Designing a Uniform Meaning Representation for Natural Language Processing
Designing a Uniform Meaning Representation for Natural Language Processing
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DOI：
10.1007/s13218-021-00722-w
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发表时间：
2021-04
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通讯作者：
J. V. Gysel;Meagan Vigus;Jayeol Chun;Kenneth Lai;Sarah Moeller;Jiarui Yao;Timothy J. O'Gorman;Andrew Cowell;W. Bruce Croft;Chu-Ren Huang;Jan Hajic;James H. Martin;S. Oepen;Martha Palmer;J. Pustejovsky;Rosa Vallejos;Nianwen Xue
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作者：
J. V. Gysel;Meagan Vigus;Jayeol Chun;Kenneth Lai;Sarah Moeller;Jiarui Yao;Timothy J. O'Gorman;Andrew Cowell;W. Bruce Croft;Chu-Ren Huang;Jan Hajic;James H. Martin;S. Oepen;Martha Palmer;J. Pustejovsky;Rosa Vallejos;Nianwen Xue
在本文中，我们提出了统一的意义表示（UMR），旨在注释文本的语义内容的意义表示。UMR主要基于抽象意义表示（AMR），这是一种最初为英语设计的注释框架，但也借鉴了其他意义表示。UMR将AMR扩展到其他语言，特别是形态复杂，资源少的语言。UMR还为AMR添加了对语义解释至关重要的功能，并通过提出一种伴随的文档级表示来增强AMR，该表示可以捕获语言现象，例如共指以及可能超出句子边界的时间和模态依赖性。
In this paper we present Uniform Meaning Representation (UMR), a meaning representation designed to annotate the semantic content of a text. UMR is primarily based on Abstract Meaning Representation (AMR), an annotation framework initially designed for English, but also draws from other meaning representations. UMR extends AMR to other languages, particularly morphologically complex, low-resource languages. UMR also adds features to AMR that are critical to semantic interpretation and enhances AMR by proposing a companion document-level representation that captures linguistic phenomena such as coreference as well as temporal and modal dependencies that potentially go beyond sentence boundaries.