论英语定语从句的计算建模

Pub Date : 2023-01-01 DOI:10.1515/opli-2022-0246
Sandiway Fong, Jason Ginsburg
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引用次数: 0

摘要

即使在这个需要大量训练数据集的重参数统计建模的时代,我们相信明确的语法符号模型有很多东西可以提供,特别是当涉及到使用最少数量的参数建模复杂的句法现象时。解释性符号模型的目标是明确表示一组允许短语结构的最小特征,因此,对于寻求参数高效语言模型的工程师来说,它们应该是感兴趣的。关系从句在语言学中有着悠久的研究历史。我们对极简程序框架中各种基本英语关系子句的形成进行了特征驱动的描述,这些子句是精确定义的,描述充分的,并且在某种意义上计算可行,因为我们没有观察到词法数组中头的数量呈指数级增长。在之前的工作之后,我们假设一个涉及uT特征和uRel特征的分析,可能同时进行。在本文中,我们将展示该分析的详细机械实现,并描述为标准英语中的that、which和who/whom亲戚计算的结构。
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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On the computational modeling of English relative clauses
Abstract Even in this era of parameter-heavy statistical modeling requiring large training datasets, we believe explicit symbolic models of grammar have much to offer, especially when it comes to modeling complex syntactic phenomena using a minimal number of parameters. It is the goal of explanatory symbolic models to make explicit a minimal set of features that license phrase structure, and thus, they should be of interest to engineers seeking parameter-efficient language models. Relative clauses have been much studied and have a long history in linguistics. We contribute a feature-driven account of the formation of a variety of basic English relative clauses in the Minimalist Program framework that is precisely defined, descriptively adequate, and computationally feasible in the sense that we have not observed an exponential scaling with the number of heads in the Lexical Array. Following previous work, we assume an analysis involving a uT feature and uRel feature, possibly simultaneously valued. In this article, we show a detailed mechanical implementation of this analysis and describe the structures computed for that , which , and who/whom relatives for standard English.
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