Assessing Corpus Evidence for Formal and Psycholinguistic Constraints on Nonprojectivity

IF 3.7 2区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Himanshu Yadav, Samar Husain, Richard Futrell
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引用次数: 3

Abstract

Abstract Formal constraints on crossing dependencies have played a large role in research on the formal complexity of natural language grammars and parsing. Here we ask whether the apparent evidence for constraints on crossing dependencies in treebanks might arise because of independent constraints on trees, such as low arity and dependency length minimization. We address this question using two sets of experiments. In Experiment 1, we compare the distribution of formal properties of crossing dependencies, such as gap degree, between real trees and baseline trees matched for rate of crossing dependencies and various other properties. In Experiment 2, we model whether two dependencies cross, given certain psycholinguistic properties of the dependencies. We find surprisingly weak evidence for constraints originating from the mild context-sensitivity literature (gap degree and well-nestedness) beyond what can be explained by constraints on rate of crossing dependencies, topological properties of the trees, and dependency length. However, measures that have emerged from the parsing literature (e.g., edge degree, end-point crossings, and heads’ depth difference) differ strongly between real and random trees. Modeling results show that cognitive metrics relating to information locality and working-memory limitations affect whether two dependencies cross or not, but they do not fully explain the distribution of crossing dependencies in natural languages. Together these results suggest that crossing constraints are better characterized by processing pressures than by mildly context-sensitive constraints.
评估语料库证据对非投射性的形式和心理语言学约束
摘要交叉依赖的形式约束在自然语言语法和解析的形式复杂性研究中发挥了重要作用。在这里,我们询问树库中交叉依赖性约束的明显证据是否可能是因为树上的独立约束而出现的,例如低arity和依赖长度最小化。我们用两组实验来解决这个问题。在实验1中,我们比较了真实树和基线树之间交叉依赖关系的形式性质的分布,如间隙度,这些树与交叉依赖关系率和其他各种性质相匹配。在实验2中,我们对两个依赖关系是否交叉进行建模,给定依赖关系的某些心理语言学特性。我们发现,来自温和上下文敏感性文献的约束(间隙度和良好嵌套性)的证据出奇地弱,超出了交叉依赖率、树的拓扑性质和依赖长度的约束所能解释的范围。然而,解析文献中出现的度量(例如,边缘度、端点交叉和头部深度差)在真实树和随机树之间存在很大差异。建模结果表明,与信息局部性和工作记忆限制相关的认知指标会影响两种依赖关系是否交叉,但它们并不能完全解释交叉依赖关系在自然语言中的分布。总之,这些结果表明,处理压力比轻度上下文敏感的约束更能表征交叉约束。
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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