fsca

IF 1.1 0 LANGUAGE & LINGUISTICS
Nathan Vandeweerd
{"title":"fsca","authors":"Nathan Vandeweerd","doi":"10.1075/ijlcr.20018.van","DOIUrl":null,"url":null,"abstract":"\n This article reports on an open-source R package for the extraction of syntactic units from dependency-parsed\n French texts. To evaluate the reliability of the package, syntactic units were extracted from a corpus of L2 French and were\n compared to units extracted manually from the same corpus. The f-score of the extracted units ranged from 0.53–0.97. Although\n units were not always identical between the two methods, manual and automatically-derived syntactic complexity measures were\n strongly and significantly correlated (ρ = 0.62–0.97, p < 0.001), suggesting that this\n package may be a suitable replacement for manual annotation in some cases where manual annotation is not possible but that care\n should be used in interpreting the measures based on these units.","PeriodicalId":29715,"journal":{"name":"International Journal of Learner Corpus Research","volume":null,"pages":null},"PeriodicalIF":1.1000,"publicationDate":"2021-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Learner Corpus Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1075/ijlcr.20018.van","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"LANGUAGE & LINGUISTICS","Score":null,"Total":0}
引用次数: 3

Abstract

This article reports on an open-source R package for the extraction of syntactic units from dependency-parsed French texts. To evaluate the reliability of the package, syntactic units were extracted from a corpus of L2 French and were compared to units extracted manually from the same corpus. The f-score of the extracted units ranged from 0.53–0.97. Although units were not always identical between the two methods, manual and automatically-derived syntactic complexity measures were strongly and significantly correlated (ρ = 0.62–0.97, p < 0.001), suggesting that this package may be a suitable replacement for manual annotation in some cases where manual annotation is not possible but that care should be used in interpreting the measures based on these units.
fsca
本文介绍了一个开源R包,用于从依赖项解析的法语文本中提取语法单元。为了评估包的可靠性,从L2法语语料库中提取句法单位,并将其与从同一语料库中手动提取的单位进行比较。提取单位的f值范围为0.53 ~ 0.97。尽管两种方法之间的单位并不总是相同的,但手工和自动派生的语法复杂性度量是强烈且显著相关的(ρ = 0.62-0.97,p < 0.001),这表明在某些情况下,手工注释是不可能的,但在解释基于这些单位的度量时应该小心使用,这个包可能是手动注释的合适替代品。
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
CiteScore
3.40
自引率
27.30%
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:481959085
Book学术官方微信