We combine two complementary ideas for learning supertaggers from highly ambiguous lexicons: grammar-informed tag transitions and models minimized via integer programming. Each st...
We propose a new model for unsupervised POS tagging based on linguistic distinctions between open and closed-class items. Exploiting notions from current linguistic theory, the sy...
Abstract People typically move and act under the constraints of an environment, making human behavior strongly place-dependent. Motion patterns, the places and the rates at which p...
Matthias Luber, Gian Diego Tipaldi, Kai Oliver Arr...
A large body of prior research on coreference resolution recasts the problem as a two-class classification problem. However, standard supervised machine learning algorithms that m...
We present a novel method for record extraction from social streams such as Twitter. Unlike typical extraction setups, these environments are characterized by short, one sentence ...