12 indexed results
The left-corner transform removes left-recursion from (probabilistic) context-free grammars and unification grammars, permitting simple top-down parsing techniques to be used.
This paper examines efficient predictive broad-coverage parsing without dynamic programming. In contrast to bottom-up methods, depth-first top-down parsing produces partial
Log-linear models provide a statistically sound framework for Stochastic ``Unification-Based'' Grammars (SUBGs) and stochastic versions of other kinds of grammars.
This paper presents a Bayesian model for unsupervised learning of verb selectional preferences. For each verb the model creates a
This paper describes a method for estimating conditional probability distributions over the parses of ``unification-based'' grammars which can utilize auxiliary
This paper introduces a non-unification-based version of LFG called R-LFG (Resource-based Lexical Functional Grammar), which combines elements from both LFG
This paper compares two different ways of estimating statistical language models. Many statistical NLP tagging and parsing models are estimated
We present a new approach to stochastic modeling of constraint-based grammars that is based on log-linear models and uses EM
This paper shows how proof nets can be used to formalize the notion of ``incomplete dependency'' used in psycholinguistic theories
The performance of PCFGs estimated from tree banks is sensitive to the particular way in which linguistic constructions are represented
FAME is designed to perform an all-sky, astrometric survey with unprecedented accuracy. It will create a rigid astrometric catalog of
Once one has enriched LFG's formal machinery with the linear logic mechanisms needed for semantic interpretation as proposed by Dalrymple