Unsupervised Detection of Metaphorical Adjective-Noun Pairs

Malay Pramanick, Pabitra Mitra


Abstract
Metaphor is a popular figure of speech. Popularity of metaphors calls for their automatic identification and interpretation. Most of the unsupervised methods directed at detection of metaphors use some hand-coded knowledge. We propose an unsupervised framework for metaphor detection that does not require any hand-coded knowledge. We applied clustering on features derived from Adjective-Noun pairs for classifying them into two disjoint classes. We experimented with adjective-noun pairs of a popular dataset annotated for metaphors and obtained an accuracy of 72.87% with k-means clustering algorithm.
Anthology ID:
W18-0909
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:
76–80
Language:
URL:
https://aclanthology.org/W18-0909
DOI:
10.18653/v1/W18-0909
Bibkey:
Cite (ACL):
Malay Pramanick and Pabitra Mitra. 2018. Unsupervised Detection of Metaphorical Adjective-Noun Pairs. In Proceedings of the Workshop on Figurative Language Processing, pages 76–80, New Orleans, Louisiana. Association for Computational Linguistics.
Cite (Informal):
Unsupervised Detection of Metaphorical Adjective-Noun Pairs (Pramanick & Mitra, Fig-Lang 2018)
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PDF:
https://aclanthology.org/W18-0909.pdf