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
- Editors:
- Roger Levy, Lucia Specia
- Venue:
- CoNLL
- SIG:
- SIGNLL
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 354–367
- Language:
- URL:
- https://aclanthology.org/K17-1036
- DOI:
- 10.18653/v1/K17-1036
- Cite (ACL):
- Dominik Schlechtweg, Stefanie Eckmann, Enrico Santus, Sabine Schulte im Walde, and Daniel Hole. 2017. German in Flux: Detecting Metaphoric Change via Word Entropy. In Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017), pages 354–367, Vancouver, Canada. Association for Computational Linguistics.
- Cite (Informal):
- German in Flux: Detecting Metaphoric Change via Word Entropy (Schlechtweg et al., CoNLL 2017)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/K17-1036.pdf
- Code
- Garrafao/MetaphoricChange