Contextualized knowledge base sense embeddings in word sense disambiguation
Published in ICDAR, 2021
Recommended citation: Saeidi, Mozhgan and Milios, Evangelos and Zeh, Norbert. (2021). " booktitle={Document Analysis and Recognition--ICDAR 2021 Workshops: Lausanne, Switzerland, September 5--10, 2021, Proceedings, Part II 16}, pages={174--186}, year={2021}, organization={Springer} Journal 1. 1(3). https://link.springer.com/chapter/10.1007/978-3-030-86159-9_37
Contextualized sense embedding has been shown to carry useful semantic information to improve the final results of various Natural Language Processing tasks. However, it is still challenging to integrate them with the information of the knowledge base, which is lacking in current state-of-the-art representations. This integration is helpful in NLP tasks, specifically in the lexical ambiguity problem. In this paper, we present C-KASE (Contextualized-Knowledge base Aware Sense Embedding), a novel approach to producing sense embeddings for the lexical meanings within a lexical knowledge base.