众包词汇多样性的词汇多样性
Hadi Khalilia1,2, Jahna Otterbacher3, Gábor Bella4
1Department of Information Engineering and Computer Science, University of Trento, Trento, Italy.
Frontiers in artificial intelligence
|December 22, 2025
概括
本研究引入了一种众包方法,以减少词汇语义资源 (LSR) 中的英语偏差. 在LingoGap平台上识别跨语言的词汇差距,提高语言数据的质量.
科学领域:
- 计算语言学 计算语言学
- 词典写作 词典写作 词典写作
- 文化人类学 文化人类学
背景情况:
- 词法语义资源 (LSR) 对NLP和语言学研究至关重要.
- 现有的LSR经常表现出英语/格鲁-撒克逊文化偏见,缺乏本地概念,并表明无法翻译 (词汇差距).
研究的目的:
- 提出和验证一种新的众包方法来减少LSR偏差.
- 解决跨语言的词汇差距问题,增强语言资源的文化特异性.
主要方法:
- 开发了LingoGap众包平台,用于跨语言的基于微任务的词汇比较.
- 群众工作者确定了同等术语,语言特定术语和词汇差距,专注于文化丰富的领域,如食物和亲属关系.
主要成果:
- 将该方法应用于英语-阿拉伯语 (食品) 和印尼语-班贾尔语 (食品) 术语.
- 确定了英语和阿拉伯语之间的2,140个词汇差距,以及印尼语和班贾尔语之间的951个词汇差距.
结论:
- LingoGap众包方法在识别和减少LSR偏差方面是有效的.
- 该平台是大规模丰富词汇和解决跨语言词汇差距的可行工具.
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