In this paper we describe the ASAP system (Automatic Semantic Alignment for Phrases) 1 which participated on the Task 1 at the SemEval-2014 contest (Marelli et al., 2014a). Our assumption is that STS (Semantic Text Similarity) follows a function considering lexical, syntactic, semantic and distributional features. We demonstrate the learning process of this function without any deep preprocessing achieving an acceptable correlation.
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Alves et al. (2014) studied this question.
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