetic Programming and Stochastic Grammars. On one hand,...

A context-free e-free grammar with regular restrictions is a context-free £-free grammar G over which a context-free rule r or G is applicable on a string x only if x e y(r) where y(r) is a regular set. It is known from [1] that the context-free £-free grammars with regular restrictions are as powerful as Chomsky's grammars of the type 0. It is shown, that the same result holds for the grammars...