俄语的三部分历时语义变化数据集

Andrey Kutuzov, Lidia Pivovarova
{"title":"俄语的三部分历时语义变化数据集","authors":"Andrey Kutuzov, Lidia Pivovarova","doi":"10.18653/v1/2021.lchange-1.2","DOIUrl":null,"url":null,"abstract":"We present a manually annotated lexical semantic change dataset for Russian: RuShiftEval. Its novelty is ensured by a single set of target words annotated for their diachronic semantic shifts across three time periods, while the previous work either used only two time periods, or different sets of target words. The paper describes the composition and annotation procedure for the dataset. In addition, it is shown how the ternary nature of RuShiftEval allows to trace specific diachronic trajectories: ‘changed at a particular time period and stable afterwards’ or ‘was changing throughout all time periods’. Based on the analysis of the submissions to the recent shared task on semantic change detection for Russian, we argue that correctly identifying such trajectories can be an interesting sub-task itself.","PeriodicalId":120650,"journal":{"name":"Workshop on Computational Approaches to Historical Language Change","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Three-part diachronic semantic change dataset for Russian\",\"authors\":\"Andrey Kutuzov, Lidia Pivovarova\",\"doi\":\"10.18653/v1/2021.lchange-1.2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a manually annotated lexical semantic change dataset for Russian: RuShiftEval. Its novelty is ensured by a single set of target words annotated for their diachronic semantic shifts across three time periods, while the previous work either used only two time periods, or different sets of target words. The paper describes the composition and annotation procedure for the dataset. In addition, it is shown how the ternary nature of RuShiftEval allows to trace specific diachronic trajectories: ‘changed at a particular time period and stable afterwards’ or ‘was changing throughout all time periods’. Based on the analysis of the submissions to the recent shared task on semantic change detection for Russian, we argue that correctly identifying such trajectories can be an interesting sub-task itself.\",\"PeriodicalId\":120650,\"journal\":{\"name\":\"Workshop on Computational Approaches to Historical Language Change\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-06-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Workshop on Computational Approaches to Historical Language Change\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18653/v1/2021.lchange-1.2\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Workshop on Computational Approaches to Historical Language Change","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18653/v1/2021.lchange-1.2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

摘要

我们提出了一个手动标注的俄语词汇语义变化数据集:RuShiftEval。它的新颖性是通过在三个时间段内对目标词的历时语义变化进行注释来保证的,而以前的工作要么只使用两个时间段,要么使用不同的目标词集。本文描述了数据集的组成和标注过程。此外,它还显示了RuShiftEval的三元性质如何允许追踪特定的历时轨迹:“在特定时间段发生变化,之后稳定”或“在所有时间段都在变化”。基于对最近关于俄语语义变化检测的共享任务提交的分析,我们认为正确识别这些轨迹本身可能是一个有趣的子任务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Three-part diachronic semantic change dataset for Russian
We present a manually annotated lexical semantic change dataset for Russian: RuShiftEval. Its novelty is ensured by a single set of target words annotated for their diachronic semantic shifts across three time periods, while the previous work either used only two time periods, or different sets of target words. The paper describes the composition and annotation procedure for the dataset. In addition, it is shown how the ternary nature of RuShiftEval allows to trace specific diachronic trajectories: ‘changed at a particular time period and stable afterwards’ or ‘was changing throughout all time periods’. Based on the analysis of the submissions to the recent shared task on semantic change detection for Russian, we argue that correctly identifying such trajectories can be an interesting sub-task itself.
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:604180095
Book学术官方微信