Sentence Meaning Representations Across Languages: What Can We Learn from Existing Frameworks?

IF 3.7 2区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Z. Žabokrtský, Daniel Zeman, M. Sevcíková
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引用次数: 17

Abstract

This article gives an overview of how sentence meaning is represented in eleven deep-syntactic frameworks, ranging from those based on linguistic theories elaborated for decades to rather lightweight NLP-motivated approaches. We outline the most important characteristics of each framework and then discuss how particular language phenomena are treated across those frameworks, while trying to shed light on commonalities as well as differences.
跨语言的句子意义表示:我们能从现有框架中学到什么?
本文概述了如何在11个深度句法框架中表示句子的意义,这些框架从几十年来基于语言学理论的框架到相当轻量级的nlp驱动的方法。我们概述了每个框架的最重要特征,然后讨论如何在这些框架中处理特定的语言现象,同时试图揭示共性和差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Computational Linguistics
Computational Linguistics 工程技术-计算机:跨学科应用
CiteScore
15.80
自引率
0.00%
发文量
45
审稿时长
>12 weeks
期刊介绍: Computational Linguistics, the longest-running publication dedicated solely to the computational and mathematical aspects of language and the design of natural language processing systems, provides university and industry linguists, computational linguists, AI and machine learning researchers, cognitive scientists, speech specialists, and philosophers with the latest insights into the computational aspects of language research.
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