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