Abstract
We present our submitted systems for Semantic Textual Similarity (STS) Track 4 at SemEval-2017. Given a pair of Spanish-English sentences, each system must estimate their semantic similarity by a score between 0 and 5. In our submission, we use syntax-based, dictionary-based, context-based, and MT-based methods. We also combine these methods in unsupervised and supervised way. Our best run ranked 1st on track 4a with a correlation of 83.02% with human annotations.
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CITATION STYLE
Ferrero, J., Besacier, L., Schwab, D., & Agnès, F. (2017). CompiLIG at SemEval-2017 Task 1: Cross-Language Plagiarism Detection Methods for Semantic Textual Similarity. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 109–114). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/S17-2012
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