This study investigated EFL learners' comprehension of scalar properties of three types of emotion verbs, namely, fear type, liking and disliking emotion verbs and compare their performance with instructors and native speakers of English. The participants were 38 nonnative pre-service teachers from ELT department at a state university in Turkey, 11 ELT instructors at different universities and 10 native speakers from the USA and the UK. A scale construction task was administered, and data were collected via in person and e-mail according to participants' judgements on scalar emotion verbs in terms of their relative order on a linear scale. The quantitative data were analysed using SPSS. The results revealed that in terms of constructing consistent scales with previously determined scales in literatutre, pre-service teachers performed poorly for fear-type and disliking emotion verbs, they were partly successful in constructing consistent scales for liking verbs. It was also found that similarly instructors performed poorly in constructing scales for fear-type and disliking verbs, but they were better than pre-service teachers. They were also successful in constructing scales for liking verbs. Native speakers were successful in fear-type and liking verbs; however, like non-native participants, they performed poorly in constructing consistent scales for disliking verbs. This means that there are cross-cultural differences among participants' judgement of emotion verbs on a linear scale in terms of their intensity. This study provides valuable information for the studies on lexical resources (e.g., VerbNet, WordNet etc.) Previous studies (e.g. Fellbaum & Mathieu,2014; Sheinman, & Tokunaga, 2009) show a way to represent the scalar properties of emotion verbs in WordNet, and other possible extensions to additional verb families can cause a more subtle semantic analysis of emotion verbs in lexical databases with potential benefits for automatic inferencing, language pedagogy and translation. This study contributes to semantic analysis of emotion verbs in lexical databases. It also provides some implications for students, language teachers, and policy makers in terms of vocabulary learning and teaching.