Abstract
In Jäger (2019) a computational framework was defined to start from parallel word lists of related languages and infer the corresponding vocabulary of the shared proto-language. The SIGTYP 2022 Shared Task is closely related. The main difference is that what is to be reconstructed is not the proto-form but an unknown word from an extant language. The system described here is a re-implementation of the tools used in the mentioned paper, adapted to the current task.- Anthology ID:
- 2022.sigtyp-1.8
- Volume:
- Proceedings of the 4th Workshop on Research in Computational Linguistic Typology and Multilingual NLP
- Month:
- July
- Year:
- 2022
- Address:
- Seattle, Washington
- Editors:
- Ekaterina Vylomova, Edoardo Ponti, Ryan Cotterell
- Venue:
- SIGTYP
- SIG:
- SIGTYP
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 63–69
- Language:
- URL:
- https://aclanthology.org/2022.sigtyp-1.8
- DOI:
- 10.18653/v1/2022.sigtyp-1.8
- Cite (ACL):
- Gerhard Jäger. 2022. Bayesian Phylogenetic Cognate Prediction. In Proceedings of the 4th Workshop on Research in Computational Linguistic Typology and Multilingual NLP, pages 63–69, Seattle, Washington. Association for Computational Linguistics.
- Cite (Informal):
- Bayesian Phylogenetic Cognate Prediction (Jäger, SIGTYP 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2022.sigtyp-1.8.pdf