7 papers
Using a Probabilistic Class-Based Lexicon for Lexical Ambiguity Resolution
Detlef Prescher, Stefan Riezler, Mats Rooth
This paper presents the use of probabilistic class-based lexica for disambiguation in target-word selection. Our method employs minimal but precise contextual information for disam…
Lexicalized Stochastic Modeling of Constraint-Based Grammars using Log-Linear Measures and EM Training
Stefan Riezler, Detlef Prescher, Jonas Kuhn +1
We present a new approach to stochastic modeling of constraint-based grammars that is based on log-linear models and uses EM for estimation from unannotated data. The techniques ar…
Estimators for Stochastic ``Unification-Based'' Grammars
Mark Johnson, Stuart Geman, Stephen Canon +2
Log-linear models provide a statistically sound framework for Stochastic ``Unification-Based'' Grammars (SUBGs) and stochastic versions of other kinds of grammars. We describe two…
Statistical Inference and Probabilistic Modelling for Constraint-Based NLP
Stefan Riezler
We present a probabilistic model for constraint-based grammars and a method for estimating the parameters of such models from incomplete, i.e., unparsed data. Whereas methods exist…
Inside-Outside Estimation of a Lexicalized PCFG for German
Franz Beil, Glenn Carroll, Detlef Prescher +2
The paper describes an extensive experiment in inside-outside estimation of a lexicalized probabilistic context free grammar for German verb-final clauses. Grammar and formalism fe…
Inducing a Semantically Annotated Lexicon via EM-Based Clustering
Mats Rooth, Stefan Riezler, Detlef Prescher +2
We present a technique for automatic induction of slot annotations for subcategorization frames, based on induction of hidden classes in the EM framework of statistical estimation.…