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In this paper we provide a quantitative evaluation of information automatically extracted from machine readable dictionaries. Our results show that for any one dictionary, 55--70% of the extracted information is garbled in some way. However, we show that these results can be dramatically reduced to about 6% by combining the information extracted from five dictionaries. It therefore appears that even if individual dictionaries are an unreliable source of semantic information, multiple dictionaries can play an important role in building large lexical-semantic databases.

An assessment of semantic information automatically extracted from machine readable dictionaries