1. A machine-implemented method comprising: obtaining a plurality of instances and a plurality of attributes, wherein each instance has one or more attributes of the plurality of attributes as attributes of the instance; for each attribute of an instance: identifying a plurality documents from an unstructured document collection that are relevant to the instance, where each of the documents include at least a value for the attribute of the instance; grouping values of the attribute of the instance into two or more groups; and establishing a subset of the one or more values of the attribute as characterizing the instance including selecting one group of values from the two or more groups; and adding each instance, the respective attributes of each instance, and the respective subset of values for the corresponding attributes to a structured data collection.
7. The method of claim 1 , further comprising: extracting a first candidate value of a first attribute of a first instance from a first electronic document; extracting a second candidate value of the first attribute of the first instance from a second electronic document; determining a first likelihood that the first candidate value correctly characterizes the first attribute of the first instance; determining a second likelihood that the second candidate value correctly characterizes the first attribute of the first instance; determining that the first likelihood is higher than the second likelihood; and establishing, in response to determining that the first likelihood is higher than the second likelihood, the first candidate value rather than the second candidate value as characterizing the first instance in the structured data collection.