Language-independent ensemble approaches to metaphor identification

Jonathan Dunn, Jon Beitran De Heredia, Maura Burke, Lisa Gandy, Sergey Kanareykin, Oren Kapah, Matthew Taylor, Dell Hines, Ophir Frieder, David Grossman, Newton Howard, Moshe Koppel, Scott Morris, Andrew Ortony, Shlomo Argamon

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations


True natural language understanding requires the ability to identify and understand metaphorical utterances, which are ubiquitous in human communication of all kinds. At present, however, even the problem of identifying metaphors in arbitrary text is very much an unsolved problem, let alone analyzing their meaning. Furthermore, no current methods can be transferred to new languages without the development of extensive language-specific knowledge bases and similar semantic resources. In this paper, we present a new language- independent ensemble-based approach to identifying linguistic metaphors in natural language text. The system's architecture runs multiple corpus-based metaphor identification algorithms in parallel and combines their results. The architecture allows easy integration of new metaphor identification schemes as they are developed. This new approach achieves state-of-the-art results over multiple languages and represents a significant improvement over existing methods for this problem.

Original languageEnglish
Title of host publicationCognitive Computing for Augmented Human Intelligence - Papers Presented at the 28th AAAI Conference on Artificial Intelligence, Technical Report
PublisherAI Access Foundation
Number of pages7
ISBN (Electronic)9781577356646
StatePublished - 2014
Event28th AAAI Conference on Artificial Intelligence, AAAI 2014 - Quebec City, Canada
Duration: Jul 27 2014 → …

Publication series

NameAAAI Workshop - Technical Report


Conference28th AAAI Conference on Artificial Intelligence, AAAI 2014
CityQuebec City
Period07/27/14 → …


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