“…These text-based problems range from novel word problems (e.g., king:queen::man:woman) to mapping sentence elements (e.g., "She is growing like a weed") to drawing parallels between stories (Ichien, Lu, & Holyoak, 2020). Initially, analogical reasoning started as psychologically-based algorithms (see (Gentner, 1983); (Holyoak & Thagard, 1989); (Hofstadter & Mitchell, 1995)) but recently, with the rise of natural language processing, vector space models and artificial neural network approaches have increased in popularity (Combs, Bihl, Ganapathy, & Staples, 2022). To date, the most prominent vector space models include Word2Vec (Mikolov, Sutskever, Chen, Corrado, & Dean, 2013;Mikolov, Tomas, Yih, & Zweig, 2013), Global Vectors (GloVe) (Pennington, Socher, & Manning, 2014), and fastText (Bojanowski, Grave, Joulin, & Mikolov, 2017).…”