  Multiword expressions (MWEs) represent lexemes that should be treated as
single lexical units due to their idiosyncratic nature. Multiple NLP
applications have been shown to benefit from MWE identification, however the
research on lexical complexity of MWEs is still an under-explored area. In this
work, we re-annotate the Complex Word Identification Shared Task 2018 dataset
of Yimam et al. (2017), which provides complexity scores for a range of
lexemes, with the types of MWEs. We release the MWE-annotated dataset with this
paper, and we believe this dataset represents a valuable resource for the text
simplification community. In addition, we investigate which types of
expressions are most problematic for native and non-native readers. Finally, we
show that a lexical complexity assessment system benefits from the information
about MWE types.
