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We present a description of the system submitted to the Semantic Textual Similarity (STS) shared task at SemEval 2016. The task is to assess the degree to which two sentences carry the same meaning. We have designed two different methods to automatically compute a similarity score between sentences. The first method combines a variety of semantic similarity measures as features in a machine learning model. In our second approach, we employ training data from the Interpretable Similarity subtaskdoi:10.18653/v1/s16-1093 dblp:conf/semeval/PrzybylaNSKA16 fatcat:ybiyhw6cpzej5mwud42otlltee