A Report on the FigLang 2022 Shared Task on Understanding Figurative Language

Arkadiy Saakyan, Tuhin Chakrabarty, Debanjan Ghosh, Smaranda Muresan

Abstract
We present the results of the Shared Task on Understanding Figurative Language that we conducted as a part of the 3rd Workshop on Figurative Language Processing (FigLang 2022) at EMNLP 2022. The shared task is based on the FLUTE dataset (Chakrabarty et al., 2022), which consists of NLI pairs containing figurative language along with free text explanations for each NLI instance. The task challenged participants to build models that are able to not only predict the right label for a figurative NLI instance, but also generate a convincing free-text explanation. The participants were able to significantly improve upon provided baselines in both automatic and human evaluation settings. We further summarize the submitted systems and discuss the evaluation results.
Anthology ID:
2022.flp-1.26
Volume:
Proceedings of the 3rd Workshop on Figurative Language Processing (FLP)
Month:
December
Year:
2022
Address:
Abu Dhabi, United Arab Emirates (Hybrid)
Editors:
Debanjan Ghosh, Beata Beigman Klebanov, Smaranda Muresan, Anna Feldman, Soujanya Poria, Tuhin Chakrabarty
Venue:
Fig-Lang
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
178–183
Language:
URL:
https://aclanthology.org/2022.flp-1.26
DOI:
10.18653/v1/2022.flp-1.26
Bibkey:
Cite (ACL):
Arkadiy Saakyan, Tuhin Chakrabarty, Debanjan Ghosh, and Smaranda Muresan. 2022. A Report on the FigLang 2022 Shared Task on Understanding Figurative Language. In Proceedings of the 3rd Workshop on Figurative Language Processing (FLP), pages 178–183, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.
Cite (Informal):
A Report on the FigLang 2022 Shared Task on Understanding Figurative Language (Saakyan et al., Fig-Lang 2022)
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PDF:
https://preview.aclanthology.org/dois-2013-emnlp/2022.flp-1.26.pdf
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