Using structured text for large-scale attribute extraction

Abstract

We propose a weakly-supervised approach for extracting class attributes from structured text available within Web documents. The overall precision of the extracted attributes is around 30% higher than with previous methods operating on Web documents. In addition to attribute extraction, this approach also automatically identifies values for a subset of the extracted class attributes.