Abstract
This paper describes systems submitted to the Metaphor Shared Task at the Second Workshop on Figurative Language Processing. In this submission, we replicate the evaluation of the Bi-LSTM model introduced by Gao et al.(2018) on the VUA corpus in a new setting: TOEFL essays written by non-native English speakers. Our results show that Bi-LSTM models outperform feature-rich linear models on this challenging task, which is consistent with prior findings on the VUA dataset. However, the Bi-LSTM models lag behind the best performing systems in the shared task.- Anthology ID:
- 2020.figlang-1.26
- Volume:
- Proceedings of the Second Workshop on Figurative Language Processing
- Month:
- July
- Year:
- 2020
- Address:
- Online
- Editors:
- Beata Beigman Klebanov, Ekaterina Shutova, Patricia Lichtenstein, Smaranda Muresan, Chee Wee, Anna Feldman, Debanjan Ghosh
- Venue:
- Fig-Lang
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 192–196
- Language:
- URL:
- https://aclanthology.org/2020.figlang-1.26
- DOI:
- 10.18653/v1/2020.figlang-1.26
- Cite (ACL):
- Kevin Kuo and Marine Carpuat. 2020. Evaluating a Bi-LSTM Model for Metaphor Detection in TOEFL Essays. In Proceedings of the Second Workshop on Figurative Language Processing, pages 192–196, Online. Association for Computational Linguistics.
- Cite (Informal):
- Evaluating a Bi-LSTM Model for Metaphor Detection in TOEFL Essays (Kuo & Carpuat, Fig-Lang 2020)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-2/2020.figlang-1.26.pdf