Evaluating a Bi-LSTM Model for Metaphor Detection in TOEFL Essays

Kevin Kuo, Marine Carpuat


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
Venues:
ACL | Fig-Lang | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
192–196
Language:
URL:
https://www.aclweb.org/anthology/2020.figlang-1.26
DOI:
10.18653/v1/2020.figlang-1.26
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PDF:
http://aclanthology.lst.uni-saarland.de/2020.figlang-1.26.pdf
Video:
 http://slideslive.com/38929721