C3SL at SemEval-2021 Task 1: Predicting Lexical Complexity of Wordsin Specific Contexts with Sentence Embeddings
Abstract:
We present our approach to predicting lexical complexity of words in specific contexts, as entered LCP Shared
Task 1 at SemEval 2021. The approach consists of separating sentences into smaller chunks, embedding them with
Sent2Vec, and reducing the embeddings into a simpler vector used as input to a neural network, the latter for
predicting the complexity of words and expressions. Results show that the pre-trained sentence embeddings are
not able to capture lexical complexity from the language when applied in cross-domain applications.