When extracting information about concepts from the Web, the problem is not recall, but precision: trying to identify which properties of a concept are genuinely distinctive. We discuss a series of experiments in empirical ontology using both unsupervised and supervised methods, showing that not all semantic relations we can extract from text are equally useful, and suggesting that attempting to identify concept attributes (parts, qualities, and the like) and their values results in better concept descriptions than those obtained by being less selective.
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