... The major problem is that more and more basic methods capable of estimating the semantic similarity of pieces of text are being proposed (Navigli & Martelli, 2019). In the end, a plethora of reasonable methods are available, each based on very different concepts and assumptions, and the knowledge engineer does not know which one to use from the classical techniques (Corley & Mihalcea, 2005;Deerwester et al., 1990;Han et al., 2013;Huang et al., 2012;Janowicz et al., 2008;Jiang & Conrath, 1997;Leacock & Chodorow, 1998;Levenshtein, 1966;Li et al., 2003;Lin, 1998;Pedersen et al., 2007;Resnik, 1999;Rodríguez & Egenhofer, 2003;Sánchez et al., 2011;Seco et al., 2004) to the most recent ones (Aouicha et al., 2016;Bojanowski et al., 2017;Cer et al., 2018;Deudon, 2018;Devlin et al., 2019;He & Lin, 2016;Lastra-Díaz et al., 2017;Levy et al., 2015;Mikolov et al., 2013;Peters et al., 2018;Pilehvar & Navigli, 2015;Qu et al., 2018;Zhang et al., 2020). Therefore, many researchers agree that appropriately combining different semantic similarity measures could avoid fatal errors when implementing solutions working in production settings (Mihalcea et al., 2006;Pirrò, 2009;Potash et al., 2016). ...