Inferring Morphological Complexity from Syntactic Dependency Networks: A Test

Guglielmo Inglese, Luca Brigada Villa


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
Editors:
Ekaterina Vylomova, Elizabeth Salesky, Sabrina Mielke, Gabriella Lapesa, Ritesh Kumar, Harald Hammarström, Ivan Vulić, Anna Korhonen, Roi Reichart, Edoardo Maria Ponti, Ryan Cotterell
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
Bibkey:
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)
Copy Citation:
PDF:
https://aclanthology.org/2021.sigtyp-1.2.pdf
Code
 bavagliladri/tb2net
Data
Universal Dependencies