A minimally supervised machine learning framework is described for extracting relations of various complexity. Bootstrapping starts from a small set of n-ary relation instances as...
In this paper we propose a rule-based approach to extract dependency and grammatical relations from the Venice Italian Treebank (VIT) (Delmonte et al., 2007) with bracketed tree s...
Abstract Super Flexible Messaging (SFM) provides a powerful and elegant message passing abstraction for transferring arbitrary data between remote processes. SFM achieves the simpl...
This paper demonstrates how unsupervised techniques can be used to learn models of deep linguistic structure. Determining the semantic roles of a verb's dependents is an impo...
Background: Genomic functional information is valuable for biomedical research. However, such information frequently needs to be extracted from the scientific literature and struc...