Metaphor identification using verb and noun clustering

Citation

Ekaterina Shutova, Lin Sun, and Anna Korhonen (2010). Metaphor identification using verb and noun clustering. COLING 2010.

Online Version

http://dl.acm.org/citation.cfm?id=1873894

Basic Idea

The basic idea of this paper is to expand the metaphorical Subject-Verb or Verb-Object pairs, e.g., (nation, flex, nsbj), or (burn, money, dobj), and use the expanded pairs to find the new metaphor in the open text. In this paper, they built clusters of verb and noun respectively, and expand the S-V/V-O pairs based on those clusters.

Discussions

Though the concept is simple, there might be some tricks:

• Good clustering seems important. They use the features developed based on selectional preferences of verb to build the verb clusters, and also used syntactic features to build the noun cluster. These features might be quite critical to make good clusters and thus achieve good metaphor detection. However, their features and tools are not openly accessible and not very easy to reproduce.

• Filtering out verbs with weak selectional preferences is also important, but it also requires good noun clustering. In this paper, they adopted the method proposed by Resnik (1997) to measure the strength of selectional preferences of verbs based on noun clusters, and filter out the verbs with weak selectional preference, e.g., "take", "put", "get".

Reference

• Resnik, P. 1997. Selectional preference and sense disambiguation. In ACL SIGLEX Workshop on Tagging Text with Lexical Semantics, Washington, D.C.