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A STUDY OF TEXTUAL ENTAILMENT

机译:语篇互动研究

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摘要

In this paper we study a graph-based approach to the task of Recognizing Textual Entailment between a Text and a Hypothesis. The approach takes into account the full lexico-syntactic context of both the Text and Hypothesis and is based on the concept of subsumption. It starts with mapping the Text and Hypothesis on to graph structures that have nodes representing concepts and edges representing lexico-syntactic relations among concepts. An entailment decision is then made on the basis of a subsumption score between the Text-graph and Hypothesis-graph. The results obtained from a standard entailment test data set were promising. The impact of synonymy on entailment is quantified and discussed. An important advantage to a solution like ours is its ability to be customized to obtain high-confidence results.
机译:在本文中,我们研究了一种基于图的方法来识别文本和假设之间的文本蕴涵。该方法考虑了文本和假设的全部词汇句法语境,并且基于包含的概念。它从将“文本和假设”映射到图形结构开始,该图形结构具有表示概念的节点和表示概念之间的词汇句法关系的边缘。然后根据文本图和假设图之间的包含分数来做出蕴含决策。从标准的包装测试数据集获得的结果很有希望。量化和讨论了同义对蕴含的影响。像我们这样的解决方案的一个重要优势是可以定制以获得高可信度结果的能力。

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