SemantiKLUE: Semantic Textual Similarity with Maximum Weight Matching

Abstract

This paper describes the SemantiKLUE system (Proisl et al., 2014) used for the SemEval-2015 shared task on Semantic Textual Similarity (STS) for English. The system was developed for SemEval-2013 and extended for SemEval-2014, where it participated in three tasks and ranked 13th out of 38 submissions for the English STS task. While this year's submission ranks 46th out of 73, further experiments on the selection of training data led to notable improvements showing that the system could have achieved rank 22 out of 73. We report a detailed analysis of those training selection experiments in which we tested different combinations of all the available STS datasets, as well as results of a qualitative analysis conducted on a sample of the sentence pairs for which SemantiKLUE gave wrong STS predictions.