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An Empirical Study of Span Representations in Argumentation Structure Parsing

机译:参数结构解析中跨度表示的实证研究

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For several natural language processing (NLP) tasks, span representation is attracting considerable attention as a promising new technique; a common basis for an effective design has been established. With such basis, exploring task-dependent extensions for argumentation structure parsing (ASP) becomes an interesting research direction. This study investigates (ⅰ) span representation originally developed for other NLP tasks and (ⅱ) a simple task-dependent extension for ASP. Our extensive experiments and analysis show that these representations yield high performance for ASP and provide some challenging types of instances to be parsed.
机译:对于几种自然语言处理(NLP)任务,跨距表示作为一种有前途的新技术正吸引着相当多的关注。建立有效设计的共同基础。在这样的基础上,探索与任务相关的扩展以进行论证结构分析(ASP)成为一个有趣的研究方向。本研究调查(ⅰ)最初为其他NLP任务开发的跨度表示形式,以及(ⅱ)ASP的简单的依赖于任务的扩展。我们广泛的实验和分析表明,这些表示形式为ASP带来了高性能,并提供了一些具有挑战性的实例类型进行解析。

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