We present a novel framework for auto- mated extraction and approximation of nu- merical object attributes such as height and weight from the Web. Given an object-attribute pair, we discover and ana- lyze attribute information for a set of com- parable objects in order to infer the desired value. This allows us to approximate the desired numerical values even when no ex- act values can be found in the text. Our framework makes use of relation defining patterns and WordNet similarity information. First, we obtain from the Web and WordNet a list of terms similar to the given object. Then we retrieve attribute values for each term in this list, and infor- mation that allows us to compare different objects in the list and to infer the attribute value range. Finally, we combine the re- trieved ...

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