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This paper demonstrates how the parallel examination of distributional data and frame semantic information can expose word senses that are not documented in FrameNet. In our case study, we compare the distributional features of the word crime to its properties stored in the FrameNet database also considering dictionary data that we find in three online monolingual dictionaries. Our analysis indicates that crime has senses that are absent from FrameNet. The five senses that we identify can bedoi:10.34103/argumentum/2020/4 fatcat:ilslnrqvcfbqbmid25kwj2ysa4