Davida Fromm


2014

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Two Approaches to Metaphor Detection
Brian MacWhinney | Davida Fromm
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

Methods for automatic detection and interpretation of metaphors have focused on analysis and utilization of the ways in which metaphors violate selectional preferences (Martin, 2006). Detection and interpretation processes that rely on this method can achieve wide coverage and may be able to detect some novel metaphors. However, they are prone to high false alarm rates, often arising from imprecision in parsing and supporting ontological and lexical resources. An alternative approach to metaphor detection emphasizes the fact that many metaphors become conventionalized collocations, while still preserving their active metaphorical status. Given a large enough corpus for a given language, it is possible to use tools like SketchEngine (Kilgariff, Rychly, Smrz, & Tugwell, 2004) to locate these high frequency metaphors for a given target domain. In this paper, we examine the application of these two approaches and discuss their relative strengths and weaknesses for metaphors in the target domain of economic inequality in English, Spanish, Farsi, and Russian.

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Resources for the Detection of Conventionalized Metaphors in Four Languages
Lori Levin | Teruko Mitamura | Brian MacWhinney | Davida Fromm | Jaime Carbonell | Weston Feely | Robert Frederking | Anatole Gershman | Carlos Ramirez
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

This paper describes a suite of tools for extracting conventionalized metaphors in English, Spanish, Farsi, and Russian. The method depends on three significant resources for each language: a corpus of conventionalized metaphors, a table of conventionalized conceptual metaphors (CCM table), and a set of extraction rules. Conventionalized metaphors are things like “escape from poverty” and “burden of taxation”. For each metaphor, the CCM table contains the metaphorical source domain word (such as “escape”) the target domain word (such as “poverty”) and the grammatical construction in which they can be found. The extraction rules operate on the output of a dependency parser and identify the grammatical configurations (such as a verb with a prepositional phrase complement) that are likely to contain conventional metaphors. We present results on detection rates for conventional metaphors and analysis of the similarity and differences of source domains for conventional metaphors in the four languages.