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Computational poetics encompasses the wide range of challenges implicit in analyzing and generating poetry – in all of its many forms – through computational techniques and frameworks. In this paper, we build on a nascent body of work that has proposed the use of the limerick as a ‘model organism’ for computational poetics, and in particular the use of Benchmarked Poetic Minimal Pairs (BPoMP) as an investigative framework, especially for the evaluation of the poetic abilities of deep learning language models. To that end, we include results for two new BPoMP tasks of interest for limerick analysis – the word deletion task and the limerick completion tasks. We include a release of a data set for the deletion task. We also offer up a suite of an additional ten BPoMP challenges whose precise formulations still require detail.

Urspr. Konferenzveröffentlichung/Originally conference publication: 1st Annual Conference of Computational Literary Studies, 01.-02.06.2022, Darmstadt, Germany