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This paper describes the system developed by the Laboratoire d'analysestatistique des textes (LAST) for the Lexical Complexity Prediction shared taskat SemEval-2021. The proposed system is made up of a LightGBM model fed withfeatures obtained from many word frequency lists, published lexical norms andpsychometric data. For tackling the specificity of the multi-word task, it usesbigram association measures. Despite that the only contextual feature used wassentence length, the system achieved an honorable performance in the multi-wordtask, but poorer in the single word task. The bigram association measures werefound useful, but to a limited extent.

LAST at SemEval-2021 Task 1: Improving Multi-Word Complexity Prediction Using Bigram Association Measures