Studying Taxonomy Enrichment on Diachronic WordNet Versions
Studying Taxonomy Enrichment on Diachronic WordNet Versions
复制标题
研究历时 WordNet 版本的分类丰富
DOI：
10.18653/v1/2020.coling-main.276
复制
发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Natalia V. Loukachevitch
中科院分区：
文献类型：
--
作者：
Irina Nikishina;Alexander Panchenko;V. Logacheva;Natalia V. Loukachevitch
在大量的NLP任务中，本体、分类法和同义词表一直是非常需要的。然而，大多数研究都集中在词汇资源的创造上，而不是对现有词汇资源的维护和更新。在这篇文章中，我们讨论了分类丰富的问题。也就是说，我们探索了在资源匮乏的情况下扩展分类法的可能性，并提出了几种适用于大量语言的方法。我们还创建了用于训练和评估分类丰富系统的新的英语和俄语数据集，并描述了为其他语言创建此类数据集的技术。
Ontologies, taxonomies, and thesauri have always been in high demand in a large number of NLP tasks. However, most studies are focused on the creation of lexical resources rather than the maintenance of the existing ones and keeping them up-to-date. In this paper, we address the problem of taxonomy enrichment. Namely, we explore the possibilities of taxonomy extension in a resource-poor setting and present several methods which are applicable to a large number of languages. We also create novel English and Russian datasets for training and evaluating taxonomy enrichment systems and describe a technique of creating such datasets for other languages.