Data-Driven Metaphor Recognition and Explanation

Hongsong Li, Kenny Q. Zhu, Haixun Wang
2013 Transactions of the Association for Computational Linguistics  
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,
more » ... r acquisition, recognition, and explanation. Our results shows that it significantly outperforms other state-of-the-art methods in recognizing and explaining metaphors.
doi:10.1162/tacl_a_00235 fatcat:usnnulmqx5dpdjmeug2mmgo5xe