Riddle Generation using Word Associations

Paloma Galván, Virginia Francisco, Raquel Hervás, Gonzalo Méndez

Abstract
In knowledge bases where concepts have associated properties, there is a large amount of comparative information that is implicitly encoded in the values of the properties these concepts share. Although there have been previous approaches to generating riddles, none of them seem to take advantage of structured information stored in knowledge bases such as Thesaurus Rex, which organizes concepts according to the fine grained ad-hoc categories they are placed into by speakers in everyday language, along with associated properties or modifiers. Taking advantage of these shared properties, we have developed a riddle generator that creates riddles about concepts represented as common nouns. The base of these riddles are comparisons between the target concept and other entities that share some of its properties. In this paper, we describe the process we have followed to generate the riddles starting from the target concept and we show the results of the first evaluation we have carried out to test the quality of the resulting riddles.
Anthology ID:
L16-1381
Volume:
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
Month:
May
Year:
2016
Address:
Portorož, Slovenia
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Sara Goggi, Marko Grobelnik, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
2407–2412
Language:
URL:
https://aclanthology.org/L16-1381
DOI:
Bibkey:
Cite (ACL):
Paloma Galván, Virginia Francisco, Raquel Hervás, and Gonzalo Méndez. 2016. Riddle Generation using Word Associations. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 2407–2412, Portorož, Slovenia. European Language Resources Association (ELRA).
Cite (Informal):
Riddle Generation using Word Associations (Galván et al., LREC 2016)
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PDF:
https://preview.aclanthology.org/naacl24-info/L16-1381.pdf
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