FlexSTS: A Framework for Semantic Textual Similarity
Abstract
Since 2012, Semantic Evaluation series (SemEval) propose the task of Semantic Textual Similarity (STS) as a evaluation theme, demonstrating the relevance of this research topic. In 2016, the task was first proposed to the Portuguese language, in the Workshop of Semantic Textual Similarity and Inference Evaluation (ASSIN), held during the conference PROPOR 2016. In this paper, we present the FlexSTS --- a flexible framework for STS combining several components as morphological and syntactic parsers, knowledge and lexical databases, machine learning algorithms, and algorithms for alignment and similarity. For ASSIN, FlexSTS was instantiated into three STS systems for Portuguese. The results were compared with a baseline approach that uses DICE coefficient.
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