Robert S. Swier

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We present an unsupervised method for labelling the arguments of verbs with their semantic roles. Our bootstrapping algorithm makes initial unam-biguous role assignments, and then iteratively updates the probability model on which future assignments are based. A novel aspect of our approach is the use of verb, slot, and noun class information as the basis(More)
The Medication Advisor is the latest project of the Conversational Interaction and Spoken Dialogue research group at the University of Rochester. The goal of the project is an intelligent assistant that interacts with its users via conversational natural language, and provides them with information and advice regarding their prescription medications.(More)
We develop an unsupervised semantic role labelling system that relies on the direct application of information in a predicate lexicon combined with a simple probability model. We demonstrate the usefulness of predicate lexicons for role labelling, as well as the feasibility of modifying an existing role-labelled corpus for evaluating a different set of(More)
We present an unsupervised method for labelling the arguments of verbs with their semantic roles. Our bootstrapping algorithm makes initial unam-biguous role assignments, and then iteratively updates the probability model on which future assignments are based. A novel aspect of our approach is the use of verb, slot, and noun class information as the basis(More)
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