Automatic evaluation of punning riddle template extraction

Try Agustini, Ruli Manurung

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

4 Citations (Scopus)

Abstract

This paper reports an empirical study to automatically evaluate the ability of T-PEG (Hong and Ong 2009) to extract joke templates by providing it with a corpus of punning riddles produced by another system, STANDUP (Manurung et al. 2008). This setup allows us to compare the extracted templates against the underlying data structures used by STANDUP in generating the corpus. In our setup, T-PEG is modified with a generalization component that clusters extracted templates based on structural similarity. These clusters are then compared against the underlying rules used by STANDUP to measure how well T-PEG is able to induce the schema used by STANDUP to generate the jokes. Whilst far from conclusive, an overall precision of 0.61 and recall of 0.763 suggests that T-PEG is able to extract some salient information regarding the underlying lexical relationships found within a punning riddle.

Original languageEnglish
Title of host publicationProceedings of the 3rd International Conference on Computational Creativity, ICCC 2012
EditorsDan Ventura, Mary Lou Maher, Alison Pease, Kristian Hammond, Rafael Perez y Perez, Geraint Wiggins
PublisherUniversity College Dublin
Pages134-139
Number of pages6
ISBN (Electronic)9781905254668
Publication statusPublished - 1 Jan 2012
Event3rd International Conference on Computational Creativity, ICCC 2012 - Dublin, Ireland
Duration: 30 May 20121 Jun 2012

Publication series

NameProceedings of the 3rd International Conference on Computational Creativity, ICCC 2012

Conference

Conference3rd International Conference on Computational Creativity, ICCC 2012
Country/TerritoryIreland
CityDublin
Period30/05/121/06/12

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