Data-Driven Metaphor Recognition and Explanation

Data-Driven Metaphor Recognition and Explanation Hongsong Li Microsoft Research Asia hongsli@microsoft.com Kenny Q. Zhu Shanghai Jiao Tong University kzhu@cs.sjtu.edu.cn Haixun Wang Google Research haixun@google.com Abstract 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 rec- ognize and explain the metaphors in the text. To our knowledge, this is the first purely data- driven approach of probabilistic metaphor ac- quisition, recognition, and explanation. Our results shows that it significantly outperforms other state-of-the-art methods in recognizing and explaining metaphors. 1 Introduction A metaphor is a way of communicating. It enables us to comprehend one thing in terms of another. For example, the metaphor, Juliet is the sun, allows us to see Juliet much more vividly than if Shakespeare had taken a more literal approach. We utter about one metaphor for every ten to twenty-five words, or about six metaphors a minute (Geary, 2011). Specifically, a metaphor is a mapping of concepts from a source domain to a target domain (Lakoff and Johnson, 1980). The source domain is often con- crete and based on sensory experience, while tar- get domain is usually abstract. Two concepts are connected by this mapping because they share some common or similar properties, and as a result, the meaning of one concept can be transferred to an- other. For example, in “Juliet is the sun,” the sun is the source concept while Juliet is the target concept. One interpretation of this metaphor is that both con- cepts share the property that their existence brings about warmth, life, and excitement. In a metaphor- ical sentence, at least one of the two concepts must be explicitly present. This leads to three types of metaphors: 1. Juliet is the sun. Here, both the source (sun) and the target (Juliet) are explicit. 2. Please wash your claws before scratching me. Here, the source (claws) is explicit, while the target (hands) is implicit, and the context of wash is in terms of the target. 3. Your words cut deep. Here, the target (words) is explicit, while the source (possibly, knife) is implicit, and the context of cut is in terms of the source. In this paper, we focus on the recognition and ex- planation of metaphors. For a given sentence, we first check whether it contains a metaphoric expres- sion (which we call metaphor recognition), and if it does, we identify the source and the target con- cepts of the metaphor (which we call metaphor ex- planation). Metaphor explanation is important for understanding metaphors. Explaining type 2 and 3 metaphors is particularly challenging, and, to the best of our knowledge, has not been attempted for nominal concepts 1 before. In our examples, know- ing that life and hands are the target concepts avoids the confusion that may arise if source …

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