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Proceedings of the Annual Meeting of the Cognitive Science Society
We present a highly performant, minimally supervised system for the challenging task of unconstrained conceptual property extraction (e.g., banana is fruit, spoon used for eating). Our technique employs lightly supervised support vector machines to acquire promising features from our corpora (Wikipedia and UKWAC) and uses those features to anchor the search for plausible unconstrained relations in our corpus. We introduce a novel backing-off method to find the most likely relation for eachfatcat:jx4d5h5uenb37c7odp3w27gdfq