A new, general approach is described for approximate inference in first-order probabilistic languages, using Markov chain Monte Carlo (MCMC) techniques in the space of concrete po...
We describe a pattern acquisition algorithm that learns, in an unsupervised fashion, a streamlined representation of linguistic structures from a plain natural-language corpus. Th...
Zach Solan, David Horn, Eytan Ruppin, Shimon Edelm...
In this paper we present the results of the combination of stochastic and rule-based disambiguation methods applied to Basque languagel. The methods we have used in disambiguation...
Synchronous languages rely on formal methods to ease the development of applications in an efficient and reusable way. Formal methods have been advocated as a means of increasing t...
Although classical first-order logic is the de facto standard logical foundation for artificial intelligence, the lack of a built-in, semantically grounded capability for reasonin...