1. A method, comprising: for each sequence of a plurality of attribute determination sequences in a training set, receiving a subset of attribute determinations in the attribute determination sequence that are likely to be a false positive; receiving input text, wherein at least a subset of tokens within the input text are a set of attribute tokens with corresponding attribute determinations; identifying at least one attribute determination corresponding to an attribute token of the set of attribute tokens as a false positive based on the training set; producing a set of filtered attribute tokens by filtering from said set of attribute tokens, all attribute tokens corresponding to attribute determinations that have been identified as false positives, wherein the method is performed by a computing device comprising a processor.
1. A method, comprising: for each sequence of a plurality of attribute determination sequences in a training set, receiving a subset of attribute determinations in the attribute determination sequence that are likely to be a false positive; receiving input text, wherein at least a subset of tokens within the input text are a set of attribute tokens with corresponding attribute determinations; identifying at least one attribute determination corresponding to an attribute token of the set of attribute tokens as a false positive based on the training set; producing a set of filtered attribute tokens by filtering from said set of attribute tokens, all attribute tokens corresponding to attribute determinations that have been identified as false positives, wherein the method is performed by a computing device comprising a processor. 3. The method of claim 1 , wherein identifying at least one attribute determination corresponding to an attribute token of the set of attribute tokens as a false positive comprises generating a collapsed skeleton token in which each attribute token and each series of non-attribute tokens are represented with a corresponding single character.