@inproceedings{ranjbar-zeinali-2021-lotus,
    title = "Lotus at {S}em{E}val-2021 Task 2: Combination of {BERT} and Paraphrasing for {E}nglish Word Sense Disambiguation",
    author = "Ranjbar, Niloofar  and
      Zeinali, Hossein",
    editor = "Palmer, Alexis  and
      Schneider, Nathan  and
      Schluter, Natalie  and
      Emerson, Guy  and
      Herbelot, Aurelie  and
      Zhu, Xiaodan",
    booktitle = "Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)",
    month = aug,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest_wac_2008/2021.semeval-1.95/",
    doi = "10.18653/v1/2021.semeval-1.95",
    pages = "724--729",
    abstract = "In this paper, we describe our proposed methods for the multilingual word-in-Context disambiguation task in SemEval-2021. In this task, systems should determine whether a word that occurs in two different sentences is used with the same meaning or not. We proposed several methods using a pre-trained BERT model. In two of them, we paraphrased sentences and add them as input to the BERT, and in one of them, we used WordNet to add some extra lexical information. We evaluated our proposed methods on test data in SemEval- 2021 task 2."
}