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AntNLP at CoNLL 2018 Shared Task: A Graph-based Parser for Universal Dependency Parsing

机译:CoNLL 2018共享任务上的AntNLP:用于通用依赖项解析的基于图的解析器

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摘要

We describe the graph-based dependency parser in our system (AntNLP) submitted to the CoNLL 2018 UD Shared Task. We use bidirectional lstm to get the word representation, then a bi-affine pointer networks to compute scores of candidate dependency edges and the MST algorithm to get the final dependency tree.From the official testing results, our system gets 70.90 LAS F1 score (rank 9/26), 55.92 MLAS (10/26) and 60.91 BLEX(8/26).
机译:我们在提交给CoNLL 2018 UD共享任务的系统(AntNLP)中描述了基于图的依赖关系解析器。我们使用双向lstm来获取单词表示,然后使用双仿射指针网络来计算候选依赖边缘的分数,并使用MST算法来获得最终的依赖树。从官方测试结果来看,我们的系统获得70.90 LAS F1分数(等级9/26),55.92 MLAS(10/26)和60.91 BLEX(8/26)。

著录项

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  • 会议地点 Brussels(BE)
  • 作者单位

    Department of Computer Science and Technology East China Normal University;

    Department of Computer Science and Technology East China Normal University;

    Department of Computer Science and Technology East China Normal University;

    Department of Computer Science and Technology East China Normal University;

    Department of Computer Science and Technology East China Normal University;

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  • 正文语种 eng
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