Helsinki-NLP at SemEval-2022 Task 2: A Feature-Based Approach to Multilingual Idiomaticity Detection

Sami Itkonen, Jörg Tiedemann, Mathias Creutz


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.
Anthology ID:
2022.semeval-1.14
Volume:
Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
Month:
July
Year:
2022
Address:
Seattle, United States
Editors:
Guy Emerson, Natalie Schluter, Gabriel Stanovsky, Ritesh Kumar, Alexis Palmer, Nathan Schneider, Siddharth Singh, Shyam Ratan
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
122–134
Language:
URL:
https://aclanthology.org/2022.semeval-1.14
DOI:
10.18653/v1/2022.semeval-1.14
Bibkey:
Cite (ACL):
Sami Itkonen, Jörg Tiedemann, and Mathias Creutz. 2022. Helsinki-NLP at SemEval-2022 Task 2: A Feature-Based Approach to Multilingual Idiomaticity Detection. In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022), pages 122–134, Seattle, United States. Association for Computational Linguistics.
Cite (Informal):
Helsinki-NLP at SemEval-2022 Task 2: A Feature-Based Approach to Multilingual Idiomaticity Detection (Itkonen et al., SemEval 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.semeval-1.14.pdf
Video:
 https://aclanthology.org/2022.semeval-1.14.mp4