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Chinese textual entailment with Wordnet semantic and dependency syntactic analysis

机译:用Wordnet语义和依赖语法分析的汉语文本意见

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Recognizing Inference in TExt (RITE) is a task for automatically detecting entailment, paraphrase, and contradiction in texts which addressing major text understanding in information access research areas. In this paper, we proposed a Chinese textual entailment system using Wordnet semantic and dependency syntactic approaches in Recognizing Inference in Text (RITE) using the NTCIR-10 RITE-2 subtask datasets. Wordnet is used to recognize entailment at lexical level. Dependency syntactic approach is a tree edit distance algorithm applied on the dependency trees of both the text and the hypothesis. We thoroughly evaluate our approach using NTCIR-10 RITE-2 subtask datasets. As a result, our system achieved 73.28% on Traditional Chinese Binary-Class (BC) subtask and 74.57% on Simplified Chinese Binary-Class subtask with NTCIR-10 RITE-2 development datasets. Thorough experiments with the text fragments provided by the NTCIR-10 RITE-2 subtask showed that the proposed approach can improve system's overall accuracy.
机译:识别文本(Rite)的推理是一种自动检测征求,释义和矛盾的任务,这些任务是在信息访问研究领域寻求主要文本理解的文本中。在本文中,我们使用NTCIR-10 Rite-2子任务数据集识别文本(仪式)中的推理,提出了一种使用Wordnet语义和依赖性句法方法的文本素质概要方法。 WordNet用于识别词汇级别的征兆。依赖性句法方法是应用于文本和假设的依赖树上的树编辑距离算法。我们使用NTCIR-10 Rite-2 Subtask数据集进行彻底评估我们的方法。因此,我们的系统在传统的中国二进制类(BC)SubTask上实现了73.28%,并在具有NTCIR-10 Rite-2开发数据集的简体中文二进制子任务上进行了74.57%。通过NTCIR-10 Rite-2 SubTask提供的文本碎片进行彻底的实验,表明该方法可以提高系统的整体准确性。

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