Formal Basis of a Language Universal

IF 3.7 2区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Computational Linguistics Pub Date : 2021-04-01 DOI:10.1162/coli_a_00394
M. Stanojevic, M. Steedman
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引用次数: 8

Abstract

Abstract Steedman (2020) proposes as a formal universal of natural language grammar that grammatical permutations of the kind that have given rise to transformational rules are limited to a class known to mathematicians and computer scientists as the “separable” permutations. This class of permutations is exactly the class that can be expressed in combinatory categorial grammars (CCGs). The excluded non-separable permutations do in fact seem to be absent in a number of studies of crosslinguistic variation in word order in nominal and verbal constructions. The number of permutations that are separable grows in the number n of lexical elements in the construction as the Large Schröder Number Sn−1. Because that number grows much more slowly than the n! number of all permutations, this generalization is also of considerable practical interest for computational applications such as parsing and machine translation. The present article examines the mathematical and computational origins of this restriction, and the reason it is exactly captured in CCG without the imposition of any further constraints.
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通用语言的形式基础
Steedman(2020)提出,作为自然语言语法的一种形式普遍性,产生转换规则的那种语法排列仅限于数学家和计算机科学家称为“可分离”排列的一类。这类排列正是可以用组合范畴语法(ccg)表示的一类。被排除在外的不可分排列实际上在许多关于词序在名义和言语结构中的跨语言变化的研究中似乎并不存在。在结构中,可分离排列的数目随着词法元素的数目n的增加而增加,如Schröder number Sn−1。因为这个数的增长速度比n慢得多!所有排列的数目,这种泛化对于解析和机器翻译等计算应用也有相当大的实际意义。本文考察了这一限制的数学和计算起源,以及在没有施加任何进一步约束的情况下在CCG中准确捕获它的原因。
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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