This paper describes a probabilistic model for coordination disambiguation integrated into syntactic and case structure analysis. Our model probabilistically assesses the parallel...
We present a simple history-based model for sentence generation from LFG f-structures, which improves on the accuracy of previous models by breaking down PCFG independence assumpt...
In this paper, we describe a two-stage multilingual dependency parser used for the multilingual track of the CoNLL 2007 shared task. The system consists of two components: an unla...
We present Pro3Gres, a deep-syntactic, fast dependency parser that combines a handwritten competence grammar with probabilistic performance disambiguation and that has been used i...
Gerold Schneider, Kaarel Kaljurand, Fabio Rinaldi,...
In this paper, we address a unique problem in Chinese language processing and report on our study on extending a Chinese thesaurus with region-specific words, mostly from the fina...
This paper describes ETK (Ensemble of Transformation based Keys) a new algorithm for inducing search keys for name filtering. ETK has the low computational cost and ability to ...
In this paper we propose an instance based method for lexical entailment and apply it to automatic ontology population from text. The approach is fully unsupervised and based on k...
We describe our experiments using the DeSR parser in the multilingual and domain adaptation tracks of the CoNLL 2007 shared task. DeSR implements an incremental deterministic Shif...
Giuseppe Attardi, Felice dell'Orletta, Maria Simi,...
We use a generative history-based model to predict the most likely derivation of a dependency parse. Our probabilistic model is based on Incremental Sigmoid Belief Networks, a rec...