  This paper describes the system developed by the Laboratoire d'analyse
statistique des textes (LAST) for the Lexical Complexity Prediction shared task
at SemEval-2021. The proposed system is made up of a LightGBM model fed with
features obtained from many word frequency lists, published lexical norms and
psychometric data. For tackling the specificity of the multi-word task, it uses
bigram association measures. Despite that the only contextual feature used was
sentence length, the system achieved an honorable performance in the multi-word
task, but poorer in the single word task. The bigram association measures were
found useful, but to a limited extent.
