@inproceedings{a5ae62cc01184df2a1e048881d57c582,
title = "LU-BZU at SemEval-2021 Task 2: Word2Vec and Lemma2Vec performance in Arabic Word-in-Context disambiguation",
abstract = "This paper presents a set of experiments to evaluate and compare between the performance of using CBOW Word2Vec and Lemma2Vec models for Arabic Word-in-Context (WiC) disambiguation without using sense inventories or sense embeddings. As part of the SemEval-2021 Shared Task 2 on WiC disambiguation, we used the dev.ar-ar dataset (2k sentence pairs) to decide whether two words in a given sentence pair carry the same meaning. We used two Word2Vec models: Wiki-CBOW, a pre-trained model on Arabic Wikipedia, and another model we trained on large Arabic corpora of about 3 billion tokens. Two Lemma2Vec models was also constructed based on the two Word2Vec models. Each of the four models was then used in the WiC disambiguation task, and then evaluated on the SemEval-2021 test.ar-ar dataset. At the end, we reported the performance of different models and compared between using lemma-based and word-based models.",
author = "Moustafa Al-Hajj and Mustafa Jarrar",
note = "Publisher Copyright: {\textcopyright} 2021 Association for Computational Linguistics.; 15th International Workshop on Semantic Evaluation, SemEval 2021, co-located with The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, ACL-IJCNLP 2021 ; Conference date: 05-08-2021 Through 06-08-2021",
year = "2021",
doi = "10.18653/v1/2021.semeval-1.99",
language = "English",
series = "SemEval 2021 - 15th International Workshop on Semantic Evaluation, Proceedings of the Workshop",
publisher = "Association for Computational Linguistics (ACL)",
pages = "748--755",
editor = "Alexis Palmer and Nathan Schneider and Natalie Schluter and Guy Emerson and Aurelie Herbelot and Xiaodan Zhu",
booktitle = "SemEval 2021 - 15th International Workshop on Semantic Evaluation, Proceedings of the Workshop",
address = "United States",
}