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Recognizing metaphors and identifying the source-target mappings is an important task as metaphorical text poses a big challenge for machine reading. To address this problem, we automatically acquire a metaphor knowledge base and an isA knowledge base from billions of web pages. Using the knowledge bases, we develop an inference mechanism to recognize and explain the metaphors in the text. To our knowledge, this is the first purely datadriven approach of probabilistic metaphor acquisition,doi:10.1162/tacl_a_00235 fatcat:usnnulmqx5dpdjmeug2mmgo5xe