@inproceedings{itkonen-etal-2022-helsinki,
    title = "{H}elsinki-{NLP} at {S}em{E}val-2022 Task 2: A Feature-Based Approach to Multilingual Idiomaticity Detection",
    author = {Itkonen, Sami  and
      Tiedemann, J{\"o}rg  and
      Creutz, Mathias},
    editor = "Emerson, Guy  and
      Schluter, Natalie  and
      Stanovsky, Gabriel  and
      Kumar, Ritesh  and
      Palmer, Alexis  and
      Schneider, Nathan  and
      Singh, Siddharth  and
      Ratan, Shyam",
    booktitle = "Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)",
    month = jul,
    year = "2022",
    address = "Seattle, United States",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2022.semeval-1.14/",
    doi = "10.18653/v1/2022.semeval-1.14",
    pages = "122--134",
    abstract = "This paper describes the University of Helsinki submission to the SemEval 2022 task on multilingual idiomaticity detection. Our system utilizes several models made available by HuggingFace, along with the baseline BERT model for the task. We focus on feature engineering based on properties that typically characterize idiomatic expressions. The additional features lead to improvements over the baseline and the final submission achieves 15th place out of 20 submissions. The paper provides error analysis of our model including visualisations of the contributions of individual features."
}