LangResearchLab NC at SemEval-2021 Task 1: Linguistic Feature Based Modelling for Lexical Complexity

SEMEVAL 2021  ·  Raksha Agarwal, Niladri Chatterjee ·

The present work aims at assigning a complexity score between 0 and 1 to a target word or phrase in a given sentence. For each Single Word Target, a Random Forest Regressor is trained on a feature set consisting of lexical, semantic, and syntactic information about the target. For each Multiword Target, a set of individual word features is taken along with single word complexities in the feature space. The system yielded the Pearson correlation of 0.7402 and 0.8244 on the test set for the Single and Multiword Targets, respectively.

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