WECA: A WordNet-Encoded Collocation-Attention Network for Homographic Pun Recognition

Yufeng Diao, Hongfei Lin, Di Wu, Liang Yang, Kan Xu, Zhihao Yang, Jian Wang, Shaowu Zhang, Bo Xu, Dongyu Zhang

Abstract
Homographic puns have a long history in human writing, widely used in written and spoken literature, which usually occur in a certain syntactic or stylistic structure. How to recognize homographic puns is an important research. However, homographic pun recognition does not solve very well in existing work. In this work, we first use WordNet to understand and expand word embedding for settling the polysemy of homographic puns, and then propose a WordNet-Encoded Collocation-Attention network model (WECA) which combined with the context weights for recognizing the puns. Our experiments on the SemEval2017 Task7 and Pun of the Day demonstrate that the proposed model is able to distinguish between homographic pun and non-homographic pun texts. We show the effectiveness of the model to present the capability of choosing qualitatively informative words. The results show that our model achieves the state-of-the-art performance on homographic puns recognition.
Anthology ID:
D18-1272
Volume:
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
Month:
October-November
Year:
2018
Address:
Brussels, Belgium
Editors:
Ellen Riloff, David Chiang, Julia Hockenmaier, Jun’ichi Tsujii
Venue:
EMNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
2507–2516
Language:
URL:
https://aclanthology.org/D18-1272
DOI:
10.18653/v1/D18-1272
Bibkey:
Cite (ACL):
Yufeng Diao, Hongfei Lin, Di Wu, Liang Yang, Kan Xu, Zhihao Yang, Jian Wang, Shaowu Zhang, Bo Xu, and Dongyu Zhang. 2018. WECA: A WordNet-Encoded Collocation-Attention Network for Homographic Pun Recognition. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 2507–2516, Brussels, Belgium. Association for Computational Linguistics.
Cite (Informal):
WECA: A WordNet-Encoded Collocation-Attention Network for Homographic Pun Recognition (Diao et al., EMNLP 2018)
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https://preview.aclanthology.org/ml4al-ingestion/D18-1272.pdf
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