Interpretable semantic textual similarity: Finding and explaining differences between sentences

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• 作者：I. Lopez-Gazpio ; M. Maritxalar ; A. Gonzalez-Agirre ; G. Rigau ; L. Uria ; E. Agirre ; ^{e.agirre@ehu.eus}
• 关键词：Interpretability ; Tutoring systems ; Semantic textual similarity ; Natural language understanding
• 刊名：Knowledge-Based Systems
• 出版年：2017
• 出版时间：1 March 2017
• 年：2017
• 卷：119
• 期：Complete
• 页码：186-199
• 全文大小：1247 K
• 卷排序：119

文摘

We address interpretability, the ability of machines to explain their reasoning. We formalize it for textual similarity as graded typed alignment between 2 sentences. We release an annotated dataset and build and evaluate a high performance system. We show that the output of the system can be used to produce explanations. 2 user studies show preliminary evidence that explanations help humans perform better.