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:73-80
语种:English
出版社:ACL Anthology
摘要:Words are defined based on their meanings in various ways in different resources. Aligning word senses across monolingual lexicographic resources increases domain coverage and enables integration and incorporation of data. In this paper, we explore the application of classification methods using manually-extracted features along with representation learning techniques in the task of word sense alignment and semantic relationship detection. We demonstrate that the performance of classification methods dramatically varies based on the type of semantic relationships due to the nature of the task but outperforms the previous experiments.