This article describes a number of log-linear parsing models for an automatically extracted
lexicalized grammar. The models are “full” parsing models in the sense that probabilities are …

Natural language analysis systems which combine knowledge-based and corpus-based
methods are now becoming accurate enough to be used in various applications. We …

Probabilistic modeling of lexicalized grammars is difficult because these grammars exploit
complicated data structures, such as typed feature structures. This prevents us from applying …

We present a stochastic parsing system consisting of a Lexical-Functional Grammar (LFG), a
constraint-based parser and a stochastic disambiguation model. We report on the results of …

This paper describes the role of supertagging in a wide-coverage CCG parser which uses a
log-linear model to select an analysis. The supertagger reduces the derivation space over …

This paper reports the development of loglinear models for the disambiguation in wide-
coverage HPSG parsing. The estimation of log-linear models requires high computational …

This paper describes log-linear parsing models for Combinatory Categorial Grammar
(CCG). Log-linear models can easily encode the long-range dependencies inherent in …

Het doel van de computationele taalkunde is het maken van systemen die in staat zijn
natuurlijke taal te begrijpen en te produceren, net zoals wij mensen dat doen. Het maken …

We present a hybrid MT architecture, combining state-of-the-art linguistic processing with
advanced stochastic techniques. Grounded in a theoretical reflection on the division of labor …

Probabilistic analogues of regular and context-free grammars are well-known in
computational linguistics, and currently the subject of intensive research. To date, however …