计算语言学中的组合性

IF 3 1区 文学 0 LANGUAGE & LINGUISTICS
L. Donatelli, Alexander Koller
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引用次数: 2

摘要

在现代计算语言学的许多任务中,神经模型大大优于基于语法的模型。这就提出了一个问题,即语言原则,如组合性原则,是否仍然具有建模工具的价值。我们回顾了最近的文献,发现虽然对组合性的过于严格的解释使得在语义分析任务中难以实现广泛的覆盖,但组合性对于模型从有限的数据中学习正确的语言概括仍然是必要的。调和这两种品质需要仔细探索一个新颖的设计空间;我们还回顾了一些可能有助于这一探索的最新结果。预计《语言学年度评论》第9卷的最终在线出版日期为2023年1月。修订后的估计数请参阅http://www.annualreviews.org/page/journal/pubdates。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Compositionality in Computational Linguistics
Neural models greatly outperform grammar-based models across many tasks in modern computational linguistics. This raises the question of whether linguistic principles, such as the Principle of Compositionality, still have value as modeling tools. We review the recent literature and find that while an overly strict interpretation of compositionality makes it hard to achieve broad coverage in semantic parsing tasks, compositionality is still necessary for a model to learn the correct linguistic generalizations from limited data. Reconciling both of these qualities requires the careful exploration of a novel design space; we also review some recent results that may help in this exploration. Expected final online publication date for the Annual Review of Linguistics, Volume 9 is January 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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来源期刊
CiteScore
7.20
自引率
6.20%
发文量
37
期刊介绍: The Annual Review of Linguistics, in publication since 2015, covers significant developments in the field of linguistics, including phonetics, phonology, morphology, syntax, semantics, pragmatics, and their interfaces. Reviews synthesize advances in linguistic theory, sociolinguistics, psycholinguistics, neurolinguistics, language change, biology and evolution of language, typology, as well as applications of linguistics in many domains.
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