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Amazon at MRP 2019: Parsing Meaning Representations with Lexical and Phrasal Anchoring

机译:亚马逊参加MRP 2019:使用词汇和短语锚定解析含义表示

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This paper describes the system submission of our team Amazon to the shared task on Cross Framework Meaning Representation Parsing (MRP) at the 2019 Conference for Computational Language Learning (CoNLL). Via extensive analysis of implicit alignments in AMR, we recategorize five meaning representations (MRs) into two classes: Lexical-Anchoring and Phrasal-Anchoring. Then we propose a unified graph-based parsing framework for the lexical-anchoring MRs, and a phrase-structure parsing for one of the phrasal-anchoring MRs, UCCA. Our system submission ranked 1st in the AMR subtask, and later improvements shows promising results on other frameworks as well.
机译:本文描述了我们的团队Amazon在2019年计算语言学习大会(CoNLL)上完成跨框架含义表示解析(MRP)共享任务的系统提交。通过对AMR中的隐式对齐方式的广泛分析,我们将五个含义表示(MR)重新分类为两类:词法固定和短语固定。然后,我们为词汇锚定的MR提出了一个基于图的统一解析框架,并且为其中一个短语锚定的MR UCCA提出了短语结构解析。我们的系统提交在AMR子任务中排名第一,后来的改进也显示了在其他框架上的可喜结果。

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