Automatically extracting word relationships as templates for pun generation

Authors:
Bryan Anthony Hong;Ethel Ong
Affiliations:
De La Salle University, Manila, Philippines;De La Salle University, Manila, Philippines
Venue:
CALC '09 Proceedings of the Workshop on Computational Approaches to Linguistic Creativity
Year:
2009

Citing 3
Cited 0

ConceptNet — A Practical Commonsense Reasoning Tool-Kit

BT Technology Journal
Computational Humor

IEEE Intelligent Systems
Generating Punning Riddles from Examples

ISUC '08 Proceedings of the 2008 Second International Symposium on Universal Communication

Quantified Score

Hi-index	0.00

Visualization

Abstract

Computational models can be built to capture the syntactic structures and semantic patterns of human punning riddles. This model is then used as rules by a computer to generate its own puns. This paper presents T-PEG, a system that utilizes phonetic and semantic linguistic resources to automatically extract word relationships in puns and store the knowledge in template form. Given a set of training examples, it is able to extract 69.2% usable templates, resulting in computer-generated puns that received an average score of 2.13 as compared to 2.70 for human-generated puns from user feedback.