German in Flux: Detecting Metaphoric Change via Word Entropy

Dominik Schlechtweg, Stefanie Eckmann, Enrico Santus, Sabine Schulte im Walde, Daniel Hole


Abstract
This paper explores the information-theoretic measure entropy to detect metaphoric change, transferring ideas from hypernym detection to research on language change. We build the first diachronic test set for German as a standard for metaphoric change annotation. Our model is unsupervised, language-independent and generalizable to other processes of semantic change.
Anthology ID:
K17-1036
Volume:
Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017)
Month:
August
Year:
2017
Address:
Vancouver, Canada
Venue:
CoNLL
SIG:
SIGNLL
Publisher:
Association for Computational Linguistics
Note:
Pages:
354–367
Language:
URL:
https://www.aclweb.org/anthology/K17-1036
DOI:
10.18653/v1/K17-1036
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PDF:
http://aclanthology.lst.uni-saarland.de/K17-1036.pdf
Presentation:
 K17-1036.Presentation.pdf