ID10M: Idiom Identification in 10 Languages
Simone Tedeschi, Federico Martelli, Roberto Navigli · Findings of the Association for Computational Linguistics: NAACL 2022 · 2022
Idioms are phrases which present a figurative meaning that cannot be (completely) derived by looking at the meaning of their individual components.Identifying and understanding idioms in context is a crucial goal and a key challenge in a wide range of Natural Language Understanding tasks.Although efforts have been undertaken in this direction, the automatic identification and understanding of idioms is still a largely underinvestigated area, especially when operating in a multilingual scenario.In this paper, we address such limitations and put forward several new contributions: we propose a novel multilingual Transformer-based system for the identification of idioms; we produce a highquality automatically-created training dataset in 10 languages, along with a novel manuallycurated evaluation benchmark; finally, we carry out a thorough performance analysis and release our evaluation suite at https:// github.com/Babelscape/ID10M.