In this paper, we present a learning approach to the scenario template task of information extraction, where information filling one template could come from multiple sentences. ...
To truly understand language, an intelligent system must be able to connect words, phrases, and sentences to its perception of objects and events in the world. Current natural lan...
We consider the problem of learning to parse sentences to lambda-calculus representations of their underlying semantics and present an algorithm that learns a weighted combinatory...
Abstract. We propose to use semi-supervised learning methods to classify evaluative expressions, that is, tuples of subjects, their attributes, and evaluative words, that indicate ...
In this paper, we propose a novel method for semi-supervised learning of nonprojective log-linear dependency parsers using directly expressed linguistic prior knowledge (e.g. a no...