Towards Universal Segmentations: UniSegments 1.0
Zdeněk Žabokrtský, Niyati Bafna, Jan Bodnár, Lukáš Kyjánek, Emil Svoboda, Magda Ševčíková, Jonáš Vidra
Abstract
Our work aims at developing a multilingual data resource for morphological segmentation. We present a survey of 17 existing data resources relevant for segmentation in 32 languages, and analyze diversity of how individual linguistic phenomena are captured across them. Inspired by the success of Universal Dependencies, we propose a harmonized scheme for segmentation representation, and convert the data from the studied resources into this common scheme. Harmonized versions of resources available under free licenses are published as a collection called UniSegments 1.0.- Anthology ID:
- 2022.lrec-1.122
- Volume:
- Proceedings of the Thirteenth Language Resources and Evaluation Conference
- Month:
- June
- Year:
- 2022
- Address:
- Marseille, France
- Editors:
- Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 1137–1149
- Language:
- URL:
- https://aclanthology.org/2022.lrec-1.122
- DOI:
- Cite (ACL):
- Zdeněk Žabokrtský, Niyati Bafna, Jan Bodnár, Lukáš Kyjánek, Emil Svoboda, Magda Ševčíková, and Jonáš Vidra. 2022. Towards Universal Segmentations: UniSegments 1.0. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 1137–1149, Marseille, France. European Language Resources Association.
- Cite (Informal):
- Towards Universal Segmentations: UniSegments 1.0 (Žabokrtský et al., LREC 2022)
- PDF:
- https://preview.aclanthology.org/teach-a-man-to-fish/2022.lrec-1.122.pdf
- Data
- CELEX