Abstract
Research in linguistic typology has shown that languages do not fall into the neat morphological types (synthetic vs. analytic) postulated in the 19th century. Instead, analytic and synthetic must be viewed as two poles of a continuum and languages may show a mix analytic and synthetic strategies to different degrees. Unfortunately, empirical studies that offer a more fine-grained morphological classification of languages based on these parameters remain few. In this paper, we build upon previous research by Liu & Xu (2011) and investigate the possibility of inferring information on morphological complexity from syntactic dependency networks.- Anthology ID:
- 2021.sigtyp-1.2
- Volume:
- Proceedings of the Third Workshop on Computational Typology and Multilingual NLP
- Month:
- June
- Year:
- 2021
- Address:
- Online
- Venue:
- SIGTYP
- SIG:
- SIGTYP
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 10–22
- Language:
- URL:
- https://aclanthology.org/2021.sigtyp-1.2
- DOI:
- 10.18653/v1/2021.sigtyp-1.2
- Cite (ACL):
- Guglielmo Inglese and Luca Brigada Villa. 2021. Inferring Morphological Complexity from Syntactic Dependency Networks: A Test. In Proceedings of the Third Workshop on Computational Typology and Multilingual NLP, pages 10–22, Online. Association for Computational Linguistics.
- Cite (Informal):
- Inferring Morphological Complexity from Syntactic Dependency Networks: A Test (Inglese & Brigada Villa, SIGTYP 2021)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/2021.sigtyp-1.2.pdf
- Code
- bavagliladri/tb2net
- Data
- Universal Dependencies