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DANGNT@UIT.VNU-HCM at SemEval 2019 Task 1: Graph Trans-formation System from Stanford Basic Dependencies to Universal Conceptual Cognitive Annotation (UCCA)

机译:DANGNT@UIT.VNU-HCM在SemEval 2019上的任务1:从斯坦福基本依赖关系到通用概念认知注释(UCCA)的图形转换系统

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This paper describes the graph transformation system (GT System) for SemEval 2019 Task 1: Cross-lingual Semantic Parsing with Universal Conceptual Cognitive Annotation (UCCA)~1. The input of GT System is a pair of text and its unannotated xml, which is a layer 0 part of UCCA form. The output of GT System is the corresponding full UCCA xml. Based on the idea of graph illustration and transformation, we perform four main tasks when building GT System. At the first task, we illustrate the graph form of Stanford dependencies~2 of input text We then transform into an intermediate graph in the second task. At the third task, we continue to transform into ouput graph form. Finally, we create the output UCCA xml The evaluation results show that our method generates good-quality UCCA xml and has a meaningful contribution to the semantic representation sub-field in Natural Language Processing.
机译:本文介绍了SemEval 2019任务1:使用通用概念认知注释(UCCA)〜1的跨语言语义解析的图形转换系统(GT System)。 GT System的输入是一对文本及其未注释的xml,它是UCCA格式的第0层部分。 GT System的输出是相应的完整UCCA xml。基于图形图解和变换的思想,我们在构建GT系统时执行四个主要任务。在第一个任务中,我们说明输入文本的斯坦福依赖关系〜2的图形形式,然后在第二个任务中转换为中间图形。在第三项任务中,我们将继续转换为输出图形式。最后,我们创建了输出UCCA xml。评估结果表明,我们的方法生成了高质量的UCCA xml,并对自然语言处理中的语义表示子字段做出了有意义的贡献。

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