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Automatic generation of linguistic artifacts is a problem that has been sporadically tackled over the years. The main goal of this paper is to explore how concept associations can be useful from a computational creativity point of view to generate some of these artifacts. We present an approach where finding associations between concepts that would not usually be considered as related (for example life and politics or diamond and concrete ) could be the seed for the generation of creative and surprising linguistic artifacts such as rhetorical figures ( life is like politics ) and riddles ( what is as hard as concrete? ). Human volunteers evaluated the quality and appropriateness of the generated figures and riddles, and the results show that the concept associations obtained are useful for producing these kinds of creative artifacts.

Propp's influential structural analysis of fairy tales created a powerful schema for representing storylines in terms of character functions, which is straightforward to exploit in computational semantic analysis and procedural generation of stories of this genre. We tackle two resources that draw on the Proppian model - one formalizes it as a semantic markup scheme and the other as an ontology - both lacking linguistic phenomena explicitly represented in them. The need for integrating linguistic information into structured semantic resources is motivated by the emergence of suitable standards that facilitate this, and the benefits such joint representation would create for transdisciplinary research across Digital Humanities, Computational Linguistics, and Artificial Intelligence.