“…Metaphor is of course used in many forms of poetry, and rule-based and statistical models have enabled the classification of metaphor in a corpus of English language poems (Kesarwani, Inkpen, Szpakowicz and Tanasecu (2017). Other models have enabled the detection of metaphor in expressionistic German poems (Reinig & Rehbein, 2019), identification of features that the predict period of origin, authorship, and goodness ratings (Jacobs & Kinder, 2017), and the differentiation of metaphor created by renowned poets and non-professional authors (Jacobs & Kinder, 2018). Additional examples of CL methods that have been used to study poetry include the detection of emotion in Punjabi poetry using Naive Bayesian and Support Vector Machine techniques (Saini & Kaur, 2020), stanza identification in Hindi poetry (Audichya & Saini, 2021), probabilistic topic modeling to study topic, meter, and authorship in Persian poems (Asgari & Chappelier, 2013), statistical and rule-based methods to determine the metrical and semantic aspects of 16th- and 17th-century Spanish Golden Age sonnets (Navarro-Colorado, 2015), and enjambment detection in a large diachronic corpus of Spanish sonnets (Ruiz, Canton, Poibeau & Gonzalez-Blanco, 2017).…”