利用卫星资源改进形态学的UD处理

K. Dobrovoljc, T. Erjavec, Nikola Ljubesic
{"title":"利用卫星资源改进形态学的UD处理","authors":"K. Dobrovoljc, T. Erjavec, Nikola Ljubesic","doi":"10.18653/v1/W19-8004","DOIUrl":null,"url":null,"abstract":"This paper presents the conversion of the reference language resources for Croatian and Slovenian morphology processing to UD morphological specifications. We show that the newly available training corpora and inflectional dictionaries improve the baseline stanfordnlp performance obtained on officially released UD datasets for lemmatization, morphology prediction and dependency parsing, illustrating the potential value of such satellite UD resources for languages with rich morphology.","PeriodicalId":294555,"journal":{"name":"Proceedings of the Third Workshop on Universal Dependencies (UDW, SyntaxFest 2019)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Improving UD processing via satellite resources for morphology\",\"authors\":\"K. Dobrovoljc, T. Erjavec, Nikola Ljubesic\",\"doi\":\"10.18653/v1/W19-8004\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents the conversion of the reference language resources for Croatian and Slovenian morphology processing to UD morphological specifications. We show that the newly available training corpora and inflectional dictionaries improve the baseline stanfordnlp performance obtained on officially released UD datasets for lemmatization, morphology prediction and dependency parsing, illustrating the potential value of such satellite UD resources for languages with rich morphology.\",\"PeriodicalId\":294555,\"journal\":{\"name\":\"Proceedings of the Third Workshop on Universal Dependencies (UDW, SyntaxFest 2019)\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Third Workshop on Universal Dependencies (UDW, SyntaxFest 2019)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18653/v1/W19-8004\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Third Workshop on Universal Dependencies (UDW, SyntaxFest 2019)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18653/v1/W19-8004","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

本文介绍了克罗地亚语和斯洛文尼亚语形态学处理的参考语言资源到UD形态学规范的转换。我们的研究表明,新获得的训练语料库和屈折字典提高了在官方发布的语义语义数据集上获得的基线standfordnlp性能,用于词法化、词法预测和依赖关系分析,说明了这种卫星语义语义资源对具有丰富词法的语言的潜在价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improving UD processing via satellite resources for morphology
This paper presents the conversion of the reference language resources for Croatian and Slovenian morphology processing to UD morphological specifications. We show that the newly available training corpora and inflectional dictionaries improve the baseline stanfordnlp performance obtained on officially released UD datasets for lemmatization, morphology prediction and dependency parsing, illustrating the potential value of such satellite UD resources for languages with rich morphology.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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:481959085
Book学术官方微信