Quantitative Methods in Morphology: Corpora and Other “Big Data” Approaches

M. Marelli
{"title":"Quantitative Methods in Morphology: Corpora and Other “Big Data” Approaches","authors":"M. Marelli","doi":"10.1093/acrefore/9780199384655.013.602","DOIUrl":null,"url":null,"abstract":"Corpora are an all-important resource in linguistics, as they constitute the primary source for large-scale examples of language usage. This has been even more evident in recent years, with the increasing availability of texts in digital format leading more and more corpus linguistics toward a “big data” approach. As a consequence, the quantitative methods adopted in the field are becoming more sophisticated and various.\n When it comes to morphology, corpora represent a primary source of evidence to describe morpheme usage, and in particular how often a particular morphological pattern is attested in a given language. There is hence a tight relation between corpus linguistics and the study of morphology and the lexicon. This relation, however, can be considered bi-directional. On the one hand, corpora are used as a source of evidence to develop metrics and train computational models of morphology: by means of corpus data it is possible to quantitatively characterize morphological notions such as productivity, and corpus data are fed to computational models to capture morphological phenomena at different levels of description. On the other hand, morphology has also been applied as an organization principle to corpora. Annotations of linguistic data often adopt morphological notions as guidelines. The resulting information, either obtained from human annotators or relying on automatic systems, makes corpora easier to analyze and more convenient to use in a number of applications.","PeriodicalId":331003,"journal":{"name":"Oxford Research Encyclopedia of Linguistics","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Oxford Research Encyclopedia of Linguistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/acrefore/9780199384655.013.602","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

Corpora are an all-important resource in linguistics, as they constitute the primary source for large-scale examples of language usage. This has been even more evident in recent years, with the increasing availability of texts in digital format leading more and more corpus linguistics toward a “big data” approach. As a consequence, the quantitative methods adopted in the field are becoming more sophisticated and various. When it comes to morphology, corpora represent a primary source of evidence to describe morpheme usage, and in particular how often a particular morphological pattern is attested in a given language. There is hence a tight relation between corpus linguistics and the study of morphology and the lexicon. This relation, however, can be considered bi-directional. On the one hand, corpora are used as a source of evidence to develop metrics and train computational models of morphology: by means of corpus data it is possible to quantitatively characterize morphological notions such as productivity, and corpus data are fed to computational models to capture morphological phenomena at different levels of description. On the other hand, morphology has also been applied as an organization principle to corpora. Annotations of linguistic data often adopt morphological notions as guidelines. The resulting information, either obtained from human annotators or relying on automatic systems, makes corpora easier to analyze and more convenient to use in a number of applications.
形态学的定量方法:语料库和其他“大数据”方法
语料库是语言学中非常重要的资源,因为它们构成了大量语言使用实例的主要来源。近年来,随着数字格式文本可用性的增加,这一点更加明显,导致越来越多的语料库语言学转向“大数据”方法。因此,该领域采用的定量方法变得更加复杂和多样化。当涉及到形态学时,语料库代表了描述语素使用的主要证据来源,特别是在给定语言中特定的形态学模式被证明的频率。因此,语料库语言学与词法和词汇的研究有着密切的联系。然而,这种关系可以被认为是双向的。一方面,语料库被用作开发度量和训练形态学计算模型的证据来源:通过语料库数据,可以定量表征诸如生产力之类的形态学概念,语料库数据被馈送到计算模型中,以捕捉不同描述层次的形态学现象。另一方面,形态学也被作为一种组织原理应用于语料库。语言学资料的注释通常采用形态学概念作为指导。由此产生的信息,无论是从人类注释者那里获得的,还是依赖于自动系统的,都使语料库更容易分析,更方便在许多应用程序中使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信