期刊名称：Conference on European Chapter of the Association for Computational Linguistics (EACL)
出版年度：2021
卷号：2021
页码：53-62
语种：English
出版社：ACL Anthology
摘要：We propose a novel method of homonymy-polysemy discrimination for three Indo-European Languages (English, Spanish and Polish). Support vector machines and LASSO logistic regression were successfully used in this task, outperforming baselines. The feature set utilised lemma properties, gloss similarities, graph distances and polysemy patterns. The proposed ML models performed equally well for English and the other two languages (constituting testing data sets). The algorithms not only ruled out most cases of homonymy but also were efficacious in distinguishing between closer and indirect semantic relatedness.
