CNRC at SemEval-2016 task 1: Experiments in crosslingual semantic textual similarity

Abstract

We describe the systems entered by the National Research Council Canada in the SemEval-2016 Task1: Crosslingual Semantic Textual Similarity. We tried two approaches: One computes a true crosslingual similarity based on features extracted from lexical semantics and shallow semantic structures of the source and target fragments, combined using a linear model. The other approach relies on Statistical Machine Translation, followed by a monolingual semantic similarity, relying again on syntactic and semantic features. We report our experiments using trial data, as well as official final results on the evaluation data.