Exploiting a Verb Lexicon in Automatic Semantic Role Labelling
نویسندگان
چکیده
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 semantic roles. We achieve a substantial improvement over an informed baseline.
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تاریخ انتشار 2005