In this contribution, we describe the system presented by the PolyU CBS-Comp Team at the Task 1 of SemEval 2021, where the goal was the estimation of the complexity of words in a given sentence context. Our top system, based on a combination of lexical, syntactic, word embeddings and Transformers-derived features and on a Gradient Boosting Regressor, achieves a top correlation score of 0.754 on the subtask 1 for single words and 0.659 on the subtask 2 for multiword expressions.
|Name||SemEval 2021 - 15th International Workshop on Semantic Evaluation, Proceedings of the Workshop|
|Conference||15th International Workshop on Semantic Evaluation|
|Period||5/08/21 → 6/08/21|
- Computational Theory and Mathematics
- Computer Science Applications
- Theoretical Computer Science