We present ExB Themis -a word alignmentbased semantic textual similarity system developed for SemEval-2015 Task 2: Semantic Textual Similarity. It combines both string and semantic similarity measures as well as alignment features using Support Vector Regression. It occupies the first three places on Spanish data and additionally places second on English data. ExB Themis proved to be the best multilingual system among all participants.
We present our state of the art multilingual text summarizer capable of single as well as multi-document text summarization. The algorithm is based on repeated application of TextRank on a sentence similarity graph, a bag of words model for sentence similarity and a number of linguistic pre-and post-processing steps using standard NLP tools. We submitted this algorithm for two different tasks of the MultiLing 2015 summarization challenge: Multilingual Singledocument Summarization and Multilingual Multi-document Summarization.
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