Detecting Figurative Word Occurrences Using Recurrent Neural Networks

Agnieszka Mykowiecka, Aleksander Wawer, Malgorzata Marciniak


Abstract
The paper addresses detection of figurative usage of words in English text. The chosen method was to use neural nets fed by pretrained word embeddings. The obtained results show that simple solutions, based on words embeddings only, are comparable to complex solutions, using many sources of information which are not available for languages less-studied than English.
Anthology ID:
W18-0916
Volume:
Proceedings of the Workshop on Figurative Language Processing
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Editors:
Beata Beigman Klebanov, Ekaterina Shutova, Patricia Lichtenstein, Smaranda Muresan, Chee Wee
Venue:
Fig-Lang
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
124–127
Language:
URL:
https://preview.aclanthology.org/build-pipeline-with-new-library/W18-0916/
DOI:
10.18653/v1/W18-0916
Bibkey:
Cite (ACL):
Agnieszka Mykowiecka, Aleksander Wawer, and Malgorzata Marciniak. 2018. Detecting Figurative Word Occurrences Using Recurrent Neural Networks. In Proceedings of the Workshop on Figurative Language Processing, pages 124–127, New Orleans, Louisiana. Association for Computational Linguistics.
Cite (Informal):
Detecting Figurative Word Occurrences Using Recurrent Neural Networks (Mykowiecka et al., Fig-Lang 2018)
Copy Citation:
PDF:
https://preview.aclanthology.org/build-pipeline-with-new-library/W18-0916.pdf