Daniel Hole

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2017

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German in Flux: Detecting Metaphoric Change via Word Entropy
Dominik Schlechtweg | Stefanie Eckmann | Enrico Santus | Sabine Schulte im Walde | Daniel Hole
Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017)

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.
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